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Synthetic APIs Shape the Future of Data Acquisition and Management
 

Synthetic APIs Shape the Future of Data Acquisition and Management

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Transcript of a BriefingsDirect podcast on how companies can transform their use of data from a variety of sources.

Transcript of a BriefingsDirect podcast on how companies can transform their use of data from a variety of sources.

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    Synthetic APIs Shape the Future of Data Acquisition and Management Synthetic APIs Shape the Future of Data Acquisition and Management Document Transcript

    • Synthetic APIs Shape the Future of Data Acquisition and Management Transcript of a BriefingsDirect podcast on how companies can transform their use of data from a variety of sources. Listen to the podcast. Find it on iTunes. Sponsor: Kapow Technologies Dana Gardner: Hello, and welcome to a special BriefingsDirect panel discussion coming to you from the 2013 Kapow.wow user conference in Redwood Shores, California. We'll hear how innovative companies are dodging data complexity through the use of Synthetic APIs. We'll see how -- from across many different industries and regions of the globe -- inventive companies are able to get the best information delivered to those who can act on it -- with speed, and at massive scale. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, and I'll be your moderator as our panel explains how they improved data-use benefits from novel information integration to gain business success. [Kapow Technologies is a sponsor of BriefingsDirect podcasts.] Please join me in welcoming our panel: Jürgen Hase and Rüdiger Adam, both vice presidents of the Machine to Machine (M2M) Competence Center at Deutsche Telekom AG in Bonn; Søren Nissen, the CEO and founder of Click A Taxi in Copenhagen; Doug Potvin, the Chief Financial Officer (CFO) at Trinity Logistics in Seaford, Delaware, and Pedro Saraiva, product manager for the Content Shared Platform and Rapid Sourcing at Thomson Reuters in London. One of the things that's been fascinating for me at this conference is to see how efficient “robots” are accessing important data, which elevates the importance of the data very rapidly, which then leads to innovation -- not just efficiency, not just repaving of cow paths -- but in doing entirely new and different business achievements. The end result is often business transformation - and entirely changing the nature of the business. So that's what we're going to be talking about today. Jürgen, tell me a bit about your operations there at the Machine to Machine Competency Center, and why what you’ve been doing with Synthetic APIs has been transformative. Jürgen Hase: We have to collect data from whatever type of sources – structured and unstructured data formats. And for us, for the future, a key driver is how to handle it all, based on end cost. That's really important for us. And this is in a global way. That means it’s not merely a solution for the Germans or for Europe. We have to act in an international way.
    • For this, the Synthetic API is one of the key drivers because we can't add millions of types of APIs on a different technology layer or a different IT layer. We have to use the same way internally. As you know, Deutsche Telekom has many different customer relationship management (CRM) and enterprise resource planning (ERP) systems. And to handle all of this we need a Synthetic API. I believe that makes it simpler and easier for us. If not, we'd have to hire an additional 100,000 people to make it possible. Transformative? Gardner: And just to probe a bit more on that, has this been transformative in an economic sense, as you’ve saved money by doing it this way or has it been transformative in an enablement sense, that is to say, gaining advantage in processes and/or being able to accomplish things that you really just couldn't do? Hase: First of all, machine to machine (M2M) has two aspects. One aspect in general is to optimize process, the customer's process, and one of its key drivers is to collect the data and manage the data in the right way. The second way is to generate new services and make it possible to onboard a customer for an M2M solution. It’s really important that nobody is waiting two months for a running system. We have to do it in one week or in a few days. That's really important. Saving time and saving money are really important. Gardner: Also at Deutsche Telekom, Rüdiger, you've been more involved with the hands-on aspects of doing the synthetic API integration and access, pulling together the means of doing this. I'm interested in that transformation basis. How has this impacted your staff, the workers, the developers, the process analysts - those you have tasked with doing this? What have been the efficiencies or benefits that would be of a transformative nature from that perspective? Rüdiger Adam: It takes a long time to create new interfaces and get data access to all of these systems. It takes around 10-12 months to get it up and running with normal IT development path. Our experience is that we can use a couple of these catalysts and our business logic on top to create prototypes, which run in the short term, 10-40 days. If it's a little bit more complex, then perhaps is takes two months. Then, we can test and prove these, adopt other requirements or business needs, and be very flexible. We're close to the customer, and that's the point that helps us to set up the right requirements.
