Bmw Essay Example | Topics and Well Written Essays - 1250 words

Bmw - Essay Example From the promoting side three improvements make the requirement for data more noteworthy now than before: worldwide showcasing, the client situated advertising approach and the nonprice rivalry. Data changes the money related choices represented by the numbers into business choices dependent on the likelihood of option vital suppositions in this way it necessitates that the business has planned a procedure and this technique and its suspicions are tested. Along these lines, the association needs to consistently improve so as to remain and get hostile. The administration requires deals information particularly up-to-the moment provides details regarding current deals. It needs to have exact information on stock degrees of items, it needs data on client profiles (monetary and individual information), on promoting use, on customers’ observation about the organization and its items, on industry deals and pieces of the overall industry, on staff’s preparing needs, on budgetary parts of the organization (obligations, advances, income, planning and so forth.), on R&D and on creation line prerequisites. The BMW Group follows the effective elements system for example the natural well disposed vehicle creation and the client direction. On account of the utilization of adaptable working techniques and working-time accounts, the BMW Group coordinates its creation limits exceptionally proficiently to changes sought after on the different deals markets. Distinguish a case of every one of key, strategic and operational choices which may be/have been taken by your picked business. Clarify why these choices are separately key, strategic and operational. 18 imprints Number ONE expresses our case to administration, its letters O, N and E represent Opportunities, New and Efficiency: we need to benefit as much as possible from new chances and accomplish new degrees of productivity. Basically, the name Number ONE represents all that we do in connection

Principle Agent Moral Hazard

The significant issue was that the business banks overemphasized in such home loan sponsored protections. Another piece of the story Is that Basel I agrees are attributed with offering seeds to the possibility of everything that could prompt downturn and Basel II Is credited with amplifying Its Impact. Shaped In 1988 and received by 1992, Basel I concurs were a lot of rules and guidelines, to be embraced by GIG nations, that distributed distinctive hazard evaluations to different kinds of advantages held by banks. Resources, here, alluded to bonds, contracts fix etc.It set aside a long effort for the economies to pragmatist the issues related with such sorts of framework. For instance, in such a structure a business bank was allowed to keep aside no fluid capital in the event that it had all administration bonds or gold as resources. This was so in light of the fact that such resources were viewed as sheltered. Further, it was expected of them to save aside little rates of capital fo r each home loan, business credit or securities they Issued. With the presentation of Basel 2, the rundown was extended to bonds sponsored by obligations like ar or property advances but then needed to keep just a 2 percent of extra capital.Flip side to this was the bonds should have AAA or AAA FICO scores from the legislature. Insights advise that Just preceding the downturn, 81 percent of all Mortgage upheld protections held by the business banks had AAA FICO score. Further, 93 percent of all home loan supported protections held by these banks had AAA FICO score or held bonds Issued by an administration supported endeavor. Presently this Is the place the job of good danger comes Into play.When Basel I and abstinently Basel II agrees were Introduced, the essential point of the created economies was to energize customer spending and Investments by the banks. It was not totally unforeseeable for everybody to understand that sponsorship obligation or garbage controlling FICO scores, e conomies attempted to make an inevitable framework that given to take care of just as took care of upon its own. The financiers were thusly motivations to face challenges of high size, with all the investors' cash close by, accepting that there is an administration continually backing them.Soon the whole framework parted with. This made a greater good peril. How to limit such issues? TO lessen such an issue of Principal Agent issue prompting downturn, it is basic that the controllers are on their toes. In USA, SEC didn't find a way to guarantee that the Rating organizations don't rate protections high with no solid sponsorship to do as such. Additionally the FIDE, the Fed, the Comptroller of the Currency, and the Office of Thrift Supervision depended indiscriminately on the evaluations given by the Credit rating agencies.Therefore, all principles and guidelines given under law ought to be executed appropriately and Justly by the controllers. The administration ought to likewise guar antee the auspicious section of significant legitimate arrangement and bills. Likewise, in spite of the fact that Basel Ill accords have been embraced and executed by the greater part of the nations and the cutoff time is 2019 for it, the current economic situations show that the Minimum Capital necessities need a redesign too. Henceforth, Basel 4 could be begun to be worked upon with refined changes and the legislatures ought to keep the principles under such necessities.

CP4 Cloud-based BI and Analytics Solutions from Birst - Podcast with Brad Peters

CP4 Cloud-based BI and Analytics Solutions from Birst - Podcast with Brad Peters INTRODUCTIONMartin: Hi, data is so much around us but the major point is we need to find insights in it. Today I am here with Brad. Hi, Brad, who are you and what do you do?Brad: So I am Brad Peters. I am one of the co-founders of a company called Birst â€" BIRST. We are a cloud based business intelligence and analytics company focused on helping organizations take data from their operations in businesses and help them make sense of it so they can run their businesses more efficiently and effectively.Martin: Cool. When did you start this company and how did you come up with this kind of business idea?Brad: I started in 2005. I have actually been in the analytics space for some time. Interesting enough, prior to starting the company which was really based on carrying some of the things I had seen in a prior the prior life forward into what we saw was a more modern era. Prior the company I was actually in another company called Siebel systems which was then a large customer relationshi p management software company. The company that sold solutions for sales, service and marketing organizations, intended to have a lot of people that use their software, arguably the predecessor of salesforce.com.We discovered something in the late nineties that all of this customer data was going into systems and into our system and we were doing a good job helping sales reps put stuff in the system but we weren’t making good use of that data for the purposes of managing the business or understanding our customers or doing anything like that. So we decided to embark upon a journey of seeing how we can make this data more useful. And we did that by partnering with some existing business intelligence providers. At the time the business object was for example the partner that we chose to use and put on top of the Siebel to see effect that would work for us.We tried it but what was interesting is that was a product that was built for relatively limited use years and years prior and ou r customers really had challenges using it. It was challenge product line. And one of the challenges was that unlike how most people had used these other types of analytics products before in the past which were usually a few people at a time at a department who were super technical, we were selling to sales people who probably didn’t like tech. Technology wasn’t a big part of their skill set and we wanted thousands of people to be able to use information and data and that really wasn’t how people thought about analytics and data before. And so we were challenged there and we had to come up with a solution.So we took a second try at it and we ended up buying and building some technology that was really about how do we take analytics and spread it out to a lot more people in an organization. We created, if you are a technologist at all, when web servers first came around there was this technology called application servers that were designed to build scalable applications deliv ered to a lot of people around the web. We kind of build the first one of those from analytics and we saw that really succeed very, very well. In fact, the analytics product line at Siebel became the largest product line in the company over the next several years.It really spoke to a couple of things. On the positive side it spoke to this incredible demand by regular people that has been growing as far back as I remember to have access to facts and information to make decisions.You know probably 30 or 40 years ago it was generally accepted that you made decisions based on the rules of thumb, habits or things like that, but I think this is really accelerating in the last several years. Even ten years ago we were seeing that people were much more comfortable making decisions and there is the much greater desire to make decisions based on facts. And so the demand for our products was increasing.Maybe less positive thing or slightly negative thing was the other products in the company w ere shrinking so we kind of crossed in the middle why were the other products shrinking. They were older technology; they were built on what we would call it client server technology. They were not web or cloud based. And we were seeing those products being basically disrupted in the market place by other cloud providers, namely guys like salesforce and folks like that. The big advantage or the many big advantages of the cloud is the fundamentally new way of building and writing and delivering software than it had been done in the past. As a consumer it is just a lot easier to consume the cloud way less painful, way more friction free and so people were moving that way on the CRM side.Martin: Did you start Birst as a cloud service provider already or did you just come one or two years later?Brad: No, so this is the thing we said “Okay, if this CRM stuff is being disrupted by cloud, by guys like salesforce and right now and omniture and you know, go down the list. And because it is hard to install, difficult to maintain and all this nonscalable, all this sort of stuff well shoot, analytics is even worse, because there are even more pieces to put together when you play with analytics. Maybe the cloud has a role to play for analytics”.So we started Birst in 2005 with the vision of bringing analytics to a modern cloud based architecture. I think in hindsight we were probably a few years ahead of the market when we decided to go do that. But yes from the very beginning we said: ”Look, there are major architectural shifts that go on in software probably every 20 to 30 years. We are seeing one right now when we went from main frames to minis, from minis to PC, to client server, to now web. We have seen these massive shifts. So whenever there is a massive shift there is an opportunity to rebuild and rethink, reimagine if you will