Licensing Agreement Essay Example | Topics and Well Written Essays - 2000 words

Permitting Agreement - Essay Example This is viewed as the initial step of protected innovation. This report will recognize issues that Alarmz ltd may look by going into a concurrence with a Brazilian organization and how distinguished issues may be survived. Presentation Alarmz Ltd is an organization that prides itself with the utilization of innovatively refreshed vehicle cautions five years running. We convey and fit the top brands in vehicle cautions including Clifford, Cobra, Hornet, Viper, Avital, Laserline and Autowatch and all types of vehicle alert, leaving sensors, sound, shrouded lighting and so forth. We additionally fit vehicle frill at incredibly low costs. Our claim to fame incorporates remote beginning and 2way vehicle alerts and our customers are ensured astounding outcomes. With the expansion in vehicle burglaries and defective vehicle GPS beacons, there is a need to guarantee that vehicles have very much produced and working cautions. This has prompted our organization, Alarmz Ltd to make thoughts for the assembling of another sealed caution. This caution will be planned in a manner that limits odds of altering by individuals who have vindictive goals with the vehicle. This caution framework will have highlights that will be not the same as other market alerts. In this journey, we had the option to recognize the Brazilian Company Redfern Integrated Optics (RIO) Inc as our favored maker. RIO Inc. is an organization that is notable for the assembling and improvement of optical and subsystems dependent on Planar External Cavity Laser Technology (PLANEX). It conveys restrictive value execution returns in vitality, security, foundation, metrology, and different markets. The characteristics of items delivered by RIO Inc are the best so far in the market. Instances of disappointment by clients have been negligible. The conveyance of their items is on a wide territory scale, as they have satisfactory transportation that administers appropriation. This is along these lines, the better ch oice we have distinguished to work with as an assembling organization. There is a requirement for Alarmz Ltd to go into a permitting concurrence with RIO Inc. A permitting understanding is important on the grounds that, our organization needs to ensure its scholarly and innovation rights. Since our organization concocted a thought and needs to make the item a reality, we despite everything need to have rights over the item as the creators. Alarmz ltd should build its income, and the item can do that. Settling on an authorizing understanding guarantees that Alarmz ltd; the first designers of the item appreciate the advantages of the item and are included when an expansion of cost for the item is required. An authorizing understanding will empower our organization to expand perceivability and access to our item under a trademark with RIO Inc. A permitting understanding will empower the item to focus on our organization. This is a licensed innovation that can get representative, when s hared and utilized in the correct way. Alarmz ltd should be cautious in entering an authorizing understanding and satisfactory examination ought to be done before with sufficient lawful direction. The understanding is legally binding between Alarmz ltd and RIO Inc., or whatever other organization that we may decide to work together. In this understanding, RIO Inc. can abuse our item, procedure and assembling it, however obliged to pay us sovereignty from the offer of the item. The authorizing understandings will give Alarmz ltd satisfaction in benefits that will be accomplished by the creation and offer of the caution. In making a permitting understanding, we will offer constraints to RIO Inc, who isn't the

Taliesin West - Organic Design in a Desert Garden

Taliesin West - Organic Design in a Desert Garden Taliesin Westâ began not as a fantastic plan, however a basic need. Forthright Lloyd Wright and his understudies had voyage a significant distance from his Taliesin school in Spring Green, Wisconsin to manufacture a retreat lodging in Chandler, Arizona. Since they were a long way from home, they set up camp on a stretch of the Sonoran Desert close to the building site outside of Scottsdale. Wright experienced passionate feelings for the desert. He wrote in 1935 that the desert was an excellent nursery, with its edge of dry mountains spotted like the panthers skin or inked with astounding examples of creation. Its sheer magnificence of room and example doesn't exist, I think, on the planet, Wright declared. This incredible desert garden is Arizonas boss resource. Building Taliesin West The early camp at Taliesin West contained minimal more than brief safe houses made of wood and canvas. In any case, Frank Lloyd Wright was propelled by the emotional, tough scene. He imagined a detailed complex of structures that would typify his idea of natural engineering. He needed the structures to develop from and mix with nature. In 1937, the desert school known as Taliesin West was propelled. Following in the convention of Taliesin in Wisconsin, Wrights understudies contemplated, worked, and lived in covers they created utilizing materials local to the land. Taliesin is a Welsh word importance sparkling temple. Both of Wrights Taliesin properties embrace the shapes of the earth like a sparkling forehead on the bumpy scene. Natural Design at Taliesin West Engineering antiquarian G. E. Kidder Smith advises us that Wright showed his understudies to structure in family relationship with the earth, scolding understudies, for example, not to expand on a slope in predominance, yet next to it in association. This is the embodiment of natural design. Hauling stone and sand, the understudies built structures that appeared to develop from the earth and the McDowell Mountains. Wood and steel pillars upheld translucent canvas rooftops. Regular stone joined with glass and plastic to make amazing shapes and surfaces. Inside space streamed normally beyond any confining influence desert. For some time, Taliesin West was a retreat from the brutal Wisconsin winters. In the long run, cooling was included and understudies remained through the fall and spring. Taliesin West Today At Taliesin West, the desert is rarely still. Throughout the years, Wright and his understudies rolled out numerous improvements, and the school keeps on developing. Today, the 600 section of land complex incorporates a drafting studio, Wrights previous compositional office and living quarters, a lounge area and kitchen, a few theaters, lodging for understudies and staff, an understudy workshop, and sweeping grounds with pools, porches and nurseries. Trial structures worked by student designers dab the scene. Taliesin West is home of the Frank Lloyd Wright School of Architecture, whose graduated class become Taliesin Fellows. Taliesin West is additionally the central command of the FLW Foundation, a ground-breaking administrator of Wrights properties, strategic, heritage. In 1973 the American Institute of Architects (AIA) gave the property its Twenty-five Year Award. On its fiftieth commemoration in 1987, Taliesin West won exceptional acknowledgment from the U.S. Place of Representatives, which considered the complex the most noteworthy accomplishment in American creative and compositional articulation. As indicated by the American Institute of Architects (AIA), Taliesin West is one of 17 structures in the United States that epitomize Wrights commitment to American design. Close to Wisconsin, social affair of the waters, Wright has composed, Arizona, parched zone, is my preferred State. Each altogether different from the other, however something individual in them both not to be found somewhere else. Sources Straightforward Lloyd Wright On Architecture: Selected Writings (1894-1940), Frederick Gutheim, ed., Grossets Universal Library, 1941, pp. 197, 159Source Book of American Architecture by G. E. Kidder Smith, Princeton Architectural Press, 1996, p. 390The Future of Architecture by Frank Lloyd Wright, New American Library, Horizon Press, 1953, p. 21

ThoughtSpot

