Thursday, February 5, 2015

Kony gives enterprises the means to make mobile development a force multiplier for business productivity

Orlando, Fla. -- Kony, Inc. burnished its mobile development credentials this week at the Kony World conference here, detailing new updates to its visual tools and platform, expanding its partner ecosystem, and launching a new enterprise mobile app marketplace with the debut of CRM app Kony Sales.

The combined efforts are designed to help businesses gain enterprise-grade mobile productivity fast, leveraging central services and automation, embracing all end-points from a common code base, and encouraging users themselves to tweak their apps best.

"We are going to do to mobile what Salesforce did to web apps with Force,” said Kony CEO Tom Hogan at the Orlando conference, one of three Kony user gatherings set for 2015, with the others soon in Frankfurt and Dubai.
We are going to do to mobile what Salesforce did to web apps with Force

Hogan encouraged enterprise IT leaders to not force their users to make compromises as they seek mobile apps for extending and improving their business processes. Enterprise business users want to have their native interface usability benefits, but developers need to enjoy cross-platform benefits to deliver their apps with speed and security. They can both get their way, says Hogan. [Disclosure: Kony is a sponsor of BriefingsDirect podcasts.]

 "Consumers won’t tolerate the pace of enterprise IT,” said Hogan, pointing out that demand for mobility has led IDC to predict that 25 percent of IT budgets by 2017 will go to supporting the mobile enterprise.

Trouble in mobile pursuits

At the same time, says IDC, 50 percent of enterprises are having trouble linking mobile front ends to the rest of IT. This is where Kony is focusing its efforts, to bridge the divide between what users demand and enterprises can responsibly deliver in enterprise mobility.

Competitive pressures are trumping IT efficiency, forcing a higher pace and larger budgets to attain effective mobility, says Hogan. A leading mobility analyst agrees.

"We are at the end of the golden age of the standalone app," Forrester Principal Analyst Jeffrey Hammond told the Kony user crowd. “Instead, we’re now in a mobile mind shift, with the vast majority of users already on mobile devices,” he said.

Forrester surveys show that "improving customer experience” in using mobile apps is now much higher among the very top of planned business initiatives, says Hammond.

Factoring "effectiveness, ease, and emotion" are keys to designing good mobile apps, he continued, adding that business should "own an equal share of determining a mobile strategy. … By doing this, you actually help IT get the job done better,” says Hammond.

A big hold-up for mobile apps velocity, however, is the need to code each of multiple end-point platforms, says Hammond. Continuous delivery and fast feedback via analytics is only just beginning but is essential for mobile apps development in-house at enterprises.

To do rapid test and release mobile app dev -- and to gain that feedback loop -- enterprises need force multipliers like stronger tools and platforms with automation, says Hammond. They also need to gain more of the skills needed for a mobile-first capability.

"Kony MobileFabric is a good example of the kind or architecture enterprises need to do proper mobile development," says Hammond.

That's behind the Kony drive to expand its role in a lifecycle approach to enterprise mobile attainment, as the company announced a growing ecosystem of partners that are offering new “ready to run” applications via Kony’s cloud-based business mobile app marketplace.

The Kony Marketplace offers a collection of ready to run apps, reusable components, and design templates. These allow the growing list of partners to speed the process of adopting and delivering mobile apps to meet business demand.

The new partners, who will offer their solutions throught the marketplace include: Broadstrokes, Factual, InfoStretch, Knack, PopcornApps, Quinscape, Redora, Softechnologies, Splyt, Stefinini, UST Global, VeraSynth, and ZineOne.

“Industry experts are predicting that the demand for mobile apps will dramatically increase for enterprise organizations in the next few years,” said Burley Kawasaki, Kony senior vice president of products. “To meet this demand, enterprises are looking for ways to empower their businesses to rapidly deliver secure, enterprise-level mobile apps with great user experiences. Our goal is to provide a rich collection of pre-built apps and app models through the Kony Marketplace, which they can use to quickly build their mobile apps."