    • Gardner: Doug, I’d like to go to you next. You’re a little bit smaller than Deutsche Telekom. One of the interesting things about Doug’s organization is he's the Chief Financial Officer, but he's also in-charge of IT. So you can think of him as also the IT Director. This has some benefits. He doesn’t have to argue for funding except in his own mind. Perhaps on the way home, he has a little argument -- the devil on one shoulder and the angel on the other. But, what he has been able to do is act rapidly. Tell us a little bit about what you've been doing with Synthetic APIs and why that's been transformative for your organization? Doug Potvin: It's transformative in the sense that I am not Deutsche Telekom. I am not Siemens. I am not a large name out there in the marketplace. So, my being able to go to a FedEx and UPS and say: "Build an API for me so I can go ahead and interact with your system," is not going to happen, and I know that. Business is easier Finding a way to interact with these websites outside of that has enabled me to do business a whole lot easier and better, and that's what makes it so nice. Now, I can play as a big player, go in and do what I need to do, grab the information, the data and stuff, and then be able to process the data and get their information done automatically. That's able to transform the business right there. Gardner: You started with being able to essentially do something better that was hard before. It was manual and paper-based, and you improved on that. But then, as you told me, you've been able to gain insight into things happening in the external market that put some ideas in your mind about being able to give you an advantage vis-à-vis your competition and also to perhaps to stake out entirely new lines of revenue. Tell us how that's transformative? Potvin: I wasn’t going to enter the Kapplets competition, but just last night, I submitted this idea. It just hit me hearing the discussion of how people were using the technology to go out and look at getting all these carriers who submit to us either by emails or carrier load boards where they are emptied at. Taking all that information, I can have a business development person go out there and say: "Give me all that and do it within a six-month period. Give me all the carriers who maybe emptied in Toledo, Ohio." All of a sudden, I get a list of 12 carriers and those 12 carriers have trucks there, Monday, Tuesday, Wednesday, Thursday, and Friday. All of a sudden, I know I've got available capacity in that market, and I know where those trucks want to get to. Then, I take a robot and say: "Go out to Hoover's and grab all the manufacturing companies within a 50-mile radius of Toledo." Then, through a credit reporting agency I get the traffic spend for those companies, go to D&B and make sure they cleared my credit standards, and I deliver to my business-development people a known list of shippers who meet my credit
    • requirements. All of a sudden, they're not cold-calling. They're making an additional process there. I like Linkedin, because I know these people know people. Therefore, truck managers are going to pick these things up. I may have a referral I can get from one of my existing business partners there and put that all together. My business development person goes from the unknown- unknown to the known-known in a very simple concept. I was talking to my VP down in Texas just this morning. He said: "You know, we’ve got this available-cash list you’re talking about, Doug." Every day we get bombarded with customers who are on a first-come first-serve basis. We and a hundred other brokers get this list of people who want to move lumber, because lumber is pretty cheap, and they want to move it as cheaply as possible. You’re not going to spend a lot of time on something that's a $50-75 market. But, if you can take those two things, where the guy wants to ship a known capacity, have it put it automatically together, give that to the sales guy or the business development guy, now all of a sudden we’re just calling two or three carriers. And if they don't want to haul for the price, we can just stop it and we just go on. It's really the transformation process, and all of this has taken place in two days from the mind thinking about it, based on what you hear how the people are using it. So it's really cool. Gardner: This is a great example of this leap of simple, effective robots that nearly anyone with a little bit of training can use effectively, accessing important data that's dynamic, that leads to new business and therefore is transformative. Let's go to the Søren next, Click A Taxi is an interesting story. You're managing scale, because you're growing so rapidly. You have to be able to do this with finite resources as a startup. You've been able to grow by using more-and-more robots and automating processes. Tell us how the Synthetic APIs approach transforms you as a rapidly growing organization with limited resources? Limited resources Søren Nissen: First off, you mentioned that the keyword for a startup is limited resources. Obviously, we have this ambition that when we go live, boom, it's a success, immediately. It's never like that, but we were hoping that there would be some kind of growth and that we would be signing on more and more cab companies as we went along. As I mentioned yesterday, we needed a really structured process from day one to on-board partners with the direct cab companies, airlines, and whatever. The fantastic thing was that I hired a junior developer, put Kapow in front of him, and