ThoughtSpot INTRODUCTIONMartin: Hi, today we’re in Palo Alto in the ThoughtSpot office. Hi, Ajeet. Who are you and what are you doing?Ajeet: My name is Ajeet Singh and I’m co-founder and CEO of ThoughSpot. We started this company in 2012, I’ve been in the Valley for about seven years, actually eight years now. I came here in 2007 and joined Oracle for a start-up and started a company called Nutanix in 2009 then I started ThoughSpot in 2012.Martin: How did you come up with that business idea of ThoughtSpot?Ajeet: The business idea of ThoughtSpot was primarily I would say driven by the experience I had at Oracle and then the first startup where I worked on Aster Data Systems that was in 2007-2008 and I saw that the data infrastructure was becoming very scalable, we call it big data now. People were coming up with more scalable model of storing lots and lots of data in a cost efficient way but how this data was delivered to the end users that was not changing that was still done using the tra ditional reporting model and thats very painful because it requires a lot of work and experts you need technical experts to build reports for business users. It’s very slow and inefficient process and thats where we saw the opportunity.We saw that in the consumer space there are two billion people using search and the way to find information and we thought what if we could actually provide that user experience for numbers? What if marketing manager would go to a simple search bar and ask for revenue in a particular quarter for a particular campaign they might have done on a product line or whatever they might be interested in and just get the answers on the fly without actually having to go to somebody to say: Hey, can you brief me a report? And go back and forth on what the report should be like, changing it becomes very painful and those kinds of things.We saw there being a huge difference in how people were accessing information at home through Google and Facebook and Linkedin and at work through traditional business intelligence reporting technology and thats the gap we’re trying to fill.Martin: How did you start about it? How long did it take for you to build the first iteration of the product? When did you raise money? When did you talk to first customers?Ajeet: I would say we talked to first prospects even before we started the company. So early 2012 we spent time just learning the market. We realized that this is a big market and theres a big problem.So my way of thinking about startup has been driven more by markets. Picking the right market first is the first matter for me has been the most important thing, the idea actually comes later. What is the market and what is the problem that we can solve? There can be various ways of solving it. But before I get down identifying how exactly we want to solve the problem I want to spend time with customers, I want to look at competition, Im going to look at partners and understand how we might sell a prod uct to them, how people will buy my product in those markets and things like that.So we spent about six months just studying the market and talking to prospects, talking to partners talking to be people who sell to these companies, just learning. And once we figured that out then we learned about the problem obviously and then we went to the white board and we said, What would be the most awesome way of solving this problem? The most simple way? Because technology has become very complex and lot of innovation now is just bringing simplicity to complex way of doing things because complexity means you’re going to be slow and it will be very expensive to do things. Make them simple, lot of people can do those tasks and then do it more efficiently and they can do it easily.So we came up with this idea that if you apply search to analytics it can actually be 10X to 100X difference in how people operate today. Then we started defining the product, defining our architecture of the produc t and spent about six months on designing the product. When I say design I’m talking about the technical design, some part of UI design. Because what we’re building is very UX driven but in the back there is a lot of complexity that we have to deal with. So it was important to make sure that all platform is architectured well so when we go to market we dont have to go iterate and iterate.Martin: At what point in time did you think about talking to investors?Ajeet: So this being my second startup. I already had some existing relationships with some investors. As I said my previous company I started 2009 and that company has actually done really well so in the process I had the opportunity to work with Lightspeed Ventures and Khosla Ventures and both of them are great investors great people. For me its only been about people because the kinds of things we do for some people it might look crazy. Only thing that is guaranteed is the experience of working with awesome people. So it w as basically working with the same sort of folks, making me sure that we are going after the market and a problem that is highly valuable, we spent time on that and raising money itself was I would say not the biggest challenge that we had to overcome.BUSINESS MODEL OF THOUGHTSPOTMartin: Ajeet, let’s talk about the business model of ThoughtSpot. So what are basically the customers that you are targeting and especially in terms of the functions that maybe more adoptive to your solutions? And exactly what is the value proposition besides only being simpler to get access to data and analytics that you deliver to those customers?Ajeet: We currently are focused on mid to large enterprises (Global 2000), that is the way I would categorize my market segments and within these we are building a solution that is designed for business functions (sales, marketing, operations, supply chain, finance, and so forth) but what were building is very scalable. So we can go to a large company and pote ntially they might have 50,000 people that would want to use ThoughtSpot. So this is a solution that can start small with a few hundred people and then on time you can scale to thousands of people.So we do also get involved with IT departments, so typically a director or VP of Business Intelligence would be someone we will to talk to, or somebody from the business side. And the value proposition for them is imagine you were talking to marketing person, a head of marketing, whois primary responsibility is to reduce customer churn, then they have currently existing way of looking at data of how the churn numbers are over time and how different campaigns might have an effect on churn. We would go in and demonstrate to them with our technology they can get access to their churn data in a much more granular and much more ad hoc way, because theyre launching campaigns and this is actually a real example. Previously it would take them two to three months to find out what the effect of the campaign was on their churn numbers, now they can do that in a few minutes. So launching campaigns and next day as soon as the data starts to come in I can go in and understand how major numbers are changing by geography by product line on those kinds of things and then based on that I can then optimize which campaigns I do more, which campaigns I do less, and things like that.We now have customers that are across almost all major industry verticals (retail, financial services, telecom, manufacturing, and so on), so we work with a whole range of people.Martin: From my point of view the major benefit of ThoughtSpot is that you’re making it super easy and accessible for people to access the data in a company. How does a customer of you ingest the data into ThoughtSpot and how do you set a specific user rights to data because maybe only the c-level management would like to have access to financials and some other people should not?Ajeet: So were doing to data / to enterprise data wha t Google did to newspapers. Long time ago people used to get information from newspapers and it was published by a few people and it was then formatted, it had headlines and there’s a front-page and sports page and so on. It was very rigid in structure because only a few people could publish the newspaper. But with Google now anybody can go in and find information they want and the news they want and things like that.When we apply the same model to enterprise the user experience model remains the same but other things change. The kind of things that changed I would say number one is the type of data we’re going after. Google and most of search engines