the prior generation of stuff that came before. And we set out to do that in the world of analytics.Martin: Brad, imagine I am a compa ny and I have got lots of different data sources like Google Analytics, I have my own web logs and maybe some API data and so on and so forth. How does it work? How do I get this data into your kind of Birst cloud platform? How do I get some analytics out of there? And how do you make sure that the quality of the data is ensured?Brad: Great question. The interesting thing is that this is what the hard stuff is. That is what most people who don’t come from an analytics background easily mistake is that they look at pretty pixels on a screen and they say: “Oh, it is a pretty chart. That’s where the value is.” Reality is I think that the charting and the visuals while pretty are fairly simple. That is not where the hard stuff is. That is not where the value is. The value is in the data. It is in coming up with answers. We like to say at Birst that pretty wrong answer is still a wrong answer. It is all about how do you create an infrastructure so that you can get the correct ans wer or you can get the answers that you need to the questions that you have when you need them so you can make decisions based on facts. It turns out that is not easy to do. That was another thing that we kind of even as analytics veterans we underestimated that because it is extremely hard.So the challenge is even more broad than just say Google analytics and some web log data and things like that. Most companies that we deal with have that. They also have Salesforce they have a bunch of stuff that is inside of their firewall on premise or they may have a data warehouse already. They have a bunch of stuff sitting in a bunch of different places that each give you a silo or piece of information about how their business is performing but the question they want to ask span those silos. They want to ask questions like when I did that web advertising campaign how did that turn into leads and did those leads close into deals and how much did it cost me to generate a customer? Those are pr etty expensive questions that you can’t answer by taking one of those pieces by itself. You have got to look across all of them.So we had to spend a bunch of years building technology that can handle data in two ways. The first way is we can take data and connect to something like Google Analytics or Salesforce or SAP and we can extract data and we can make it what we would call analytically ready because the applications in its raw form not really good for answering questions. It is built in ways, there are whole ways that engineers structure data for the purposes of application that make it hard to use for analytics. We turn it into an analytically useful form.But also, there is other data that is sitting out there that is already been worked with and is tuned into something that is useful in which case we don’t load that into Birst. We just connect to it. We map on top of whatever it is and then when we need it we just query it in place and so we create this layer, we call it our user data tier, and that basically allows us to present to the end user this integrated picture of all this data in their company. Even if some of it is in Birst and some of it is not, we created this unified view then we can then allow people to ask questions off, create visualizations and dashboards and reports in a whole variety of ways of looking at that data so they can ask and answer the kind of questions that they want.Martin: What happens, Brad, if I am having like you said different data sources but in the history I wasn’t aware of that and I was only looking at the silo type of analytics which we both agree is not where the value lies. I am pumping the data into the Birst platform but apparently how do you want to join this data if I don’t use the same kind of user identifiers or different time stamp technologies or something like this?Brad: It is a great question and I think this is where a lot of people get hung up with analytics. So in these different silos I w ould say in our empirical experience more often than not there are relationships between data that can be exported directly and this notion of a customer name being different in one place and being different in another place. While that is true that particular issue is a smaller issue than we typically see in larger systems and there is a ton of value that can be gotten out without solving those types of fuzzier issues. Out of systems just straight as they are with a little bit of extra work we can tie those systems together so they generate common identifiers and do the kids of linking that you expect. It is not magic and that is something that folks need to keep in mind. But also it is not instrumentable either. It takes a bit of work and there is a well-defined best practice and by doing it intelligently you can minimize the amount of work involved. There is still some work that needs to get done every time you want to bring in a new silo into your overall mix in terms of how tha t silo relates but through intelligent use of automation and other types of tools we can keep that as a manageable piece of work.And then the benefits of once you have done that, once you have created a mechanism for cross keying various systems or relating these different elements. Keep in mind relations can be as low level as I have a transactional key that synchronize across different systems. They can also be as simple as time. What if I just know that have spent so much in advertising revenue in a month and I have got so much in leads. That’s valuable in on itself and certainly not an excuse. You can conform data on multiple levels and you don’t have to solve the intergalactic data integration issue to get a ton of value out of it. I think the goal of analytics is to do everything incrementally and do it iteratively and start by taking the lowest hanging fruit and continually to take more and more chunks of value off the table as you continue to add more richness to your da ta set. But not having a perfectly integrated data set is not an excuse for not starting.Martin: And how do I ingest all my data sources into your system. Do you have APIs for all systems or do I need to build some kind of data pipelines myself?Brad: We do. So that is one of the other challenges we had to solve when we moved to cloud. We couldn’t assume and in some cases it would have been ok to assume but we didn’t feel we were in position to assume that all of the data pipeline and data integration and data transformation logic would be done before the people gave the data to us because it would be wonderful if everybody just piped into Birst a super clean single table that added everything exactly as we wanted and all we had to do was chart it. I don’t think in the history of Birst that has ever happened.So we actually have a data pipeline as a part of our process and what we wanted to do is not just add the data pipeline but have that data pipeline be built into the visual ization and analytics pipeline as well so that when you define something and bring it in by connecting it to the other piece you minimize the amount of duplication, integration work you can automate a lot more of those hand offs by having it be together. So we have APIs that can get data all over the place whether it can be cloud based services thing, like RESTful API and those sorts of things or on premise databases or file systems, or Amazon, or all the various ways that SAP has you to connect SAP. All of that stuff we have connectors for. We have built hundreds of connectors for hundreds of types of ways to bring data in and connect to data.Martin: And how did you start. I assume your prioritized those connectors over each other because in the beginning you did not have infinite resources. How did you prioritize in the beginning?Brad: Really good question and this is the standard product management question where you had to be ruthless in your prioritization about how stuff works and what you are going to do.When we got started Salesforce was not that big. We were tiny, but they were not the dominant factor that they are today. So the biggest single source of data that we actually saw was databases. The good news is some of that has already been standardizes so we started out with that and we started doing the standard exercise which is let’s look at the market and let’s figure out some combination of presence where is most data in companies that we see. And we line that up with what kinds of customers do we thing we were initially going to get and where do they have most of their data. And that helped us prioritize and come up with a few some early sources and then over time we built an infrastructure that allowed us to not have to build these in one of fashion that allowed us to build a framework for adding new sources that then we can scale up and turn into a connector machine if you will.BUSINESS MODEL OF BIRSTMartin: Brad, when we are thinking abou t business model what are typically your customer segments and can you give us some kind of demographics or statistics on them?Brad: Yes, sure. I would say it has changed over time. So where we are today is Birst serves more often than not larger companies or more sophisticated analytical or data scenarios. If you have a single table and you just want to put a chart on it there is a hundred different things that you can do to go do that. But if you have hundreds of tables or tens of tables coming maybe from many different applications we call that schematically complex data. And when you have schematically complex data that is where Birst shines. We are much better at handing that than other tools. And you typically find that data in larger companies with more sophisticated environment or in organizations where you are taking a large percentage of what they are doing and making that analytically useful so say that for example embedded use cases. Somebody is building an application, they want to add analytics to it and they will embed us in the process.We sell right now to other software companies that embed analytics in their application and we help them get their arms around that data and then we also sell to companies for use internally to analyze data from the applications that they are using. So one is for companies to resell to their customers the other is for companies to use internally. And for the internal use case like I said it is moving to larger customers but I would say five or six years ago I think the cloud was probably a little new for a larger customers and larger customers were still playing around with a lot of the legacy vendors â€" the big mega vendor guys and were just learning about the cloud. So we were probably focused more on what we would call the mid-market mid-sized companies who probably didn’t have any analytics software and we became a one stop shop for these folks, because we had everything. And over time as our product has gotten even richer we have seen those customers get larger and larger.Martin: Cool. Brad, how did you find and acquire the customers in the beginning? So imagine, after you have built the first integration of your product, just trying to go to the market. How did you find and acquire those customers?Brad: We’ve got to several go to market models. The initial go to market model was actually different. Initial go to market model was predicated on the idea that it was going to be very