Mobile apps are way different

And these new mobile apps need to be designed differently, because they are different. They are typically situational, with dynamic requirements, in high demand, possibly throw-away, and often like consumer apps, said Van Baker, Gartner vice president and leading mobility analyst, to the Kony World crowd on Thursday.

User experience is the key, echoed Baker for other speakers at the conference. "User centricity is the only option. It must bring the relevant information to the user in a relevant fashion,” he said. And so mobile technology needs to adapt to people, not the other way around, he says.

And today’s mobile apps are just a stepping stone. By 2017, 50 percent of today’s deployed mobile apps will be rewritten or replaced, said Baker.

Traditional IT is being shunted aside by those who will get their mobile apps one way or another. Indeed, shadow IT spending is going to 50 percent, and so will be the third largest IT budget item, said Baker.
By 2017, 50 percent of today’s deployed mobile apps will be rewritten or replaced

So IT needs to deliver tools to the enterprise that business analysts can use to make mobile apps, IT will not keep up using waterfall-style code-based development, says Baker. So IT will end up surrendering the client development to business analysts using visual tools, concludes Gartner’s Baker

Other predictions from Baker: By 2018, more than half of all business to employee mobile apps will be created by business analysts with codeless tools like Kony’s. And by 2020, web- and mobile-style app integration will have fully displaced traditional approaches, he said.

That jibes well with what researcher IDC has predicted, that the number of apps optimized for mobility will quadruple by 2016.

Given this sea-change in the enterprise, Kony has moved quickly to help businesses provide mobile-first apps for their sales teams. Kony this week released its first ready to run Kony Sales app suite, featured in the new Kony Marketplace. The mobile productivity extension app for SAP and Salesforce allows sales representatives to:
  • Increase sales rep productivity
  • Manage tasks and follow-ups
  • Accelerate pipeline activity
  • Manage leads, accounts, opportunities and contacts, and
  • Work offline to capture information while traveling, and then sync it to the back-end once they return to the office. 
Built on top of Kony’s Mobility Platform and composed with Kony Modeler, the Kony Sales app can be easily extended, configured and customized by business analysts and sales operations personnel. Kony Sales is optimized for iOS and Android phones and tablets, and has the ability to receive upgrades while preserving customizations.

Expect more business-centric apps like Kony Sales soon, targetng such arenas as finance and healthcare. Kony's ISV partners will help drive the creation of these market-driven apps, said Kony officials.

Composition tool set

Also available this week is Kony Modeler, a powerful visual, composition toolset for business users to assemble and configure mobile-first apps from reusable, lightweight app models available in Kony’s app marketplace. With Kony Modeler business users can rapidly customize their apps for unique industry requirements, business units and processes, and then immediately deploy the changes to end-users on iOS or Android phones and tablets.

Powered by Kony MobileFabric, the enterprise mobile back-end services platform, has also been extended with the addition of a brand new App Services layer that enables IT to power these model-driven applications and allows them to be configured and deployed to the cloud. It enables rapid customization, automatic upgrades and versioning, and significantly lower total cost of ownership (TCO) for ongoing app maintenance.
Enterprises are looking for ways to empower their businesses to rapidly deliver secure, enterprise-level mobile apps with great user experiences.

"We are really excited about our partnership with Kony and our presence in the Kony Marketplace," said Debjani Deb, CEO and co-founder of ZineOne, a real-time mobile messaging platform. "Our solution helps businesses increase conversions on mobile by instrumenting their app with our light-weight, easy-to-use SDK. This enables them to actually have real-time conversations with their customers within the app itself to enhance experience and increase engagement."