    • he sounds like a PhD in APIs suddenly. You put Kapow in front of a junior developer, and in any partner-integration discussions you have, you just say: "We don't care how we do it. There are no requirements." The airline will ask can you do this? We can. Just that, in itself, is fantastic when using Kapow. There are no requirements from any external partners that we need to comply with, which is great. Gardner: Something is also interesting about your organization. You're dealing with taxicab companies, and when I think of taxicab companies, I think of surly men with beards, coffee, maybe something stronger, yelling at people to do their job. There's not a lot of finesse, not a lot of grace, but an absolute need to get the job done right on time. What's it like dealing with that sort of organization and how has your ability to actually bring IT to them, rather than expecting them to have any IT to bring to you, worked? Nissen: The funny thing is that they actually all live at The Four Seasons and wear suits. No, you're spot on in terms of the kind of people we're dealing with. In the typical cab company we interact with, the general manager will sometimes be answering the phones in their own call center. It's taking some time to perfect our pitch, the first thing is that I can't do any integration. I can send it in an email, and maybe they'll have an SMS gateway in their PBX system from the '80s. The second you mention that we'll automate it and integrate it, they say that's not possible. Before they hang up, we say, "We can do this without you lifting a finger." They don't really believe it, but they we say, "Just send us a password and a login for your Web booking application, and we'll call you in a couple of days and show you it works." Gardner: So again, it's simplicity, being able to take the IT to those who might not be IT people, still getting sophisticated things done, ultimately transformative, not APIs, not software for integration at a platform level. It's a very interesting approach. Next, Pedro of Thomson Reuters, an information company. You are the information broker within the information company. It sounds like a pretty good authority on what works and what doesn't work, when it comes to moving unstructured information around. Tell us what you're doing at Thomson Reuters with this approach of synthetic APIs. Is it transforming your task? Everything is changing Pedro Saraiva: I'm hearing many common themes here. One of them, beyond any doubt, is agility. The world keeps changing. Data is changing. The sources are changing. Our customers are changing. We are changing.
    • So our requirements for content are constantly changing. The ways in which we look at content are changing, and previously it took us months, years, perhaps forever, because we couldn’t even do it. Now, we can look at the source and confidently say two days, perhaps three days, but we'll do it, and we'll get it done. There is a certain amount of excitement about being able to do that. Suddenly, you're thinking, "If I can do this, what will I be able to do next?" It changes the way you look at web- content acquisition, going from being something you don't want to do to something that you want to do more of. The other way in which we can really get a lot of value from leveraging the right technology is to think about synthetic APIs. I just thought about this now. A lot of what we do is exactly that. It's going to a website, a Web source, that has a user interface. They don’t have a structured documented feed, but we need their data. They actually want to provide that data. If we want to automate it reliably and predictably, if we want to have a straight through automation of that acquisition, there is one thing we know we can do, which is build a robot. And we know it works. We are not aware of many technologies that would give that degree of confidence. Can you do it, can you do it now and can you do it quickly? So it really optimizes our task and allows us to focus on what we want to do. Gardner: Another takeaway for me from this event, and it jibes with some of the thinking I have been developing lately as well, is that the traditional IT diagram always has data at the bottom usually represented by cylinders, round objects, icons, and that everything else is on top. The bottleneck is in how well your applications, middleware, or platform can access that data. But, it seems, based on what we're hearing, is that information, especially when it's mission- critical information that needs to be used in processes right in the field, changes that. We should start to think about taking the data from the bottom of the diagram and maybe moving it to the side, because we are going to be accessing data in more ways across the organization’s boundaries as well. So, if you have an ecosystem, a supply chain, a thousand taxicab companies, this changes fundamentally what the data integration requirements are. Therefore we have to think differently about the architecture. I’d like to pose similar questions to our panel and see if they agree. Is it time to rethink the architecture of data at the bottom or is data something that surrounds IT and therefore IT needs to adapt to that? Let's start again with Deutsche Telekom, the biggest company here. Is it time to rethink architecture and even the concept of data now that you can use Synthetic APIs to bring it into processes almost at any point and with significant ease?