hard to do a mass market approach for small company. So let’s not do a mass market approach initially because that requires a lot of capital and it requires a lot of brand presence and those sorts of things. It was something that’s a lot more focused.Initially, we didn’t have a lot on the BI or analytics piece and so what we decided to do was actually to build the applications rather than to build a full line analytics product. We said: “Let’s go after a single use case. Let’s go after a sin gle application for a single industry in a single vertical” and in our case financial services and wealth management and we said: Let’s build custom built solutions around that. And when we do that we go from company to company within the vertical and as we do that we will build out our technology platform and make it more horizontal over time and then we go to another vertical or two. And then eventually we will go horizontal once our platform is built out to be able to be marketed directly as a platform.So we actually ended up targeting the use case and application first and didn’t have much product actually built initially. It was more around work: Here is an area of value for you Mr. Customer. If we are able to do this clearly this would be of value to you, do you agree? Yes. Ok, so let’s go jointly and get building this together. So they were a relatively small number of people we found a couple of early customers that were partners with us to build those early use case s and we used that to push our platform forward.And then as we push the platform forward we made It more general, we got better and richer. And then we get a big push when the financial markets imploded in 2008 and a lot of our target customer base kind of went away literally. And I said: “Okay, if our core market is gone and the next two or three markets that we are going to go sell to are gone maybe it is time to go horizontal now. ”So in 2009 it was when we shifted to horizontal. But by then we had enough critical mass that we had from salespeople we had some marketing people we can go and do the kids of things you would expect selling to more horizontal set of capabilities would need.Martin: And how is the revenue model working? Especially how do you price and what do you price.Brad: Well we are consistent with most cloud companies. We are typically per user per year. We have customers that sign up. There is generally a modest startup fee just to get folks kind of hooked up but as a standard cloud model which is the more you use it the more value you get, the more we participate in that value.Martin: Because I would have assumed a hybrid model for example one part being on a per user model or per user, per month whatsoever and on the other hand based on storage.Brad: The thing about storage is we do have to charge for it because if there is no charge for its customers can just go crazy and put infinite amounts of data in there. At the same time storage has become so commoditized and storage is one of those things where this is the marketing challenge we run into which is when we store data we don’t just store data on a disk. We have high performance database that is tuned for analytics, that is an analytical system with high performance hardware around that. It is designed so that when you query that data you get fast results and you get the kinds of things that you want. That is not like Amazon S3 where I am sticking something on a cheap disk somewh ere and I may call it once in a blue moon. This is very, very different environment.So the challenge we have had is it is more expensive than more disks. But when you charge for storage the average instinct of most customers is: “Shoot, I can go down to fries or go on whatever website I want and I can go buy a disk drive for 200 bucks that contains terabytes. Storage should be free.” And they don’t think about it is not just the disks or the storage. It is all of the other stuff that goes with it. By the way we have to back it up and we have to have disaster recovery and reliability and all the things you have got to do. But it is still just instinctively for customers tough to think storage is expensive.So what we have done is we have made that as small as we can and so typically is part of our customer model unless the storage gets really big. The storage is actually relatively small piece of the overall picture. It is more based on the value in users.Martin: Ok, cool. Who d o you perceive your competitors to be and why do you think you are better and in what dimensions are you outcompeting them?Brad: We kind of have two classes of competitors I’d say in the market place. Ultimately, what we are trying to do â€" we are trying to create a disruptive way of thinking about analytics in the market place to give people better economics and better responsiveness and better ability to make decisions with data. And so really we have to compete against the alternatives the people are looking at in the market place. And there are kind of two alternatives the people see.The first is the legacy toolset that people have. They are typically the mega vendors that you can think about â€" the big blue and red and other logos you can imagine. And those folks have toolsets that have grown up over the last 25 or 30 years. The core code for these systems was probably written in C++ 25 years ago. So it is old stuff, really old stuff. Analytics is a complicated beast and so there is a lot of different pieces to building an analytical system, we were talking about data pipelines and those sort of things. When you go to these companies in order for them to give you a solution it is not one product. It is probably a collection of at least 5 to 10 different products that you have to have and you as a customer have to like put it all together and make it work. We like to say the only thing integrated about these like legacy guys is the price list. You have big price list that has lots of stuff on it. But then once you buy it you have got to go put it all together and that is one of the big areas where people don’t like analytics because you call up the IT people and say: “Hey, I want to get analytics on this data” and they say: “Okay, we will see you next year because we have got to go do this major project that is probably similar to building an aircraft.So that lack of integration makes them there is a lot of stuff you can do with them but they a re really low level and they are leveraging really old components. They don’t get any benefit or any lift from any modern software architectures and techniques that are being done today like RUIs is based on the Google framework and we have got stuff from Facebook and Netflix and stuff like that built into our product. They get no lift from that, they are completely fragmented, they are expensive but they have a large vendor relationship because they are big folks and a lot of people don’t look really deep when they buy the stuff. So that is one opportunity for us to radically change the economics of analytics by making stuff way easier to consume within those folks and that is one set of competitors in the market place.The other set is what we would call desktop software. Over the last 6 or 7 years there have been an array of new folks that have shown up in this market place that have said: “Wow, these suits of tools that the large enterprises have collected over the years by acquiring all those companies are really complex and so what we are going to do is we are going to focus on a much simpler problem.” If you only have a single table or maybe a couple of tables let’s at least make that really easy to use one product and let’s do that on desktop. So anybody anywhere who is an analyst can plug a data on the desktop and make a pretty dashboard or pretty chart.That works really well and they have done really, really well with these limited use cases and they are doing that certainly next step up from where maybe Microsoft Excel left off. Excel is probably the most prevalent analytical product in the world and not probably, it Is way more prevalent than anything else but it has it’s great deficiency in that the format of the data you are looking at and the data itself are one and the same. They are both in the same place. So if I create a report today with an Excel and I want to do it again next week I kind of have to rebuild it from scratch. The re is no scalability or leverage in Excel. And Excel is really hard to manage and so it is the first thing but it is really messy.These desktop tools kind of go a little bit beyond Excel and they let you take some tools and create more repeatable process on the desktop level but they gave up on enterprise and sophisticated data sets for bigger problems and bigger analytical needs. And so where we fit is really when you have something that is more than just a few individual or small problems, you have something that an organization needs to look at when you want to deal with organizational level analytics and you don’t want to endure the pain and suffering associated with these legacy tool sets were built in prehistoric year. Now you have an opportunity to leverage cloud architectures and those sorts of things and handle those problems. And that is where we fit, it is really agility of some of these desktop tools but on an enterprise or organizational scale.ADVICE TO ENTREPRENEURS FROM BRAD PETERSMartin: Good. Brad, let’s talk about your learnings during your entrepreneurial journey. What have been your major learnings and maybe your biggest mistakes?Brad: Well, I think learning occurs on a couple levels. I went to business school I had a technical background coming in so I grew up in an entrepreneurial family. My dad started a company in the late 70s around software for the early microcomputers that were there. So I had some exposure to what starting a company was like and starting a company in San Diego in the 1980s was not an easy thing to do. There wasn’t a lot of venture capital or anything like that around so it was really hard. So I had appreciation going for this stuff. You could jump on a gusher and there are a lot of people that mistake luck for brilliance. They tend to assume they have much higher IQ than they actually do because they got lucky. That is possible you can certainly get lucky. You can certainly find an opportunity that with passab le execution will get you to something that is successful and those happen and they are stories in the Valley and they become these legends that people get excited about.But I think the much more common case is this stuff is pretty hard to do because nobody really wants you to succeed. I think they like the idea of the new guy but nobody wants to buy from the new guy. So it is much harder to get going. And so I kind of knew that going in and my partner was in a similar mode. His father started some companies as well. He actually founded Polycon and Picturetel and a number of companies that are pretty famous. I would like to say one thing.When we started he gave us one word of advice. He said pretty apt: “Whatever you do, avoid death.” And that sounds really trivial but in reality a lot of people make a lot of moves with this idea that being bold is great but more companies die then don’t and if you do something that allows yourself to be killed you don’t give yourself the op portunity to be in the right place in the right time when the market moves your way. Most companies that are successful are there when the market