“Knack Systems is happy to partner with Kony to bring enterprise mobility solution to its customers. Organizations currently using SAP solutions will be able to quickly empower their mobile workforce by leveraging Kony’s flexible mobile platform and solutions fully integrated with their SAP ERP and CRM solutions,” said George Kaadi, Managing Director Client Services and CIO Advisory, Knack Systems.  “Knack Systems is a niche consulting firm with experience in SAP and Kony technologies that helps customers to enable their mobile workforce to be more efficient and provide better customer experience.”

As enterprises adopt more of a strategic approach to mobility, they change the way they do business, not just attach new front ends to business services, says Forrester's Hammond.

Developers that bring the most context to the mobile app and associated processes wins, said Hammond at Kony World. Think mobile-first, but make sure it’s part of a true enterprises mobility strategy, including the inout from both IT and business, he said.

Looking to the future, Kony expects even more end-points to enter the picture -- from wearables and the Internet of Things -- and need to be addressed with a rapid app development capability. Forrester agrees.

"Expect with wearables a shift from mobile moments to micro moments to hold a user’s attention," says Hammond.

Yet even as the complexity around mobility increases, enterprises are still confronted with the need to get their essential mobile apps to market faster, to modernize their mobile apps lifecycle, and to gain and embed the ability to constantly revise and adjust mobile apps amid myriad back-end services and APIs.

It's into this opportunity that Kony is focused and building global momentum, said Hogan in summing up the conference.

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Tuesday, February 3, 2015

Rapid matching of consumer inferences to ads serves up a big data success story

The next BriefingsDirect big data innovation success story uncovers how New York-based adMarketplace, a search syndication advertising network, uses big data to improve its search advertising capabilities.

In part two of our series on adMarketplace, we'll explore how they instantly capture and analyze massive data to allow for efficient real-time bidding for traffic sources for online advertising. And we'll hear how the data-analysis infrastructure also delivers rapid cost-per-click insights to advertisers.

 Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy.

To learn how, BriefingsDirect sat down with Raj Yakkali, Director of Data Infrastructure at adMarketplace, at the recent HP Big Data 2014 Conference in Boston. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Tell us about adMarketplace. What do you do, and why is big data such a big part of that?

Yakkali: adMarketplace is a leading advertising platform for search intent. We provide the advertisers with the consumer space where they can project their ads. The benefit of the adMarketplace comes into play where we provide a data platform that can match those ads with the right user intent.

When user searches for a certain keyword, they're directly telling us what they want to see, and we match it perfectly well with our ads. The relationship that we have with our advertisers is that we match them well and make it accessible in exactly what the user is thinking. We do some predictive analytics on top of what the user is saying. We add that dimension to our user search and provide ads aptly.

Gardner: I'm all for getting better ads based on lot of things I already get. Do you have more than just keywords in terms of how you can draw inference, and what sort of scale of data are we talking about when it comes to all that inference information about an intent on behalf of the consumer?

15 dimensions

Yakkali: Keyword search is one side or one dimension of the user search. There are also category campaigns that the advertisers are running. At the same time, there's a geospatial analysis to it as well. There are 15 dimensions that we go through to provide an ad that is perfectly fit for the advertiser and for the consumer to see and take advantage of to meet their needs. With some of the ads, we are trying to serve the user’s requirements and needs. With all these variables, this sounds like you're going to be gathering an awful lot of information. You also need to reply back with your results very fast or you lose the opportunity for that consumer to get the ad and then even click through and make a decision. Tell me about scale and speed.

Yakkali: You're right on with that question. In this business, latency is your enemy. If you look into the certain metrics, there are almost a half a billion requests that we're receiving every day and we have to match all of those ads with a sub-second performance. We have internal proprietary datasets, which we take care of before matching these ads. And there are two platforms that we've built internally.
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One is called Bid Smart. That performs the analysis between the user intent and the traffic sources that the user search is coming from. At the same time, the price of that ad goes to the publisher. There are the pricing strategies, the traffic sources, and the user intent of the search. All of these things are put together. That predictive analytics system gathers all this information and emits the right ad towards the consumer.
With the partnership with Vertica, we’re able to take the dataset, derive analytics about it, and provide our marketers with all that information.