that are out there, the data they’re ingesting are documents, there are web pages, radios, videos and things like that. What we’re going after is, we are connecting to the most valuable data assets in large companies. So that data sits in their ERP system or data ware houses or any kind of databases, now we have Hadoop, it’s complicated environment.So the type of data we have to deal with is very complicated, so we had to build a new kind of search technology that can understand all the complexities in the databases like tables and joints, columns and things like that. And it was done from scratch.Now when youll use, search and analyze this data the performance expectations are also completely changed because in our traditional reporting environment your report comes back in 20-30 seconds and that’s considered fast. But if you’re in the search bar, the user expectation is very different. So our search engine is backed by a very high performance computational engine that can take data from hundreds of tables and billions of rows and do joints on the fly and give results to end users at certain speed.The third big change is security as you said. People want to get enough data across departments, across different levels and things of that nature.And last but not the least, I will say the biggest way in which we differ from a classic search engine is accuracy and trustworthiness of the data. Because if I am looking for friends on Facebook or im looking for books on Amazon, or Im looking for coffee shops on Google Ill get probably 10, 20, 30 results for any given search where I’ll have to pick which of them is relevant for me. There is no guarantee that something is going to give me an answer which Im interested in, but if I’m giving ThoughtSpot in the hands of a hundred marketing analysts or hundred financial analysts or thousands of people in an organization that might be doing very specific functions, they are used to getting data from reports or Excel sheets. They will not accept guesswork.So we have to build the technology that does not do any guesswork, it actually uses intelligence that is already there their data and uses that combined with the inputs from the user through the search bar and always gives them one single result. Even though on the front it’s very simpl e, in the backend we had to handle scale and complexity of data and we have to handle security and governance. And the nice thing is that when we go to our customers with ThoughtSpot the business users are happy because all of them can access data on the fly whenever they want to. IT department is also happy because today IT department is buried under a long list of report requests and theyre always behind. Some of them told us they feel like report monkeys and they build more and more reports as opposed to going to the business and saying what kind of data can I give you so that you can make better business decisions.With ThougtSpot IT can be in the business of finding new data sources, provisioning new data sources and putting security and governance around them and business users can access the data that they’re supposed to access.Martin: Ajeet, how did you acquire the first one or two customers? How do you convince them: Guys, please give me access to the most precious data th at you have and I give you some kind of answers to that?Ajeet: In the Valley and elsewhere as well there is a model of working with your investors to get access to initial customers. We also do that and it is extremely helpful in making introductions to potential customers. But at least for me the way we like to build the company is it has to be done in an organic way and what I mean by that is we have to find a natural fit between what we are building and the segment of the market that will be interested in.When Im going through the process of defining and building the product the exact specific market segment is not that well known and also how I place the product to them and how they will they use it, what’s important and what’s not that also is not known. So you go through this process of finding the product market fit. The product market fit is better if it is done organically by the company itself where you might have I would say 18 months before we had a product we had an inside sales person who was reaching out to people, calling them and doing demos. About a year before having a product, we had a full sales team and these are expensive sales teams, you can spend anywhere from half a million to a million every year on sales team. But for the kinds of things we are doing it typically takes 12 months to figure out what exactly is the product market fit. Is my product good for small companies or is it good for big companies? If it is good for big companies who are the people that I need to talk to? Who will be more in the buying process and what do they look for? What features are important? All this has to be discovered in the field organically.If you just depend on your own network which is friends and family, or you depend on investors then youll go to people who will try your product because there was an introduction that was made or they are your friends. And that might give you false positive because they would say: This is awesome, this is grea t. I love it. You dont know if theyre saying that because they love you or they love the product. They can also be false negative because maybe theyre not the right users for the product that you are building the right user is somewhere else.So I think it has to be a good mix of reaching out to the network as well as organic outreach with a bias I have a personal bias towards organic outreach. And in our case this is what we did, we reached out to people organically, we showed them the product, we got their feedback and where the best fit we went after those. Since we were building enterprise product and the data is very sensitive (that’s what you were hinting at), it is on-premise product so we’re actually going to deploy our product inside the firewalls of a customer so that they dont have to worry about data security and those kind of things.Martin: Did provide your first customers just free trial to show the value and then after youve shown the value then you said: Okay, let s put some revenue numbers behind that? Or did you start in the beginning: I would like to put some dollar sign on that?Ajeet: Yes, even our beta were paid, our first beta were also paid. We didnt want to give our product out for free even for trial because it leads to the same situation I was talking about earlier. You end up with people that just want to kick the trials either because you know they have fun keeping trials with new technology or taking it because theyre doing a favor to you and your investors. But if you ask for even $1, asking for $1 is so much more valuable than giving your product away for free. So the goal there is not to make money and fund your business, the goal is to make sure that the problem youre trying to solve is a real problem.So if I go to a business and it is lets say an accounting firm that wants to understand how should I do all my business and which of my customers are the most profitable for me that has to be a real problem so that I know you if the product actually works there is product promise that has to match with the business problem and then value can get created. So its very important to make sure that youre going after real problems and not just trying to to get lucky or have some good accidents along the way and eventually get to success.Martin: Ajeet, lets talk about the technology of ThoughtSpot. If I’m a potential client and Im signing up to ThoughtSpot, how does it work then? How is your machine learning working?Ajeet: The way we thought about building the product was we want make it simple on the frontend for the end users but we also want to make it simple on the backend for IT to set it up. Because traditional products theyre very clunky for business users to end users we call them humans so we like to call ourselves analytics for humans, average human beings might be experts in sales marketing but not in analytics should be able to access data. So you want to make it simple for the humans on the fronten d but on the backend also there is a lot of work that is done to set up BI products. You have to kind of enter the data source