is there. You can’t really move the market so you have to be around until the market is there.For us what I think we focus in learning was learn how to quickly read the market as best we can and try to adapt to what we are learning as quickly as possible. Our market has gone through probably three or four major changes since we started the company and we had to change three or four times pretty significantly. And it is always a balance, you want to jump very quickly on the new thing but there is risk associated with that. So it is how do you walk the line of putting a foot forward on the next rock that you are going to put your weight on but don’t take your weight fully off the rock that you are currently standing on. But it is sinking, it is going away so you have got to make sure the next rock is stable before you put all your weight there and keep your balanced. That really has been our focus â€" making sure that we make fast but judicious steps forward.Martin: You nicely put the frame when you said that the father of your co-founder gave you type of advice. What advice would you give your children if they wanted to start a company?Brad: Fail fast. I love the avoid death because it has been true in every case that I am aware of but as a second piece of advice I think fail fast. It is very easy to hang on to something that is marginally successful but won’t get you there and if it is not working admit failure quickly and move on.Martin: And how do you identify whether it is failure or whether you just need to stick around a little bit longer and waiting until the market keeps moving?Brad: That is the big billion-dollar question. I think that is where this whole idea of being adaptable is trying to figure that out as quickly as possible. And that means being ruthless in being honest with yourself are you fail ing or not and sometimes you have to stick in there. You have to say: “Look, I don’t know if this is succeeding or failing and so here is what I am going to do, but these are the signs I am going to look for and when it comes to this we are going to fail”. But don’t fail on an idea before you get the next thing lined up because you don’t want to shoot your foot off.Martin: Great. Brad, thank you so much for sharing your knowledge.Brad: Thank you I really appreciate it. Thanks, Martin.Martin: And if you are looking for a great cloud BI solution and you have a lot of data scattered along your company, check out Birst. Thanks.THANKS FOR LISTENING! Welcome to the fourth episode of our podcast!You can download the podcast to your computer or listen to it here on the blog. Click here to subscribe in iTunes. INTRODUCTIONMartin: Hi, data is so much around us but the major point is we need to find insights in it. Today I am here with Brad. Hi, Brad, who are you and what do you do?Brad: So I am Brad Peters. I am one of the co-founders of a company called Birst â€" BIRST. We are a cloud based business intelligence and analytics company focused on helping organizations take data from their operations in businesses and help them make sense of it so they can run their businesses more efficiently and effectively.Martin: Cool. When did you start this company and how did you come up with this kind of business idea?Brad: I started in 2005. I have actually been in the analytics space for some time. Interesting enough, prior to starting the company which was really based on carrying some of the things I had seen in a prior the prior life forward into what we saw was a more modern era. Prior the company I was actually in another company called Siebel systems which was then a large customer relationshi p management software company. The company that sold solutions for sales, service and marketing organizations, intended to have a lot of people that use their software, arguably the predecessor of salesforce.com.We discovered something in the late nineties that all of this customer data was going into systems and into our system and we were doing a good job helping sales reps put stuff in the system but we weren’t making good use of that data for the purposes of managing the business or understanding our customers or doing anything like that. So we decided to embark upon a journey of seeing how we can make this data more useful. And we did that by partnering with some existing business intelligence providers. At the time the business object was for example the partner that we chose to use and put on top of the Siebel to see effect that would work for us.We tried it but what was interesting is that was a product that was built for relatively limited use years and years prior and ou r customers really had challenges using it. It was challenge product line. And one of the challenges was that unlike how most people had used these other types of analytics products before in the past which were usually a few people at a time at a department who were super technical, we were selling to sales people who probably didn’t like tech. Technology wasn’t a big part of their skill set and we wanted thousands of people to be able to use information and data and that really wasn’t how people thought about analytics and data before. And so we were challenged there and we had to come up with a solution.So we took a second try at it and we ended up buying and building some technology that was really about how do we take analytics and spread it out to a lot more people in an organization. We created, if you are a technologist at all, when web servers first came around there was this technology called application servers that were designed to build scalable applications deliv ered to a lot of people around the web. We kind of build the first one of those from analytics and we saw that really succeed very, very well. In fact, the analytics product line at Siebel became the largest product line in the company over the next several years.It really spoke to a couple of things. On the positive side it spoke to this incredible demand by regular people that has been growing as far back as I remember to have access to facts and information to make decisions.You know probably 30 or 40 years ago it was generally accepted that you made decisions based on the rules of thumb, habits or things like that, but I think this is really accelerating in the last several years. Even ten years ago we were seeing that people were much more comfortable making decisions and there is the much greater desire to make decisions based on facts. And so the demand for our products was increasing.Maybe less positive thing or slightly negative thing was the other products in the company w ere shrinking so we kind of crossed in the middle why were the other products shrinking. They were older technology; they were built on what we would call it client server technology. They were not web or cloud based. And we were seeing those products being basically disrupted in the market place by other cloud providers, namely guys like salesforce and folks like that. The big advantage or the many big advantages of the cloud is the fundamentally new way of building and writing and delivering software than it had been done in the past. As a consumer it is just a lot easier to consume the cloud way less painful, way more friction free and so people were moving that way on the CRM side.Martin: Did you start Birst as a cloud service provider already or did you just come one or two years later?Brad: No, so this is the thing we said “Okay, if this CRM stuff is being disrupted by cloud, by guys like salesforce and right now and omniture and you know, go down the list. And because it is hard to install, difficult to maintain and all this nonscalable, all this sort of stuff well shoot, analytics is even worse, because there are even more pieces to put together when you play with analytics. Maybe the cloud has a role to play for analytics”.So we started Birst in 2005 with the vision of bringing analytics to a modern cloud based architecture. I think in hindsight we were probably a few years ahead of the market when we decided to go do that. But yes from the very beginning we said: ”Look, there are major architectural shifts that go on in software probably every 20 to 30 years. We are seeing one right now when we went from main frames to minis, from minis to PC, to client server, to now web. We have seen these massive shifts. So whenever there is a massive shift there is an opportunity to rebuild and rethink, reimagine if you will the prior generation of stuff that came before. And we set out to do that in the world of analytics.Martin: Brad, imagine I am a compa ny and I have got lots of different data sources like Google Analytics, I have my own web logs and maybe some API data and so on and so forth. How does it work? How do I get this data into your kind of Birst cloud platform? How do I get some analytics out of there? And how do you make sure that the quality of the data is ensured?Brad: Great question. The interesting thing is that this is what the hard stuff is. That is what most people who don’t come from an analytics background easily mistake is that they look at pretty pixels on a screen and they say: “Oh, it is a pretty chart. That’s where the value is.” Reality is I think that the charting and the visuals while pretty are fairly simple. That is not where the hard stuff is. That is not where the value is. The value is in the data. It is in coming up with answers. We like to say at Birst that pretty wrong answer is still a wrong answer. It is all about how do you create an infrastructure so that you can get the correct ans wer or you can get the answers that you need to the questions that you have when you need them so you can make decisions based on facts. It turns out that is not easy to do. That was another thing that we kind of even as analytics veterans we underestimated that because it is extremely hard.So the challenge is even more broad than just say Google analytics and some web log data and things like that. Most companies that we deal with have that. They also have Salesforce they have a bunch of stuff that is inside of their firewall on premise or they may have a data warehouse already. They have a bunch of stuff sitting in a bunch of different places that each give you a silo or piece of information about how their business is performing but the question they want to ask span those silos. They want to ask questions like when I did that web advertising campaign how did that turn into leads and did those leads close into deals and how much did it cost me to generate a customer? Those are pr etty expensive questions that you can’t answer by taking one of those pieces by itself. You have got to look across all of them.So we had to spend a bunch of years building technology that can handle data in two ways. The first way is we can take data and connect to something like Google Analytics or Salesforce or SAP and we can extract data and we can make it what we would call analytically ready because the applications in its raw form not really good for answering questions. It is built in ways, there are whole ways that engineers structure data for the purposes of application that make it hard to use for analytics. We turn it into an analytically useful form.But also, there is other data that is sitting out there that is already been worked with and is tuned into something that is useful in which case we don’t load that into Birst. We just connect to it. We map on top of whatever it is and then when we need it we just query