On top of it, if you look into the amount of data, those half a billion requests that are coming into our system, it generates around two terabytes per hour. At certain times, we can't store all of it for analytics. There is a lot of data that's not inside the database. Now, with the partnership with Vertica, we’re able to take the dataset, derive analytics about it, and provide our marketers with all that information. Bid Smart is the one that does the pricing and matching.

The other thing is Advertiser 3D, which provides that detailed analytics into all these dimensions on the metrics. That provides a very good insight. Now, when it comes to the competition or the opportunity to deliver the right ad at the right time, that's where data work flows make a difference.

We utilize Vertica to directly stream all this click data into it, rather than going into certain other locations and then doing it in a batch format. We directly live-stream that data into Vertica, so that it is readily available for analytics. Our Bid Smart System makes use of that dataset. That's where we get the opportunity to deliver much better ads, with price tags, and the right user intent matched.

Gardner: It sounds very complex. There's an awful lot going on for just serving up an ad. I suppose people don’t appreciate that, but the economics here are very compelling, the more refined and appropriate an ad can be, the more likely the consumer is to buy, but there are a lot of resources that don't get wasted in the meantime. Do you have any sense of what the payoff is, either in business, financial, or technical terms for when you can really accomplish this goal of targeted advertising?

Conversion rate

Yakkali: So our conversion rate is a major key performance indicator (KPI) when it comes to understanding how well we are doing. When we see higher conversion rates, that gives us the sense that we've done the best job and user is happy with what they are searching and what they are getting.

At the at the same time, the publishers, as well as the advertisers, are happy, because the user is coming to us again and again to get that similar, beautiful experience. The advertisers are able to sell more products that meet the needs of the user. And the users are able to get the product that really caters to their needs. We're in the middle of all these things, trying provide the facilitation to the advertisers, as well as the users and the publishers' space.

Gardner: I daresay this is the very future of advertising. Now for you to accomplish these goals and create those positive KPIs, are you housing Vertica in your own data center, do you use cloud, hybrid cloud? Given that you have different platforms, different datasets, how do you manage this technically?

Yakkali: On that end, we started with testing cloud two or three years ago, but again, it turned out that because of so many unknowns and troubleshooting, we had to go with our data centers. Now, we host all our systems in our own data centers and we manage it.

We have our own hardware to deal with. Our system is a 24/7, and we have to be able to deliver the sub-second latency performance. Having your own infrastructure, you have the controlled environment where you can tweak and tune your system to get the best performance out of it.
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Considering that it is a 24/7, there are fewer excuses that you can get away with in not delivering it. For that, we do innovation in terms the data flows and the process of how we ingest the data, how we process the data, how we emit the data, and how we clean up the data when we don’t really need it.

All these things have to come together, and it really helps us having that control on all of our infrastructure and all elements in the data pipeline, starting from the user intent and user search, until we provide the data and the results.

Gardner: How long have you been using Vertica in this regard and how did you go about making that decision?

Yakkali: We've been using Vertica for four to five years and our data pipeline was not on Vertica to start with, but as Vertica came into the picture and we saw the great beauty and the powerful features that it brings to capitalize our ability.

That really helped us. With Vertica in place, we have been migrating our mechanics slowly to use it for the real-time analysis and real-time bidding and all those beautiful features that make us do what we can do better. So it’s been a great partnership with Vertica and we see many more features coming in with the new version. Our Bid Smart mechanism is also improving, and with that, algorithmic capabilities are increasing. So it’s progressing.

Feedback loop

Gardner: Tell us a little bit about where your business is heading. In addition to speed, complexity, and scale, where do you see the ability to create this feedback loop? It’s very rapid feedback loop between a lot of incoming data and an action like streaming up an ad. It seems like this could be applied to either other marketing or advertising chores or perhaps even have an ancillary business-development direction. You’ve got this platform and these data centers. Is there something else that you're gearing up for?