    • Accept and adapt Hase: I personally believe that we cannot change the whole world. It takes around 10, 15, or 20 years to change the world from the technology side. We have to accept the world’s existing IT infrastructure, the data format, all of these things, and we have to adapt it. Our part is how we can optimize the data flow between the different layers. On the other side, we'll have more open interfaces and different platforms from different partners, and to adapt all of this in the right form will take more time. For me, it's using technology we can use today, like Kapow Technology, to adapt it. How we can optimize the data world is the second step. It's a journey like with cars. We can adapt new data technology in a car, but in Germany we are selling in the German market around three million new cars per year. So it takes 10 years to change the whole world of the automotive industry from the data formats and all these things, as things coming up from the IT, from the data structure. That means we have to follow the world and adopt the old technologies, the existing technology, and also implement step-by-step new data formats and data structures. Gardner: So as with the previous speaker, the large bank, they have a little bit of everything. It doesn't go away. You have to not just replace, ripping out and bringing in new, you have to have it all and support it all. That's the nature of a large legacy business. Rüdiger, anything more to offer on this concept of a different architectural concept, now that we have such easy ability to access data and use it within our processes? Adam: Due to these different interfaces it's also crucial to reduce the risk of losing data. We heard yesterday also that the absence of data is a problem, and it's also the same for us. So if we are introducing or buying new systems, we look into our key projects, and that means that we get the data access for those purposes. We'd like to be flexible on that too. That's the reason we set up Kapow Katalyst with our solution on top. We're very flexible to adopt other data sources in a very easy way on that one, and to check out what is possible on that. We'd like to transfer this knowledge as well back to the industry. If you'd like to follow this approach and if we can work together on those standardization of interfaces, that would be great. Then we're more up to common requirements. Gardner: Let's go to a mid-tier company, in this case, Trinity. You don't have to follow the architectural diagram. If you want to throw it out and start do something different, you are a bit more flexible and dynamic. I think small-to-medium sized businesses (SMBs) actually have some advantage in agility, particularly when they can start using software as a service (SaaS) and cloud services.