obviously, then you have to talk to the business users and say: Which reports do you want? And for those reports I have to identify where the data will come from, what kind of data model Im going to need, if the query is going very slow I might have to build what is known as cubes (it’s basically pre-aggregation).I would do those computations over night, so next morning you can look at your revenue for each country. But if you wanted to look at revenue by each product line: Oops, I didn’t do that. Thats a problem with that. So you have to define all these things in advance.With ThoughtSpot we leverage lot of memory computing at scale and we have cut down on any sort of pre-computation that is required and every step we tried to make things simple and cut down on any human intervention that might be required. So what we do is we will go to your signing up with ThoughtSpot, we would implement our product, install our product in your data center. That is typically done within a day and we will get you live within 2-4 weeks from day zero. And thats just to give you a sense. The classic BI deployment takes about six months, so we have shrunk that time of six months down to 2-4 weeks for some of the biggest and most complicated data sets that are around there.The way we do this is we connect to data sources and we then build sort of a mirror image of the scheme of these data sources. And then our search engine, as I was saying earlier, has been built to understand all kinds of things that in our scheme, it will understand all the tables and joints and lots of meta data that is already present.A lot of times customers say: My data is dirty and it is not going to be ready for this, which is all data of the world is dirty and our system assumes that the data is going to be dirty and install into their dirty data. But we dont expect you to s ort of massage data in a certain way, or create a particular very specific kind of schema and set it up nicely. If you want to sort of apply a cleaning filter on top of your data so you might get very dirty data and then we allow you to put a simple filter which is a matter of hours and then you can define that and then expose that to your end users. And we will basically go to filter so all the dirtiness is filtered out and we are presenting clean results to end users.So the technology that we have built, the search engine, that leverages all the investments you have made in your data sources already to cut down that time and we dont have to go through the long process of defining any kind of natural language models or any machine learning models and then test them,verify them, and over time we get better thats not the model. On day one we are good, over time it become great.Martin: Ajeet, how did you come up with the revenue model and what is actually driving the pricing? So is i t more like storage, or computational power, or the number of users, or the just companies size? What is driving the revenue?Ajeet: Yes, it’s a good question because if you look at the pricing model that exists in the market today its a per user model. So if you’re a customer and you’re signing up I would ask you: How many users do you think you will have? And you say 100 and Ill try to sell you license for 200. And he’ll say: Give me 150. Lets started with 150 and will see over time where we end.And then IT Department says: We have 150 licenses for this. First of all, since the technology is complex lot of those licenses go waste. And if more people want to access to information, let’s say you go to new department which has 1000 people, then you need to go back to the vendor and again ask them to spend more money with them.The whole idea behind ThoughtSpot is adoption of data. Because today only 22% of people can access data and we want to increase that number significant ly. And for each of those people, we want them to be able to access the data very-very frequently, so we are talking about 10x to 100x increasing adoption of data.So we dont want to penalize our customers on number of users, we do not charge based on the number of users. Even our smallest product skill that will sell to you, you can put unlimited number of users on that. How we price our product is we set up lines and its building block models, Lego block model. So you can drag and stack them as much as you need to scale and you can start small and grow over time, but we do not have any limit on number of users for these appliances.Martin: Is this then query based or data storage based?Ajeet: It’s based on appliance which can find amount of data.ADVICE TO ENTREPRENEURS FROM AJEET SINGH In Palo Alto (CA), we meet Co-Founder CEO of ThoughtSpot, Ajeet Singh. Ajeet talks about his story how he came up with the idea and founded ThoughtSpot how the current business model works, as well as he provides some advice for young entrepreneurs.INTRODUCTIONMartin: Hi, today we’re in Palo Alto in the ThoughtSpot office. Hi, Ajeet. Who are you and what are you doing?Ajeet: My name is Ajeet Singh and I’m co-founder and CEO of ThoughSpot. We started this company in 2012, I’ve been in the Valley for about seven years, actually eight years now. I came here in 2007 and joined Oracle for a start-up and started a company called Nutanix in 2009 then I started ThoughSpot in 2012.Martin: How did you come up with that business idea of ThoughtSpot?Ajeet: The business idea of ThoughtSpot was primarily I would say driven by the experience I had at Oracle and then the first startup where I worked on Aster Data Systems that was in 2007-2008 and I saw that the data infrastructure was becomin g very scalable, we call it big data now. People were coming up with more scalable model of storing lots and lots of data in a cost efficient way but how this data was delivered to the end users that was not changing that was still done using the traditional reporting model and thats very painful because it requires a lot of work and experts you need technical experts to build reports for business users. It’s very slow and inefficient process and thats where we saw the opportunity.We saw that in the consumer space there are two billion people using search and the way to find information and we thought what if we could actually provide that user experience for numbers? What if marketing manager would go to a simple search bar and ask for revenue in a particular quarter for a particular campaign they might have done on a product line or whatever they might be interested in and just get the answers on the fly without actually having to go to somebody to say: Hey, can you brief me a r eport? And go back and forth on what the report should be like, changing it becomes very painful and those kinds of things.We saw there being a huge difference in how people were accessing information at home through Google and Facebook and Linkedin and at work through traditional business intelligence reporting technology and thats the gap we’re trying to fill.Martin: How did you start about it? How long did it take for you to build the first iteration of the product? When did you raise money? When did you talk to first customers?Ajeet: I would say we talked to first prospects even before we started the company. So early 2012 we spent time just learning the market. We realized that this is a big market and theres a big problem.So my way of thinking about startup has been driven more by markets. Picking the right market first is the first matter for me has been the most important thing, the idea actually comes later. What is the market and what is the problem that we can solve? Th ere can be various ways of solving it. But before I get down identifying how exactly we want to solve the problem I want to spend time with customers, I want to look at competition, Im going to look at partners and understand how we might sell a product to them, how people will buy my product in those markets and things like that.So we spent about six months just studying the market and talking to prospects, talking to partners talking to be people who sell to these companies, just learning. And once we figured that out then we learned about the problem obviously and then we went to the white board and we said, What would be the most awesome way of solving this problem? The most simple way? Because technology has become very complex and lot of innovation now is just bringing simplicity to