Yakkali: At this point, we're in the business of connecting the advertisers, the publishers, and the users. But that is an untapped business to what it can accomplish. The market has started its pathway towards the level of reaching that epitome. If we take a step back and try to understand it, initially, when search started, there was no Google or anything. It was more about curated search.

So the publishers put out all this content together and then projected it out to the user. They didn't know what user wanted. At the same time, when the user looked at this content, they didn't know whether they want it or whether it catered to their needs.

Then, Google came along and user search started. What that directly told was "I want this piece of information. I want to use this piece of information. And I want to see this ad that is relevant to my needs." That’s a very powerful thing. When you hear that part, you're able to analyze that piece and match it properly with the advertisers. But then again, it started to fragment.
At this point, we're in the business of connecting the advertisers, the publishers, and the users.

Now, it’s not only Google. There is Yahoo, Bing, there is mobile, and there are certain apps. There are many apps in the mobile space and each one has its own search. So not all the searches are going to Google, Yahoo, or Bing. Search is already fragmented.

We tap all those pieces. The market that is beyond Google. Yahoo-Bing is stronger and it is growing. So there is a lot of market that needs to be tapped into. We come into the place connecting the advertisers to tap that untapped marketplace.

We've been improving our internal Bid Smart algorithm that came out in the last year. Then, we also launched Advertiser 3D last year as well. Those two products have been providing tremendous growth in our revenue, and the retention rates have been stellar.

The top 60 percent of Google’s top spenders are working with us to complement their business. At the same time, we're also able to provide 50 percent increase in year-over-year revenues. It's additional revenue for them, and even our revenues are increasing based on that fact.

Gardner: It seems like you have an awful lot of runway ahead of you in terms of where search could be applied, and analytics can be drawn from that to augment these services and explode that market.

Is Vertica being used just for the intercept between the incoming data and the outgoing ad, or you are also analyzing what goes on within these marketplace so that you better appreciate, whether you can offer reports, audit trails, and that sort of thing? Is this an inclusive platform, or do you use different analytics platforms for different aspects of what you are doing?

End to end

Yakkali: We do almost everything. It is an end-to-end platform. As part of the business we look into the operational metrics of the whole thing, starting from the user search until the ad is delivered. Then, from that end, there is always that analytics piece that comes onto play, which provides insights to the marketers.

Our market base is filled with the very data-savvy marketers, and they look into each and every data dimension to understand their return on investment (ROI). We give them transparency through our Advertise 3D System and utilizing that, they're able to navigate through the space and aptly tune their campaigns to get the best out of it and to deliver the best to the customer.

Gardner: Any thoughts about other organizations that are also facing significant challenges around speed, scale, also perhaps with a big runway, in terms of knowing that more and more business could be coming their way therefore more data? What would you advise them in terms of the data architecture or the planning in order to accomplish the goals?

Yakkali: When we look at the industries and the market, the ad industry still is untapped. The healthcare industry is just getting into the business of doing much more with analytics. It’s all about the speed and the latency and the insights as well. One, at the operational level and the other, at the insight level to do more innovation on top of it.
Our market base is filled with the very data-savvy marketers, and they look into each and every data dimension to understand their return on investment (ROI).

The ability to listen to the customer depends on how fast you can capture all that feedback, and you tighten that loop of feedback so that you're able to do something with it and make a better product out of it.

So it’s all about taking a look at the datasets very closely as to what they mean, what the user is asking us, what do they want to see, and how you are listening to the customer. Those two aspects really make the difference.

You want to listen to the customer, what they really want. Are you providing it and are you able to guess what they want for tomorrow for that predictive, and going into prescriptive analytics, phase later on. You're telling them what they need to do even before they tell you.