    • Doug, how do you come down on this notion that, I don't need to think about data in some barrel, in some diagram at the bottom, but I can rethink it? Is this an architectural shift for you, how do you view this from the structure of IT? Data always existed Potvin: So the architectural diagram doesn't exist for me in the first place. What it really revolves around to me is that all this data always existed in one format or another. Whether it's in emails, in data, on a website, whether it's some type of report, it all exists somewhere. The ramp- up of the information is just because you can access it on the web, but this information has always been there in one form or another. We enabled the home-type technology. It allows you to get access to the data, which changes everything. That diagram that we're talking about was a very specific amount of data. Now, all this data is completely, as you say, Dana, around the processes. It allows us to attack it in a completely different way. All of a sudden, with the transformation within the business environment with the use of Kapow within that business, people begin thinking, what if. People begin asking if we can do this. I've got this report coming in and I get it weekly. Can we do something with this, so I can extract the data? It's a 15-page report, and I just want two numbers out of it. I just want this section out of it. I can extract that, pull it, and give it to them, so they can make a real-time business decision without going through the entire fluff to find what they are looking for. Gardner: At the other end of that typical architectural diagram with all that data, structured data at the bottom, we've had the client, the PC, and for lack of a better way, the killer app of data on that PC has been the spreadsheet, at least for many internal business processes, for many organizations and how they run things. Let's go now to Click A Taxi. You've just started this business fresh. Do you use spreadsheets? Are they a problem or a good thing for you? Nissen: We do use spreadsheets, but we use it very little. Spreadsheets still work very well for budgets and stuff like that. But then we used social collaboration tools and actually a tool called Podio, which is fantastic. It’s an evolution of Microsoft SharePoint. But as I have mentioned a couple of times, if a daily process of any person in the company takes more than 30 minutes, we want to build a robot to automate it and get rid of it. The funny thing is that I have a finance background. Kapow and the decision around Kapow started as a pure, almost cost-benefit financial analysis. How many developers can I potentially cut away and how much of my call-center expenses in Romania can I cut away by buying this
    • piece of software. Okay, it checks out. I’ll buy it. But when you, as an organization, have been working with Kapow for six to nine months, it evolves from being originally a pure financial decision to actually becoming that I can innovate much faster than I could before. Gardner: And do you use your Kapow robots to access any of those spreadsheets? Nissen: We do, yes. Gardner: And do you then also have what we would consider traditional data, say structured relational data that you are also perhaps tapping in some manner or another with a robot? Nissen: We use it in all ways and forms to connect sources. Different types of data Gardner: So, there it is, from the side. That’s what’s interesting to me. Now, Pedro, in your organization, dealing with many different types of content, both from news organizations and financial feeds, real-time, very fast transactional-type information, do these robots also fill that need for you? Is there an ability to tap different types of data and information across the spectrum of the IT landscape? Saraiva: It’s interesting that you asked me that question, because it’s a question I am asking myself right now. Up until now, we've been focused on Web content acquisition. We're now at a stage where we're thinking we've done a good job with this part of the problem. Let’s look at their content acquisition requirement feeds and so on. Perhaps we can take into consideration the availability of technologies such as Kapow and our understanding of how to make them work. Right now, I'm looking at how I would redraw the whole picture and try to understand how far we want to go, why, and what’s going to work best. have a strong suspicion that we'll find that Kapow is going to find its way very quickly to automating and improving the architecture around many areas that we previously didn’t think we were going to use it for. There are other things happening, and they were not planned. That’s also quite interesting. We now have people thinking about Kapplet-type applications. "Here I am in Bangkok, in this office. I do this job. I heard about you." They heard about me, because I've been to this conference and they know about Kapow. They heard about Kapplets and they add one-and-one and say, well this is two. If I talk to Pedro, and he can get me a robot for which I get the Kapplet and I do this, then my job will be much easier. So there is an emerging set of use cases that we haven’t anticipated, and they're being identified almost daily. At some point, there will be a pattern and we'll find a way of looking at it and saying that now we want to really take the opportunity to do something about it, not just on an ad-hoc basis, but we're going to apply Kapow to achieve this new kind of capability.