complex way of doing things because complexity means you’re going to be slow and it will be very expensive to do things. Make them simple, lot of people can do those tasks and then do it more eff iciently and they can do it easily.So we came up with this idea that if you apply search to analytics it can actually be 10X to 100X difference in how people operate today. Then we started defining the product, defining our architecture of the product and spent about six months on designing the product. When I say design I’m talking about the technical design, some part of UI design. Because what we’re building is very UX driven but in the back there is a lot of complexity that we have to deal with. So it was important to make sure that all platform is architectured well so when we go to market we dont have to go iterate and iterate.Martin: At what point in time did you think about talking to investors?Ajeet: So this being my second startup. I already had some existing relationships with some investors. As I said my previous company I started 2009 and that company has actually done really well so in the process I had the opportunity to work with Lightspeed Ventures and Khosla Ve ntures and both of them are great investors great people. For me its only been about people because the kinds of things we do for some people it might look crazy. Only thing that is guaranteed is the experience of working with awesome people. So it was basically working with the same sort of folks, making me sure that we are going after the market and a problem that is highly valuable, we spent time on that and raising money itself was I would say not the biggest challenge that we had to overcome.BUSINESS MODEL OF THOUGHTSPOTMartin: Ajeet, let’s talk about the business model of ThoughtSpot. So what are basically the customers that you are targeting and especially in terms of the functions that maybe more adoptive to your solutions? And exactly what is the value proposition besides only being simpler to get access to data and analytics that you deliver to those customers?Ajeet: We currently are focused on mid to large enterprises (Global 2000), that is the way I would categorize my market segments and within these we are building a solution that is designed for business functions (sales, marketing, operations, supply chain, finance, and so forth) but what were building is very scalable. So we can go to a large company and potentially they might have 50,000 people that would want to use ThoughtSpot. So this is a solution that can start small with a few hundred people and then on time you can scale to thousands of people.So we do also get involved with IT departments, so typically a director or VP of Business Intelligence would be someone we will to talk to, or somebody from the business side. And the value proposition for them is imagine you were talking to marketing person, a head of marketing, whois primary responsibility is to reduce customer churn, then they have currently existing way of looking at data of how the churn numbers are over time and how different campaigns might have an effect on churn. We would go in and demonstrate to them with our technolo gy they can get access to their churn data in a much more granular and much more ad hoc way, because theyre launching campaigns and this is actually a real example. Previously it would take them two to three months to find out what the effect of the campaign was on their churn numbers, now they can do that in a few minutes. So launching campaigns and next day as soon as the data starts to come in I can go in and understand how major numbers are changing by geography by product line on those kinds of things and then based on that I can then optimize which campaigns I do more, which campaigns I do less, and things like that.We now have customers that are across almost all major industry verticals (retail, financial services, telecom, manufacturing, and so on), so we work with a whole range of people.Martin: From my point of view the major benefit of ThoughtSpot is that you’re making it super easy and accessible for people to access the data in a company. How does a customer of you i ngest the data into ThoughtSpot and how do you set a specific user rights to data because maybe only the c-level management would like to have access to financials and some other people should not?Ajeet: So were doing to data / to enterprise data what Google did to newspapers. Long time ago people used to get information from newspapers and it was published by a few people and it was then formatted, it had headlines and there’s a front-page and sports page and so on. It was very rigid in structure because only a few people could publish the newspaper. But with Google now anybody can go in and find information they want and the news they want and things like that.When we apply the same model to enterprise the user experience model remains the same but other things change. The kind of things that changed I would say number one is the type of data we’re going after. Google and most of search engines that are out there, the data they’re ingesting are documents, there are web pages , radios, videos and things like that. What we’re going after is, we are connecting to the most valuable data assets in large companies. So that data sits in their ERP system or data ware houses or any kind of databases, now we have Hadoop, it’s complicated environment.So the type of data we have to deal with is very complicated, so we had to build a new kind of search technology that can understand all the complexities in the databases like tables and joints, columns and things like that. And it was done from scratch.Now when youll use, search and analyze this data the performance expectations are also completely changed because in our traditional reporting environment your report comes back in 20-30 seconds and that’s considered fast. But if you’re in the search bar, the user expectation is very different. So our search engine is backed by a very high performance computational engine that can take data from hundreds of tables and billions of rows and do joints on the fly a nd give results to end users at certain speed.The third big change is security as you said. People want to get enough data across departments, across different levels and things of that nature.And last but not the least, I will say the biggest way in which we differ from a classic search engine is accuracy and trustworthiness of the data. Because if I am looking for friends on Facebook or im looking for books on Amazon, or Im looking for coffee shops on Google Ill get probably 10, 20, 30 results for any given search where I’ll have to pick which of them is relevant for me. There is no guarantee that something is going to give me an answer which Im interested in, but if I’m giving ThoughtSpot in the hands of a hundred marketing analysts or hundred financial analysts or thousands of people in an organization that might be doing very specific functions, they are used to getting data from reports or Excel sheets. They will not accept guesswork.So we have to build the technology that does not do any guesswork, it actually uses intelligence that is already there their data and uses that combined with the inputs from the user through the search bar and always gives them one single result. Even though on the front it’s very simple, in the backend we had to handle scale and complexity of data and we have to handle security and governance. And the nice thing is that when we go to our customers with ThoughtSpot the business users are happy because all of them can access data on the fly whenever they want to. IT department is also happy because today IT department is buried under a long list of report requests and theyre always behind. Some of them told us they feel like report monkeys and they build more and more reports as opposed to going to the business and saying what kind of data can I give you so that you can make better business decisions.With ThougtSpot IT can be in the business of finding new data sources, provisioning new data sources and putting security and governance around them and business users can access the data that they’re supposed to access.Martin: Ajeet, how did you acquire the first one or two customers? How do you convince them: Guys, please give me access to the most precious data that you have and I give you