it in place and so we create this layer, we call it our user data tier, and that basically allows us to present to the end user this integrated picture of all this data in their company. Even if some of it is in Birst and some of it is not, we created this unified view then we can then allow people to ask questions off, create visualizations and dashboards and reports in a whole variety of ways of looking at that data so they can ask and answer the kind of questions that they want.Martin: What happens, Brad, if I am having like you said different data sources but in the history I wasn’t aware of that and I was only looking at the silo type of analytics which we both agree is not where the value lies. I am pumping the data into the Birst platform but apparently how do you want to join this data if I don’t use the same kind of user identifiers or different time stamp technologies or something like this?Brad: It is a great question and I think this is where a lot of people get hung up with analytics. So in these different silos I w ould say in our empirical experience more often than not there are relationships between data that can be exported directly and this notion of a customer name being different in one place and being different in another place. While that is true that particular issue is a smaller issue than we typically see in larger systems and there is a ton of value that can be gotten out without solving those types of fuzzier issues. Out of systems just straight as they are with a little bit of extra work we can tie those systems together so they generate common identifiers and do the kids of linking that you expect. It is not magic and that is something that folks need to keep in mind. But also it is not instrumentable either. It takes a bit of work and there is a well-defined best practice and by doing it intelligently you can minimize the amount of work involved. There is still some work that needs to get done every time you want to bring in a new silo into your overall mix in terms of how tha t silo relates but through intelligent use of automation and other types of tools we can keep that as a manageable piece of work.And then the benefits of once you have done that, once you have created a mechanism for cross keying various systems or relating these different elements. Keep in mind relations can be as low level as I have a transactional key that synchronize across different systems. They can also be as simple as time. What if I just know that have spent so much in advertising revenue in a month and I have got so much in leads. That’s valuable in on itself and certainly not an excuse. You can conform data on multiple levels and you don’t have to solve the intergalactic data integration issue to get a ton of value out of it. I think the goal of analytics is to do everything incrementally and do it iteratively and start by taking the lowest hanging fruit and continually to take more and more chunks of value off the table as you continue to add more richness to your da ta set. But not having a perfectly integrated data set is not an excuse for not starting.Martin: And how do I ingest all my data sources into your system. Do you have APIs for all systems or do I need to build some kind of data pipelines myself?Brad: We do. So that is one of the other challenges we had to solve when we moved to cloud. We couldn’t assume and in some cases it would have been ok to assume but we didn’t feel we were in position to assume that all of the data pipeline and data integration and data transformation logic would be done before the people gave the data to us because it would be wonderful if everybody just piped into Birst a super clean single table that added everything exactly as we wanted and all we had to do was chart it. I don’t think in the history of Birst that has ever happened.So we actually have a data pipeline as a part of our process and what we wanted to do is not just add the data pipeline but have that data pipeline be built into the visual ization and analytics pipeline as well so that when you define something and bring it in by connecting it to the other piece you minimize the amount of duplication, integration work you can automate a lot more of those hand offs by having it be together. So we have APIs that can get data all over the place whether it can be cloud based services thing, like RESTful API and those sorts of things or on premise databases or file systems, or Amazon, or all the various ways that SAP has you to connect SAP. All of that stuff we have connectors for. We have built hundreds of connectors for hundreds of types of ways to bring data in and connect to data.Martin: And how did you start. I assume your prioritized those connectors over each other because in the beginning you did not have infinite resources. How did you prioritize in the beginning?Brad: Really good question and this is the standard product management question where you had to be ruthless in your prioritization about how stuff works and what you are going to do.When we got started Salesforce was not that big. We were tiny, but they were not the dominant factor that they are today. So the biggest single source of data that we actually saw was databases. The good news is some of that has already been standardizes so we started out with that and we started doing the standard exercise which is let’s look at the market and let’s figure out some combination of presence where is most data in companies that we see. And we line that up with what kinds of customers do we thing we were initially going to get and where do they have most of their data. And that helped us prioritize and come up with a few some early sources and then over time we built an infrastructure that allowed us to not have to build these in one of fashion that allowed us to build a framework for adding new sources that then we can scale up and turn into a connector machine if you will.BUSINESS MODEL OF BIRSTMartin: Brad, when we are thinking abou t business model what are typically your customer segments and can you give us some kind of demographics or statistics on them?Brad: Yes, sure. I would say it has changed over time. So where we are today is Birst serves more often than not larger companies or more sophisticated analytical or data scenarios. If you have a single table and you just want to put a chart on it there is a hundred different things that you can do to go do that. But if you have hundreds of tables or tens of tables coming maybe from many different applications we call that schematically complex data. And when you have schematically complex data that is where Birst shines. We are much better at handing that than other tools. And you typically find that data in larger companies with more sophisticated environment or in organizations where you are taking a large percentage of what they are doing and making that analytically useful so say that for example embedded use cases. Somebody is building an application, they want to add analytics to it and they will embed us in the process.We sell right now to other software companies that embed analytics in their application and we help them get their arms around that data and then we also sell to companies for use internally to analyze data from the applications that they are using. So one is for companies to resell to their customers the other is for companies to use internally. And for the internal use case like I said it is moving to larger customers but I would say five or six years ago I think the cloud was probably a little new for a larger customers and larger customers were still playing around with a lot of the legacy vendors â€" the big mega vendor guys and were just learning about the cloud. So we were probably focused more on what we would call the mid-market mid-sized companies who probably didn’t have any analytics software and we became a one stop shop for these folks, because we had everything. And over time as our product has gotten even richer we have seen those customers get larger and larger.Martin: Cool. Brad, how did you find and acquire the customers in the beginning? So imagine, after you have built the first integration of your product, just trying to go to the market. How did you find and acquire those customers?Brad: We’ve got to several go to market models. The initial go to market model was actually different. Initial go to market model was predicated on the idea that it was going to be very hard to do a mass market approach for small company. So let’s not do a mass market approach initially because that requires a lot of capital and it requires a lot of brand presence and those sorts of things. It was something that’s a lot more focused.Initially, we didn’t have a lot on the BI or analytics piece and so what we decided to do was actually to build the applications rather than to build a full line analytics product. We said: “Let’s go after a single use case. Let’s go after a sin gle application for a single industry in a single vertical” and in our case financial services and wealth management and we said: Let’s build custom built solutions around that. And when we do that we go from company to company within the vertical and as we do that we will build out our technology platform and make it more horizontal over time and then we go to another vertical or two. And then eventually we will go horizontal once our platform is built out to be able to be marketed directly as a platform.So we actually ended up targeting the use case and application first and didn’t have much product actually built initially. It was more around work: Here is an area of value for you Mr. Customer. If we are able to do this clearly this would be of value to you, do you agree? Yes. Ok, so let’s go jointly and get building this together. So they were a relatively small number of people we found a couple of early customers that were partners with us to build those early use case s and we used that to push our platform forward.And then as we push the platform forward we made It more general, we got better and richer. And then we get a big push when the financial markets imploded in 2008 and a lot of our target customer base kind of went away literally. And I said: “Okay, if our core market is gone and the next two or three markets that we are going to go sell to are gone maybe it is time to go horizontal now. ”So in 2009 it was when we shifted to horizontal. But by then we had enough critical mass that we had from salespeople we had some marketing people we can go and do the kids of things you would expect selling to more horizontal set of capabilities would need.Martin: And how is the revenue model working? Especially how do you price and what do you price.Brad: Well we are consistent with most cloud companies. We are typically per user per year. We have customers that sign up. There is generally a modest startup fee just to get folks kind of hooked up but as a standard cloud model which is the more you use it the more value you get, the more we participate in that value.Martin: Because I would have assumed a hybrid model for example one part being on a per user model or per user, per month whatsoever and on the other hand based on storage.Brad: The thing about storage is we do have to charge for it because if there is no charge for its customers can just go crazy and put infinite amounts of data in there. At the same time storage has become so commoditized and storage is one of those things where this is the marketing