    • Gardner: Another major trend that we all need to consider these days is the impact of mobility and delivering applications, data, and information to mobile devices but also enabling those mobile devices to be the generators of even more information and data, so that it’s a two-way street. The notion of enabling mobile devices to take the place of manual processes, paper processes, even reducing the size of the device from a PC to a tablet, perhaps even to a smartphone, brings in some issues. But if you have a Synthetic API approach, where you can access it through a browser, perhaps a WebKit browser on your mobile device, a native browser to the mobile device, that again prompts some thinking that would lead to transformation. Let’s go back to Deutsche Telekom. You probably have more insight into this, because you're dealing on the M2M level. Is there anything now about rethinking data coming from the device into the IT infrastructure that the Synthetic API approach, the robot approach, is transformative? It's a fairly open-ended question, but let’s think about this now from getting the device or the person in the field or the taxicab on the city street as the input to the larger information landscape. Adam: Mobility is an important one for us, as we lead to build up the right combination. When we started, it was classical voice and then the smartphones to collect the data. Nobody is using it for voice. Everybody is using it for mobile Internet. The next step, the next wave, is coming up from the Internet of things, M2M. Combining the data But we have to combine it. On one side, we're collecting data from the device, from the machines, and to the back end system, to the classical IT. There, we have to use it to think about new IT infrastructure, how to combine it, how to use intelligent robots for the smartphone part. We have to also take feeds from the residential market and from the enterprise market, combine it in an intelligent way, and then send it back to the customer to choose the devices and to manage the world. There are a lot of opportunities to think about how we should use this new technology in a really intelligent and smart way. Gardner: If I hear you correctly, the opportunity to make all these devices, from the sensor in the chip to the person with the data-connected smartphone, the input entity, then we're going to start to see a whole lot more data. But is this data that should be going back to those cylinders at the bottom of the architectural diagram? Should they be going to the cloud? They probably will be going to all of those places, and so again this strikes me as a transformative step, in itself. Making the mobile tier the input device changes the architectural requirements for the data, but probably in ways that favor the synthetic API access to that data over time. That’s my theory. What do you think?
    • Adam: From my point of view, it’s really important. We have just read that per person, per user they will have about six devices to deal with. From tablets to smartphones to the normal PC, people would like to be very flexible. For us, as a company, it’s crucial also to deliver this data in a secure mode. Very high security is the center of all. So we need a very clever logic so that this data is not used by others. That’s one of the keys, but the presentation and the information that we would like to make available to those parties or people should be always the same, and that’s the big challenge for us as well. Devices are changing. The standards are changing. Today, they're using JavaScript. Tomorrow, they'll also have a Google solution in place. Apple is working on its own application system. So this has to be harmonized. This has to be also the same standard for us. The presentation should be the same for that one. And the data and the cloud should be accessible at any time and should be presented in the same manner. That’s the point. Gardner: So we're talking about big data, but we're not talking about it just in the traditional warehouse infrastructure. We’re not talking about big data in the context of a business intelligence (BI) application set. We’re talking about it across more consumer-type activities, but we still need to deal with this data in a governed, secured, managed way. So, we're facing some problems. From your perspective Doug, you don't probably have to worry about big data so much. You just want to access the services and the results of big data. You’re not going to be building out a warehouse. But, from this point of mobility and then those implications of the volume of data going up, how do you prepare your organization to take advantage of the big data without it being chaotic, knowing that you’re down the food chain, on the receiving end of the analysis. Potvin: Our mobility is not necessarily for us. We’re in an office with a phone and the computer, and that's pretty much what we do. We do it every day. We've had discussions about providing a mobile app for carriers, for value partners. Available publicly If we give them the mobile app, a lot of this information is available publicly. We know that they're going from point A to point B hauling our product or hauling the shipper’s product. We can give them the application saying here’s all your rest stops, here’s all the diesel stations, here’s the pricing of the diesel station, and think about it adding value to them. If we can add value to our carriers, it strengthens that relationship even more so. It's now a matter of using data to strengthen the partnerships that we have. When I get back to the office Monday, I'll be getting the mobile app dusted off, bring it back up, and add in a few more notes to this whole situation. Extracting information is already out there brings value to all the way up and down the entire process for us, entire vertical market.