some kind of answers to that?Ajeet: In the Valley and elsewhere as well there is a model of working with your investors to get access to initial customers. We also do that and it is extremely helpful in making introductions to potential customers. But at least for me the way we like to build the company is it has to be done in an organic way and what I mean by that is we have to find a natural fit between what we are building and the segment of the market that will be interested in.When Im going through the process of defining and building the product the exact specific market segment is not that well known and also how I place the product to them and how they will they use it, what’s important and what’s n ot that also is not known. So you go through this process of finding the product market fit. The product market fit is better if it is done organically by the company itself where you might have I would say 18 months before we had a product we had an inside sales person who was reaching out to people, calling them and doing demos. About a year before having a product, we had a full sales team and these are expensive sales teams, you can spend anywhere from half a million to a million every year on sales team. But for the kinds of things we are doing it typically takes 12 months to figure out what exactly is the product market fit. Is my product good for small companies or is it good for big companies? If it is good for big companies who are the people that I need to talk to? Who will be more in the buying process and what do they look for? What features are important? All this has to be discovered in the field organically.If you just depend on your own network which is friends and f amily, or you depend on investors then youll go to people who will try your product because there was an introduction that was made or they are your friends. And that might give you false positive because they would say: This is awesome, this is great. I love it. You dont know if theyre saying that because they love you or they love the product. They can also be false negative because maybe theyre not the right users for the product that you are building the right user is somewhere else.So I think it has to be a good mix of reaching out to the network as well as organic outreach with a bias I have a personal bias towards organic outreach. And in our case this is what we did, we reached out to people organically, we showed them the product, we got their feedback and where the best fit we went after those. Since we were building enterprise product and the data is very sensitive (that’s what you were hinting at), it is on-premise product so we’re actually going to deploy our produc t inside the firewalls of a customer so that they dont have to worry about data security and those kind of things.Martin: Did provide your first customers just free trial to show the value and then after youve shown the value then you said: Okay, lets put some revenue numbers behind that? Or did you start in the beginning: I would like to put some dollar sign on that?Ajeet: Yes, even our beta were paid, our first beta were also paid. We didnt want to give our product out for free even for trial because it leads to the same situation I was talking about earlier. You end up with people that just want to kick the trials either because you know they have fun keeping trials with new technology or taking it because theyre doing a favor to you and your investors. But if you ask for even $1, asking for $1 is so much more valuable than giving your product away for free. So the goal there is not to make money and fund your business, the goal is to make sure that the problem youre trying to so lve is a real problem.So if I go to a business and it is lets say an accounting firm that wants to understand how should I do all my business and which of my customers are the most profitable for me that has to be a real problem so that I know you if the product actually works there is product promise that has to match with the business problem and then value can get created. So its very important to make sure that youre going after real problems and not just trying to to get lucky or have some good accidents along the way and eventually get to success.Martin: Ajeet, lets talk about the technology of ThoughtSpot. If I’m a potential client and Im signing up to ThoughtSpot, how does it work then? How is your machine learning working?Ajeet: The way we thought about building the product was we want make it simple on the frontend for the end users but we also want to make it simple on the backend for IT to set it up. Because traditional products theyre very clunky for business users to end users we call them humans so we like to call ourselves analytics for humans, average human beings might be experts in sales marketing but not in analytics should be able to access data. So you want to make it simple for the humans on the frontend but on the backend also there is a lot of work that is done to set up BI products. You have to kind of enter the data source obviously, then you have to talk to the business users and say: Which reports do you want? And for those reports I have to identify where the data will come from, what kind of data model Im going to need, if the query is going very slow I might have to build what is known as cubes (it’s basically pre-aggregation).I would do those computations over night, so next morning you can look at your revenue for each country. But if you wanted to look at revenue by each product line: Oops, I didn’t do that. Thats a problem with that. So you have to define all these things in advance.With ThoughtSpot we leverage lot of memory computing at scale and we have cut down on any sort of pre-computation that is required and every step we tried to make things simple and cut down on any human intervention that might be required. So what we do is we will go to your signing up with ThoughtSpot, we would implement our product, install our product in your data center. That is typically done within a day and we will get you live within 2-4 weeks from day zero. And thats just to give you a sense. The classic BI deployment takes about six months, so we have shrunk that time of six months down to 2-4 weeks for some of the biggest and most complicated data sets that are around there.The way we do this is we connect to data sources and we then build sort of a mirror image of the scheme of these data sources. And then our search engine, as I was saying earlier, has been built to understand all kinds of things that in our scheme, it will understand all the tables and joints and lots of meta data that is already present .A lot of times customers say: My data is dirty and it is not going to be ready for this, which is all data of the world is dirty and our system assumes that the data is going to be dirty and install into their dirty data. But we dont expect you to sort of massage data in a certain way, or create a particular very specific kind of schema and set it up nicely. If you want to sort of apply a cleaning filter on top of your data so you might get very dirty data and then we allow you to put a simple filter which is a matter of hours and then you can define that and then expose that to your end users. And we will basically go to filter so all the dirtiness is filtered out and we are presenting clean results to end users.So the technology that we have built, the search engine, that leverages all the investments you have made in your data sources already to cut down that time and we dont have to go through the long process of defining any kind of natural language models or any machine learn ing models and then test them,verify them, and over time we get better thats not the model. On day one we are good, over time it become great.Martin: Ajeet, how did you come up with the revenue model and what is actually driving the pricing? So is it more like storage, or computational power, or the number of users, or the just companies size? What is driving the revenue?Ajeet: Yes, it’s a good question because if you look at the pricing model that exists in the market today its a per user model. So if you’re a customer and you’re signing up I would ask you: How many users do you think you will have? And you say 100 and Ill try to sell you license for 200. And he’ll say: Give me 150. Lets started with 150 and will see over