challenge we run into which is when we store data we don’t just store data on a disk. We have high performance database that is tuned for analytics, that is an analytical system with high performance hardware around that. It is designed so that when you query that data you get fast results and you get the kinds of things that you want. That is not like Amazon S3 where I am sticking something on a cheap disk somewh ere and I may call it once in a blue moon. This is very, very different environment.So the challenge we have had is it is more expensive than more disks. But when you charge for storage the average instinct of most customers is: “Shoot, I can go down to fries or go on whatever website I want and I can go buy a disk drive for 200 bucks that contains terabytes. Storage should be free.” And they don’t think about it is not just the disks or the storage. It is all of the other stuff that goes with it. By the way we have to back it up and we have to have disaster recovery and reliability and all the things you have got to do. But it is still just instinctively for customers tough to think storage is expensive.So what we have done is we have made that as small as we can and so typically is part of our customer model unless the storage gets really big. The storage is actually relatively small piece of the overall picture. It is more based on the value in users.Martin: Ok, cool. Who d o you perceive your competitors to be and why do you think you are better and in what dimensions are you outcompeting them?Brad: We kind of have two classes of competitors I’d say in the market place. Ultimately, what we are trying to do â€" we are trying to create a disruptive way of thinking about analytics in the market place to give people better economics and better responsiveness and better ability to make decisions with data. And so really we have to compete against the alternatives the people are looking at in the market place. And there are kind of two alternatives the people see.The first is the legacy toolset that people have. They are typically the mega vendors that you can think about â€" the big blue and red and other logos you can imagine. And those folks have toolsets that have grown up over the last 25 or 30 years. The core code for these systems was probably written in C++ 25 years ago. So it is old stuff, really old stuff. Analytics is a complicated beast and so there is a lot of different pieces to building an analytical system, we were talking about data pipelines and those sort of things. When you go to these companies in order for them to give you a solution it is not one product. It is probably a collection of at least 5 to 10 different products that you have to have and you as a customer have to like put it all together and make it work. We like to say the only thing integrated about these like legacy guys is the price list. You have big price list that has lots of stuff on it. But then once you buy it you have got to go put it all together and that is one of the big areas where people don’t like analytics because you call up the IT people and say: “Hey, I want to get analytics on this data” and they say: “Okay, we will see you next year because we have got to go do this major project that is probably similar to building an aircraft.So that lack of integration makes them there is a lot of stuff you can do with them but they a re really low level and they are leveraging really old components. They don’t get any benefit or any lift from any modern software architectures and techniques that are being done today like RUIs is based on the Google framework and we have got stuff from Facebook and Netflix and stuff like that built into our product. They get no lift from that, they are completely fragmented, they are expensive but they have a large vendor relationship because they are big folks and a lot of people don’t look really deep when they buy the stuff. So that is one opportunity for us to radically change the economics of analytics by making stuff way easier to consume within those folks and that is one set of competitors in the market place.The other set is what we would call desktop software. Over the last 6 or 7 years there have been an array of new folks that have shown up in this market place that have said: “Wow, these suits of tools that the large enterprises have collected over the years by acquiring all those companies are really complex and so what we are going to do is we are going to focus on a much simpler problem.” If you only have a single table or maybe a couple of tables let’s at least make that really easy to use one product and let’s do that on desktop. So anybody anywhere who is an analyst can plug a data on the desktop and make a pretty dashboard or pretty chart.That works really well and they have done really, really well with these limited use cases and they are doing that certainly next step up from where maybe Microsoft Excel left off. Excel is probably the most prevalent analytical product in the world and not probably, it Is way more prevalent than anything else but it has it’s great deficiency in that the format of the data you are looking at and the data itself are one and the same. They are both in the same place. So if I create a report today with an Excel and I want to do it again next week I kind of have to rebuild it from scratch. The re is no scalability or leverage in Excel. And Excel is really hard to manage and so it is the first thing but it is really messy.These desktop tools kind of go a little bit beyond Excel and they let you take some tools and create more repeatable process on the desktop level but they gave up on enterprise and sophisticated data sets for bigger problems and bigger analytical needs. And so where we fit is really when you have something that is more than just a few individual or small problems, you have something that an organization needs to look at when you want to deal with organizational level analytics and you don’t want to endure the pain and suffering associated with these legacy tool sets were built in prehistoric year. Now you have an opportunity to leverage cloud architectures and those sorts of things and handle those problems. And that is where we fit, it is really agility of some of these desktop tools but on an enterprise or organizational scale.ADVICE TO ENTREPRENEURS FROM BRAD PETERSMartin: Good. Brad, let’s talk about your learnings during your entrepreneurial journey. What have been your major learnings and maybe your biggest mistakes?Brad: Well, I think learning occurs on a couple levels. I went to business school I had a technical background coming in so I grew up in an entrepreneurial family. My dad started a company in the late 70s around software for the early microcomputers that were there. So I had some exposure to what starting a company was like and starting a company in San Diego in the 1980s was not an easy thing to do. There wasn’t a lot of venture capital or anything like that around so it was really hard. So I had appreciation going for this stuff. You could jump on a gusher and there are a lot of people that mistake luck for brilliance. They tend to assume they have much higher IQ than they actually do because they got lucky. That is possible you can certainly get lucky. You can certainly find an opportunity that with passab le execution will get you to something that is successful and those happen and they are stories in the Valley and they become these legends that people get excited about.But I think the much more common case is this stuff is pretty hard to do because nobody really wants you to succeed. I think they like the idea of the new guy but nobody wants to buy from the new guy. So it is much harder to get going. And so I kind of knew that going in and my partner was in a similar mode. His father started some companies as well. He actually founded Polycon and Picturetel and a number of companies that are pretty famous. I would like to say one thing.When we started he gave us one word of advice. He said pretty apt: “Whatever you do, avoid death.” And that sounds really trivial but in reality a lot of people make a lot of moves with this idea that being bold is great but more companies die then don’t and if you do something that allows yourself to be killed you don’t give yourself the op portunity to be in the right place in the right time when the market moves your way. Most companies that are successful are there when the market is there. You can’t really move the market so you have to be around until the market is there.For us what I think we focus in learning was learn how to quickly read the market as best we can and try to adapt to what we are learning as quickly as possible. Our market has gone through probably three or four major changes since we started the company and we had to change three or four times pretty significantly. And it is always a balance, you want to jump very quickly on the new thing but there is risk associated with that. So it is how do you walk the line of putting a foot forward on the next rock that you are going to put your weight on but don’t take your weight fully off the rock that you are currently standing on. But it is sinking, it is going away so you have got to make sure the next rock is stable before you put all your weight there and keep your balanced. That really has been our focus â€" making sure that we make fast but judicious steps forward.Martin: You nicely put the frame when you said that the father of your co-founder gave you type of advice. What advice would you give your children if they wanted to start a company?Brad: Fail fast. I love the avoid death because it has been true in every case that I am aware of but as a second piece of advice I think fail fast. It is very easy to hang on to something that is marginally successful but won’t get you there and if it is not working admit failure quickly and move on.Martin: And how do you identify whether it is failure or whether you just need to stick around a little bit longer and waiting until the market keeps moving?Brad: That is the big billion-dollar question. I think that is where this whole idea of being adaptable is trying to figure that out as quickly as possible. And that means being ruthless in being honest with yourself are you fail ing or not and sometimes you have to stick in there. You have to say: “Look, I don’t know if this is succeeding or failing and so here is what I am going to do, but these are the signs I am going to look for and when it comes to this we are going to fail”. But don’t fail on an idea before you get the next thing lined up because you don’t want to shoot your foot off.Martin: Great. Brad, thank you so much for sharing your knowledge.Brad: Thank you I really appreciate it. Thanks, Martin.Martin: And if you are looking for a great cloud BI solution and you have a lot of data scattered along your company, check out Birst. Thanks.THANKS FOR LISTENING!Thanks so much for joining our fourth podcast episode!Have some feedback you’d like to share?  Leave  a note in the comment section below! If you enjoyed this episode, please  share  it using the social media buttons you see at the bottom of the post.Also,  please leave an honest review for The Cleverism Podcast on iTunes or on Sou ndCloud. Ratings and reviews  are  extremely  helpful  and greatly appreciated! They do matter in the rankings of the show, and we read each and every one of them.Special thanks  to Brad for joining me this week. Until  next time!