    • We value our customers, our carriers, and our team members, and we value the communities that we find ourselves in. So, if we can add some value to these relationships, and strengthen those relationships, it's looking at data not just from my use and perspective, but also from strengthening the relationships we have. Gardner: We have one more line of questions for our panel.  What interests you about what you've heard and what might you think would be the top requirement for the next initiative for Kapow, based on your business needs? Why don't we start with you, Doug? What would you like to see from Kapow next? Potvin: We're just looking for better information coming off those PDFs and to be able to parse them a whole lot better than what we're currently able to do. That's the biggest thing, because the generation of that data that becomes critical to us. Gardner: Okay. Deutsche Telekom, same question. What, if you had a dream wish and you were the only client of Kapow, and they had to listen to you absolutely 100 percent, what would you ask them to do? Hase: For us, it's how to monetize it, not to monetize for Deutsche Telekom, but together. That's really important. We have to adapt all the different hundreds of partners of solution into the whole system. For me, that’s one of the key points that we have to think about together with Kapow, because we are not the experts on robots. We're a transport company provider, not experts of robots. Gardner: Okay. Rüdiger, your wish-list. Adam: From a technical point of view, I think it's important as well to be very flexible, also to be flexible in providing data as a service. If this is possible, I would appreciate working with Kapow on those topics. Gardner: Very good. Pedro, any thoughts about what you've seen in terms of future direction and/or wishes for your organization? Saraiva: I would like Kapplets anywhere. I would like to take a little sexy button and just throw it across the room, so that someone can just plant it on their application. Gardner: How would you refer to that? If you could brand that capability, what would you call it? Kapplets Anywhere Saraiva: Kapplets Anywhere.
    • Gardner: Kapplets Anywhere. Saraiva: Kapow would probably prefer to call it Kapplets Everywhere. Gardner: Kapplets Everywhere, okay, very good, as opposed to Windows Everywhere, that wouldn't matter. Saraiva: No, there might be an issue there with trademark on them. Gardner: Søren, do you have a wish list for things for the future? Nissen: Yesterday, we were talking about directions for Kapow, and this would probably be a really long-haul project for Kapow, spending time with the institutions that determine how websites are built. Google has guidelines and tags for optimizing a website for their Web crawlers. A lot of small companies out there have one Web developer, and that one Web developer doesn’t also have time to build a very neat and nice API. So, if Kapow would work with the HTML institutions and build guidelines where a Web developer could simply use a Kapow widget in some entry field, and select it as mandatory, this is a tag equals this, this is the data structure, and Kapow would wrap it as a RESTful API. So the small 1 to 10 people companies that don't have the resources to build an actual RESTful API with Kapow widgets inside the HTML code could just push one button and turn it into a RESTful API. Gardner: Kapplets Everywhere Ready Website Standard . . . awesome. Well, I’m afraid we’ll have to leave it there. You’ve been part of a special BriefingsDirect panel discussion, coming to you from the 2013 Kapow Wow user conference in Redwood Shores, California. We’ve been exploring the latest in real-time data acquisition, rapid information integration, and proven ways to extract business value from big data across multiple sources. And we’ve now heard how innovative companies are dodging data complexity through the use of Synthetic APIs -- and in doing so transforming their businesses. Please join me in thanking our panel: Jürgen Hase and Rüdiger Adam, both vice presidents of the Machine to Machine (M2M) Competence Center at Deutsche Telekom AG in Bonn; Søren Nissen, the CEO and founder of Click A Taxi in Copenhagen; Doug Potvin, the Chief Financial Officer (CFO) at Trinity Logistics in Seaford, Delaware, and Pedro Saraiva, product manager for the Content Shared Platform and Rapid Sourcing at Thomson Reuters in London. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host throughout this series of end-user success discussions. Thanks for listening, and come back next time. Listen to the podcast. Find it on iTunes. Sponsor: Kapow Technologies
    • Transcript of a BriefingsDirect podcast on how companies can transform their use of data from a variety of sources. Copyright Interarbor Solutions, LLC, 2005-2013. All rights reserved. You may also be interested in: • Kapow Mobile Katalyst debuts as new means to rapidly convert web applications to mobile apps sans APIs • Mobile enablement presents challenges, opportunities as enterprises retool apps for the future now • Some thoughts on the Microsoft and Nokia tag team on mobile or bust news • Kapow launches data integration platform for rapid data delivery to multiple devices • Android gaining as enterprises ramp up mobile app development across platforms and business models • Why HTML5 enables more businesses to deliver more apps to more mobile devices with greater ease • Web Data Services Extend Business Intelligence Depth and Breadth Across Social, Mobile, Web Domains