time where we end.And then IT Department says: We have 150 licenses for this. First of all, since the technology is complex lot of those licenses go waste. And if more people want to access to information, let’s say you go to new department which has 10 00 people, then you need to go back to the vendor and again ask them to spend more money with them.The whole idea behind ThoughtSpot is adoption of data. Because today only 22% of people can access data and we want to increase that number significantly. And for each of those people, we want them to be able to access the data very-very frequently, so we are talking about 10x to 100x increasing adoption of data.So we dont want to penalize our customers on number of users, we do not charge based on the number of users. Even our smallest product skill that will sell to you, you can put unlimited number of users on that. How we price our product is we set up lines and its building block models, Lego block model. So you can drag and stack them as much as you need to scale and you can start small and grow over time, but we do not have any limit on number of users for these appliances.Martin: Is this then query based or data storage based?Ajeet: It’s based on appliance which can find amou nt of data.ADVICE TO ENTREPRENEURS FROM AJEET SINGHMartin: Let’s talk about your advice for first time entrepreneurs. This is your second company. What have you learned along the way where you said this was a major learning for me going forward and I will never forget this lesson?Ajeet: Yes, there are lots of them. If you talk to anybody who has being at the startup at any capacity its the best place to learn. So my number one advice is to find amazing startups and spend some time there either in a full capacity or an employee. Because if youre someone whos driven by passion for creation which is most of people are at least here in the Valley and many other places in the world where large technical talent. So when working at the startup aou see the opportunity to have a much more open playing field where you can have your ideas come to life very quickly.If you are starting as an entrepreneur I like not to be very prescriptive about these things because every situation is very diff erent. But for me I think what is important is understanding the risk model you’re opting into, either directly or indirectly. I like to look at risks in two dimensions: market risk and execution risk. Is there going to be a market for my product, the idea that I have? And that is market risk. And if I am actually successful then i is going to be valuable that’s how I look at market risk. And I also look at the history of companies that have become successful in this market. And if I see a market that has 10-20 billion plus dollar companies built in the last ten-fifteen years that tells me that this market is large and it supports building large independent companies. On the execution side it is Can I actually build the project that Im talking about and sell it? That is the execution risk.So I personally like to go after opportunities that are very low in market risk and very high in execution risk because I don’t want to spend several years of my time and some of other peopl e time and find that there is no market for my product. But we want the execution risk to be high because you want to set a high bar for anybody else to be able to copy what you’re doing.So that is one model and Im not saying that should be the only model. There is a way of building companies that falls in this bucket. There is another model that is high market risk and low execution risk at least to begin with where I dont know if there’s a market. If you think about Uber or something else, its questionable whether market risk is low or high. But lots of consumer startups would come in that bucket.But what you have to focus on is really mitigating market risk before you do much execution. So understand the risk profile you opting into and focus on that part first. If your execution risk is high then mitigate execution risk by thinking through the product you’re going to build and thinking how you will set it, thinking through the architecture of the product before you start c alling. If your market risk is very high get the hell out of your office and go out and understand what the market is like, prototype and understand all the lean startup stuff.Martin: And assume you would have checked the market risk which is low and now the question is if youre checking on the execution risk how do you identify whether you potential solution will be like 10x or 100x better than existing solutions?Ajeet: I think some of that comes from what people call it vision. Its like you understand the market and you understand the problem. Now I was saying early in the interview, the way I like to think of the idea is what is the most awesome way of solving the problem? And the most ideal way if I had infinite money and infinite amount of people, everything? What is the most ideal way of solving this problem? And then go from there, then you start to make it viable and fix the execution risk. So I would say in the beginning it has to be driven by your vision and passion and g ut. There is no sort of science to it, big part of building a company is making gut calls.Martin: Ajeet, thank you so much for sharing your knowledge.Ajeet: Thank you, Martin. Thank you so much for having me.Martin: Great! And if you have a company and you dont know whether your business people are really checking all the data and getting the most out of, check out ThoughtSpot. Thanks.

Marketing As A Business Philosophy - 1378 Words

The concept of marketing to many people can often be simply perceived as trying to sell a product. Although, marketing is much broader than trying to sell products, it’s a philosophy that is complex which has many internal and external factors that all link back to the customer and value, which benefits should exceed the costs for both exchanging parties. This essay will initially explore the focus of marketing as a business philosophy and then explain the rationale behind the idea of successful marketing by providing essential information on the marketing concepts. The essay will then focus on the theory behind customer value and how it is subdivided into four segments whilst highlighting the different types of value that is associated†¦show more content†¦For Zoos Victoria even though it would be the adult who acts as the purchasing agent, marketing their membership to children would also be a focus as this would benefit them as they are a user of the product. From a similar perspective (Drummond Ensor, 2005) elucidates that business philosophy of marketing is that the provider offers goods and services to the customer, and the customer in return offers a purchase, support and loyalty. This relationship between the customer and provider is successful when both of them receive value, meaning the benefits from the exchange outweigh the costs they outlay. As for the zoos membership when the joining of a membership occurs the zoo (who is the provider) benefits from the transaction with the purchase of the membership, and the loyalty of choosing to visit the three zoos of Victoria. In return the customer receives the benefit of obtaining a membership and being able to visit any of the three Victorian zoos at their discretion. Understanding marketing may not be as simple some people may think it is. According to Kotler, Shaw, Fitzroy and Chandler (1983) marketing can be actually controversial because so many people can be involved and affected by marketing in many ways. In relation to the membership certain people may think that the marketing of producing a zoo membership is unnecessary and is just another form of the zoos to generate money. However some other may think that the idea ofShow MoreRelatedMarketing, Customer Value, and the Link1750 Words   |  7 Pagesthe center of business. In order to survive, companies need to acknowledge the fact that business now revolves around customers (Keith, 1960). As a result, marketing becomes one of the most prominent philosophies in business. Therefore, to get a better understanding of today’s business, this essay will be discussing about three important concepts. 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Importance of Life Revealed in Erich Maria Remarques All...