Gender Roles And Food Production Expectations - 1324 Words

Gender roles and food production expectations have been established for decades, within families. Although, the gender roles have been slowly changing these past few years, we will be analyzing how gender roles and food production are being executed in a regular household in the following analysis. Sunday, is usually the day in which all my family assembles to eat our food together. This past Sunday, a few of our cousins decided to join us, which was even better. The day finally came when I woke up to the overwhelming smell of barbecued chicken. My mother screamed at me to wake up and to help her set the table with the utensils and napkins. As I obeyed her, I looked over to the kitchen that was filled with different condiments and†¦show more content†¦Hunting was anticipated as dangerous; therefore, it makes sense that men who hunted for animals and ate the meat maintained a sense of masculinity and bravery. Besides the correlation between meat and hunting, meat also contains plenty of proteins. Proteins is known to help a person’s muscle growth increase. I never actually payed attention but, my dad loves meat, chicken, and various other carnivorous meats. I was very curious and decided to ask him why he would always eat a sizable amount of meat. He answered by saying â€Å"Well, that’s easy not only is it delicious, it has many good nutrients that help your body to be strong,† I was just a bit surprised to hear that response simply because although my dad was probably unaware of it, he was trying to conform into the typical gender norm of the father, whom by societies’ standards have to be buff and brawny to fit the role as the brave and masculine father, who is the head of the household. At the beginning of the dinner, it appeared as if everyone was starving, we sat in silence for a few minutes while we were enjoying our meals and savoring every bit of it. 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Can We Consider Walmart A Fair Competitors Online Success

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The Crystal Shard 11. Aegis-fang Free Essays

Sweat beaded on Bruenor’s hand as he put the key into the dusty lock of the heavy wooden door. This was the beginning of the process that would put all of his skill and experience to the ultimate trial. Like all master dwarven smiths, he had been waiting for this moment with excitement and apprehension since the beginning of his long training. We will write a custom essay sample on The Crystal Shard 11. Aegis-fang or any similar topic only for you Order Now He had to push hard to swing the door in on the small chamber. Its wood creaked and groaned in protest, having warped and settled since it was last opened many years before. This was a comfort to Bruenor, though, for he dreaded the thought of anyone looking in on his most prized possessions. He glanced around at the dark corridors of this little-used section of the dwarven complex, making sure once more that he hadn’t been followed, then he entered the room, putting his torch in before him to burn away the hanging fringes of many cobwebs. The only piece of furniture in the room was a wooden, iron-bound box, banded by two heavy chains joined by a huge padlock. Spiderwebs criss-crossed and flowed from every angle of the chest, and a thick layer of dust covered its top. Another good sign, Bruenor noted. He looked out into the hall again, then shut the wooden door as quietly as he could. He knelt before the chest and placed his torch on the floor beside him. Several webs, licked by its flame, puffed into orange for just an instant, then died away. Bruenor took a small block of wood from his belt pouch and removed a silver key that hung on a chain about his neck. He held the wood block firmly in front of him and, keeping the fingers of his other hand below the level of the padlock as much as possible, gently slid the key into the lock. Now came the delicate part. Bruenor turned the key slowly, listening. When he heard the tumbler in the lock click, he braced himself and quickly pulled his hand from the key, allowing the mass of the padlock to drop away from its ring, releasing a spring-loaded lever that had been pressed between it and the chest. The small dart knocked into the block of wood, and Bruenor breathed a sigh of relief. Though he had set the trap nearly a century before, he knew that the poison of the Tundra Widowmaker snake had kept its deadly sting. Sheer excitement overwhelmed Bruenor’s reverence of this moment, and he hurriedly threw the chains back over the chest and blew the dust from its lid. He grasped the lid and started to lift it but suddenly slowed again, recovering his solemn calm and reminding himself of the importance of every action. Anyone who had come upon this chest and managed to get by the deadly trap would have been pleased with the treasures he found inside. A silver goblet, a bag of gold, and a jeweled though poorly balanced dagger were mixed in among other more personal and less valuable items; a dented helm, old boots, and other similar pieces that would hold little appeal for a thief. Yet these items were merely a foil. Bruenor pulled them out and dropped them on the dirty floor without a second thought. The bottom of the heavy chest sat just above the level of the floor, giving no indication that anything more was to be found here. But Bruenor had cunningly cut the floor lower under the chest, fitting the box into the hole so perfectly that even a scrutinizing thief would swear that it sat on the floor. The dwarf poked out a small knothole in the box’s bottom and hooked a stubby finger through the opening. This wood, too, had settled over the years, and Bruenor had to tug mightily to finally pull it free. It came out with a sudden snap, sending Bruenor tumbling backward. He was back at the chest in an instant, peering cautiously over its edge at his greatest treasures. A block of the purest mithril, a small leather bag; a golden coffer, and a silver scroll tube capped on one end by a diamond were spaced exactly as Bruenor had lain them so long ago. Bruenor’s hands trembled, and he had to stop and wipe the perspiration from them several times as he removed the precious items from the chest, placing those that would fit in his pack and laying the mithril block on a blanket he had unrolled. Then he quickly replaced the false bottom, taking care to fit the knothole back into the wood perfectly, and put his phony treasure back in place. He chained and locked the box, leaving everything exactly as he had found it, except that he saw no reason to chance accidents by rearming the needle trap. * * * Bruenor had constructed his outdoor forge in a hidden nook tucked away at the base of Kelvin’s Cairn. This was a seldom traveled portion of the dwarven valley, the northern end, with Bremen’s Run widening out into the open tundra around the western side of the mountain, and Icewind Pass doing likewise on the east. To his surprise, Bruenor found that the stone here was hard and pure, deeply imbued with the strength of the earth and would serve his small temple well. As always, Bruenor approached this sacred place with measured, reverent steps. Carrying now the treasures of his heritage, his mind drifted back over the centuries to Mithril Hall, ancient home of his people, and to the speech his father had given him on the day he received his first smithy hammer. â€Å"If yer talent for the craft is keen,† his father had said, â€Å"and ye’re lucky enough to live long and feel the strength of the earth, ye’ll find a special day. A special blessin’ – some would say a curse – has been placed upon our people, for once, and only once, the very best of our smiths may craft a weapon of their choosing that outdoes any work they’d ever done. Be wary of that day, son, for ye’ll put a great deal of yerself into that weapon. Ye’ll never match its perfection in yer life again and, knowing this, ye’ll lose a lot of the craftsman’s desire that drives the swing of yer hammer. Ye may find an empty life after yer day, but if yer good as yer line says ye’ll be, ye’ll have crafted a weapon of legend that will live on long after yer bones are dust.† Bruenor’s father, cut down in the coming of the darkness to Mithril Hall, hadn’t lived long enough to find his special day, though if he had, several of the items that Bruenor now carried would have been used by him. But the dwarf saw no disrespect in his taking the treasures as his own, for he knew that he would craft a weapon to make the spirit of his father proud. Bruenor’s day had come. * * * The image of a two-headed hammer hidden within the block of mithril had come to Bruenor in a dream earlier that week. The dwarf had understood the sign at once and knew that he would have to move quickly to get everything ready for the night of power that was fast approaching. Already the moon was big and bright in the sky. It would reach its fullness on the night of the solstice, the gray time between the seasons when the air tingled with magic. The full moon would only enhance the enchantment of that night, and Bruenor believed that he would capture a mighty spell indeed when he uttered the dweomer of power. The dwarf had much work before him if he was to be prepared. His labor had begun with the construction of the small forge. That had been the easy part and he went about it mechanically, trying to hold his thoughts to the task at hand and away from the disrupting anticipation of crafting the weapon. Now the time he had waited for was upon him. He pulled the heavy block of mithril from his pack, feeling its pureness and strength. He had held similar blocks before and grew apprehensive for a moment. He stared into the silvery metal. For a long moment, it remained a squared block. Then its sides appeared to round as the image of the marvelous warhammer came clear to the dwarf. Bruenor’s heart raced, and he breathed in short gasps. His vision had been real. He fired up the forge and began his work at once, laboring through the night until the light of dawn dispelled the charm that was upon him. He returned to his home that day only to collect the adamantite rod he had set aside for the weapon, returning to the forge to sleep and later to pace nervously while he waited for darkness to fall. As soon as daylight faded, Bruenor eagerly went back to work. The metal molded easily under his skilled manipulations, and he knew that before