Importance of Life Revealed in Erich Maria Remarques All Quiet on the Western Front Erich Maria Remarques classic war novel, All Quiet on the Western Front, deals with the many ways in which World War I affected peoples lives, both the lives of soldiers on the front lines and the lives of people on the homefront. One of the most profound effects the war had was the way it made the soldiers see human life. Constant killing and death became a part of a soldiers daily life, and soldiers fighting on all sides of the war became accustomed to it. The atrocities and frequent deaths that the soldiers dealt with desensitized them to the reality of the vast quantities of people dying daily. The title character of the novel, Paul†¦show more content†¦We do not fight, we defend ourselves against annihilation. It is not against men that we fling our bombs, what do we know of men in this moment when death is hunting us down (113). Bà ¤umer also sees that the wars effects on people makes them seem physically less than human; he explains A man cannot realize that above su ch shattered bodies there are still human faces in which life goes its daily round (263). Paul accurately sums up the wars most powerful effect in one simple sentence, Our knowledge of life is limited to death (264). The war not only makes the lives of the dead less valuable; it makes those who survive have a different, more seize the day, outlook on their own lives. The deaths of friends and acquaintances in the war makes those who survive place more value on their own lives. After Kemmerichs death, Bà ¤umer feels a new-found vigor for his own life, I breathe the air deeply. The night lives, I live. I feel a hunger, greater than comes from the belly alone (33). Because of the vast amount of death and destruction, Bà ¤umer and his fellow surviving comrades have to take things as lightly as we can, so we make the most of every opportunity (232). Bà ¤umer sees the value of his own life and is cognoscente of how important it is to survive, no matter what it entails. We lie under the network of arching shells and live in a suspense of uncertainty, says Baumer, It is...a matter of chance that I am

The Benefit of Internet Free Essays

Name: Yoth Laysim Lecturer: Korop Class: Essay Writing D 16/Dec/2010 Reaction to Michael Buble â€Å"Home† One of the well-know songs by Michael Buble is â€Å"Home†. He is one of the pop singers who live in the United State of America. He sings this song to show his feeling when he gets away from the family. We will write a custom essay sample on The Benefit of Internet or any similar topic only for you Order Now In this song, the meaning of it is that after he leaves his family to do the business in Paris and Rome, he feels homesick and his hometown, too.Nonetheless, another summer day is come and gone away, he still want go home at the same time. On the other hand, even in the airplane and other place he is lucky but he still back home. However, there are million people who live with him, he still feels alone. Michael Buble sings this song to all the people all over the world to know about how is bad feeling when they go away from their hometown. When someone goes away from their family, they also feel homesick even who they are. On the other hand, this feeling of homesick, it does not care who we are, it is still in our feeling when we go away from our home. When we go to study abroad, we also feel homesick because it does not like our hometown and everything there does not like everything we have in our hometown. Reaction to my own feeling, after I listened to this song I feel the same like Michael Buble’s feeling too. This song shows us the feeling of the actor who goes away from his family.As a result, my own self when I first arrived at Phnom Penh, I felt very homesick that’s why I wanted to come back home. Moreover, I feel so sad for this man who leave from there family because he have to do his jobs at abroad. Finally, this song is very popular ones that want to show us about the feeling of the man who get away from his family although there are many people living with him in there, he still feel miss his family, too. How to cite The Benefit of Internet, Papers

The Oucasts Of Poker Flat free essay sample

# 8211 ; Overview Essay, Research Paper The Outcasts of Poker Flat is an first-class representation of colour authorship. The secret plan is short and instead developing, merely as the characters are, which is typical of a local colour narrative. The writer portrays a rugged scene which is associated with the West during its gold-rush old ages, every bit good as stereotype the characters into 1s you might anticipate to happen in any Northern Californian colony. Our hero, the gambler, is firm, cool and smart piece ever the lone wolf. He is everything that we would anticipate a true cowpuncher to be. Fictional characters like this won the West, and the writer caters to the romantic imaginativeness of his readers by picturing the traditional rugged lone wolf, but ever a true gentleman. The other characters are every bit typical of colour authorship. The cocotte with a bosom of gold, the rummy portrayed as cockamamie and dishonest ( finally he is the lone true castaway of the group ) , and Mother Shipton embodies the vision that most east cost adult females had of west seashore adult females at the time- lacking of manner and manners. We will write a custom essay sample on The Oucasts Of Poker Flat or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page Besides included in the narrative were Piney and the? Innocent? , both of whom were really much in love and dramatis personae in a romantic, yet virginal visible radiation. Ultimately, I would state that the Mother Shipton, Piney, the Innocent and the cocotte were typical, ( non stereotyped ) , because their characters began to demo true deepness and emotion one time they were trapped. The remainder of the characters were more stereotyped, demoing a lesser grade of deepness and emotion. Although the narrative is written to entertain person who has neer been to a colony in the West, there is a good grade of pragmatism in the narrative, although neer rather making any deep truths about the people- particularly those that were genuinely outcasts. I don? t think that many of the type people who were thrown out of town would give up their last rations of nutrient to salvage person else. In all honestness they were subsisters and would hold fought for endurance.