the dawn could interrupt him, the head of the hammer would be formed. Though he still had hours of work ahead of him, Bruenor felt a surge of pride at that moment. He knew that he would meet his demanding schedule. He would attach the adamantite handle the next night and all would be ready for the enchantment under the full moon on the night of the summer solstice. * * * The owl swooped silently down on the small rabbit, guided toward its prey by senses as acute as any living creature’s. This would be a routine kill, with the unfortunate beast never even aware of the coming predator. Yet the owl was strangely agitated, and its hunter’s concentration wavered at the last moment. Seldom did the great bird miss, but this time it flew back to its home on the side of Kelvin’s Cairn without a meal. Far out on the tundra, a lone wolf sat as still as a statue, anxious but patient as the silver disk of the huge summer moon broke the flat rim of the horizon. It waited until the alluring orb came full in the sky, then it took up the ancient howling cry of its breed. It was answered, again and again, by distant wolves and other denizens of the night, all calling out to the power of the heavens. The night of the summer solstice, when magic tingled in the air, exciting all but the rational beings who had rejected such base instinctual urges, had begun. In his emotional state, Bruenor felt the magic distinctly. But absorbed in the culmination of his life’s labors, he had attained a level of calm concentration. His hands did not tremble as he opened the golden lid of the small coffer. The mighty warhammer lay clamped to the anvil before the dwarf. It represented Bruenor’s finest work, powerful and beautifully crafted even now, but waiting for the delicate runes and intonations that would make it a weapon of special power. Bruenor reverently removed the small silver mallet and chisel from the coffer and approached the warhammer. Without hesitation, for he knew that he had little time for such intricate work, he set the chisel on the mithril and solidly tapped it with the mallet. The untainted metals sang out a clear, pure note that sent shivers through the appreciative dwarf’s spine. He knew in his heart that all of the conditions were perfect, and he shivered again when he thought of the result of this night’s labors. He did not see the dark eyes peering intently at him from a ridge a short distance away. Bruenor needed no model for the first carvings; they were symbols etched into his heart and soul. Solemnly, he inscribed the hammer and anvil of Moradin the Soulforger on the side of one of the warhammer’s heads, and the crossed axes of Clanggedon, the dwarven God of Battle, across from the first on the side of the other head. Then he took the silver scroll tube and gently removed its diamond cap. He sighed in relief when he saw that the parchment inside had survived the decades. Wiping the oily sweat from his hands, he removed the scroll and slowly unrolled it, laying it on the flat of the anvil. At first, the page seemed blank, but gradually the rays of the full moon coaxed its symbols, the secret runes of power, to appear. These were Bruenor’s heritage, and though he had never seen them before, their arcane lines and curves seemed comfortably familiar to him. His hand steady with confidence, the dwarf placed the silver chisel between the symbols he had inscribed of the two gods and began etching the secret runes onto the warhammer. He felt their magic transferring through him from the parchment to the weapon and watched in amazement as each one disappeared from the scroll after he had inscribed it onto the mithril. Time had no meaning to him now as he fell deeply into the trance of his work, but when he had completed the runes, he noticed that the moon had passed its peak and was on the wane. The first real test of the dwarf’s expertise came when he overlaid the rune carvings with the gem inside the mountain symbol of Dumathoin, the Keeper of Secrets. The lines of the god’s symbol aligned perfectly with those of the runes, obscuring the secret tracings of power. Bruenor knew then that his work was nearly complete. He removed the heavy warhammer from its clamp and took out the small leather bag. He had to take several deep breaths to steady himself, for this was the final and most decisive test of his skill. He loosened the cord at the top of the bag and marveled at the gentle shimmerings of the diamond dust in the soft light of the moon. From behind the ridge, Drizzt Do’Urden tensed in anticipation, but he was careful not to disturb his friend’s complete concentration. Bruenor steadied himself again, then suddenly snapped the bag into the air, releasing its contents high into the night. He tossed the bag aside, grasped the warhammer in both hands, and raised it above his head. The dwarf felt his very strength being sucked from him as he uttered the words of power, but he would not truly know how well he had performed until his work was complete. The level of perfection of his carvings determined the success of his intonations, for as he had etched the runes onto the weapon, their strength had flowed into his heart. This power then drew the magical dust to the weapon and its power, in turn, could be measured by the amount of shimmering diamond dust it captured. A fit of blackness fell over the dwarf. His head spun, and he did not understand what kept him from toppling. But the consuming power of the words had gone beyond him. Though he wasn’t even conscious of them, the words continued to flow from his lips in an undeniable stream, sapping more and more of his strength. Then, mercifully, he was falling, though the void of unconsciousness took him long before his head hit the ground. Drizzt turned away and slumped back against the rocky ridge; he, too, was exhausted from the spectacle. He didn’t know if his friend would survive this night’s ordeal, yet he was thrilled for Bruenor. For he had witnessed the dwarf’s most triumphant moment, even if Bruenor had not, as the hammer’s mithril head flared with the life of magic and pulled in the shower of diamond. And not a single speck of the glittering dust had escaped Bruenor’s beckon. How to cite The Crystal Shard 11. Aegis-fang, Essay examples

There Isnt Hardly Anybody Around Who Can Say Their Lives Havent Essays

There isn't hardly anybody around who can say their lives haven't been influenced by computers. Computers have all but taken over society as we know it. Everywhere you look, computers have greatly improved our lives. It can be as simple as going through a carwash, a computer processes the information that we feed it and adjusts the machine accordingly to give us the particular wash we paid for. Computers also play an extremely complicated role in one of the things that everybody uses in their everyday lives, our cars. Most people don't realize how much our cars have been taken over by technology, until they get the bill after one of these computers go out. Just about everything in a new car is controlled by a computer, a computer will read and recognize your driving patterns and adjusts how and when the transmission should shift from gear-to-gear so that you, as the driver, will get maximum performance from your car. In some vehicles, a computer will adjust how high the car rides from the ground. It lowers the car at highway speeds to make it more aerodynamic which will give you better gas mileage and makes the car easier to handle at these high speeds. The latest computer technology is an on-board navigational computer that will direct the driver into using the fastest and most efficient way to get to the destination. It will plan your route around any construction, traffic jams, and even inclement weather. If and when these cars break down, a mechanic will simply ask the car's on-board computer what is wrong, rather than having to go through a series of complicated troubleshooting tests. As I have clearly stated, computers have greatly improved something that most of us use every day. Another advantage of the computer that until recently I was unfamiliar with is the role of the computer in the workplace. I have worked at various jobs in my short existence on this earth. For the most part, the most technologically advanced any of them were was merely punching prices into a cash register, hardly a state-of-the-art process by any means. Most of the jobs I have worked at were more labor-oriented jobs, so I suppose that is why this is kind of a change for me. These days I wait tables at a local bar and grill. I have worked at restaurants like this before, but none of those places were dependent on a computer like this one is. For example, at my old job, when we took orders for drinks we scribbled it down on a sheet of paper and then threw it at the bartender along with another ten people so he could try and figure out just what the heck was written down. This process seemed to take forever. Now all I have to do is go to the computer, press a couple of buttons, and voila, the bartender gets a clear printout of what needs to be made. And with any luck, the drinks should be ready by the time I get to the bar. Needless to say I like the method of using the computer much better than the old way of writing everything down. This has also solved a lot of problems of the same kind in the kitchen, also. As having the experience of being a cook at one time, there was nothing that got on my nerves more than trying to read the handwriting of someone who had to take an order in a room filtering out more than 150 people making noise while trying to jot everything down as fast as they can. As you can probably imagine, this turns into a lose-lose situation for the people trying to work through all of this. The cook is mad at the server for not being able to write the order in plain English. The server is mad at the cook for always being so critical and not worrying about themselves. Eventually the person who is effected most by all of this is the customer. What happens is the cook finally just doesn't care about the order anymore and doesn't prepare a good meal, or the server gets ticked off at the cook and ends up taking out their frustration on the customer who doesn't get the quality of service that they deserve. That is a whole bunch of problems that came out of just one tiny little detail, that being not writing the order clearly enough. At my current job, when a food order is taken, the same process