That's the stage that the market is going towards. We're not even scratching the surface of prescriptive analytics. The wave has not yet started towards that route. We're still at the predictive analytics phase, and there is still a lot more to go within that space. Get the foundation stronger, drive towards prescriptive analytics, and listening to your customer, are the three aspects that would make any industry. Those three would be the key foundational pieces for making innovation.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.

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Thursday, January 22, 2015

adMarketplace solves search intent challenge with HP Vertica big data warehouse

The next BriefingsDirect big data trailblazer interview examines how New York-based adMarketplace, a search syndication advertising network, has met its daunting data-warehouse requirements.

Learn here how adMarketplace captures and analyzes massive data to allow for efficient real-time bidding for traffic sources for online advertising. And we'll hear how the data-analysis infrastructure also delivers rapid cost-per-click insights to advertisers.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Join MyVertica.

For the inside story, BriefingsDirect sat down with Michael Yudin, the Chief Technology Officer at adMarketplace at the recent  HP Discover 2014 Conference in Las Vegas. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Tell us first about what adMarketplace does. It sounds very interesting, but I'm not sure I fully understand it.

Yudin: Well, adMarketplace is the leading marketplace for search intent advertising, and let me explain what that means. Search advertising is the best form of advertising ever invented. For the first time, a consumer actually tells a computer what they're interested in. That’s why Google became so successful as a search engine.

Some things are changing in the marketplace these days. Consumer search intent is fracturing. You probably wonder what this means. It’s very simple. What this means is Google is no longer the only place you go to search for stuff.

I'll give you an example. Last night, I was looking for a Brazilian steakhouse here in Las Vegas. I didn't go on I opened my iPhone and I fired up a yellow pages (YP) app and I entered "Brazilian steakhouse" in the search box.

There are a variety of apps in my phone like that for travel, sports, news, and various other things I'm interested in. Anytime I search there, I don’t go to Consumer search has really fractured and adMarketplace has solved the monetization problem for that.

Providing value

Gardner: So when people are searching in areas other than say Google or Yahoo, how does your organization intercept with that and how does that provide value to both the consumer that’s searching and advertisers that want to provide them information?

Yudin: It benefits both the consumer and the advertiser. In the search world, an ad is really nothing more than a search result in response to user’s query. That’s why it’s so great.

Our clients are the Internet's largest marketers and brands. They use adMarketplace to acquire additional customers in addition to the other marketing channels like Google, where they are pretty much already maxed out. are only so many searches that happen in Google and they're declining. So advertisers are looking for new ways to capture consumer intent and to convert this into sales and measurable return on investment (ROI), and that's what we do for them.

Gardner: Of course, a really important thing here is to match properly, and that requires data and analysis -- and it requires speed. Tell us a little about the requirements. How do you do this technically?

Yudin: You just nailed it. This is a very, very big data problem and it has to be solved at scale and fast. And it’s also a 24x7 problem. We can never take our system down. We have a global business, and anytime you go and you search for something as a consumer, you expect to see the result right away.
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Our network handles about half a billion search queries per day and this results in about two terabytes of data per hour constantly generated by our platform, across multiple data centers. We needed a very scalable and robust analytical data warehouse solution that could handle this. Two years ago, we evaluated a number of vendors and settled on HP Vertica, which was best able to satisfy our tough requirements.

Gardner: And are these requirements primarily about the scale and volume, or are we talking also about a need for rapid query, or all the above? Give us a bit more insight into the actual requirements for your network?

Yudin: That's a great question, and I think this is what makes Vertica unique. There are products out there that can store a lot of data, but you can't get this data out of these solutions quickly and at high concurrency. We require a system that can ingest large amounts of data constantly. I am talking about terabytes and terabytes of data. This data has to be queryable right away, with very low latency requirements.

Some of our queries for Advertiser 3D and analytical dashboard are preplanned queries obviously, but they are very big data queries and the service-level agreement (SLA) on these queries is two seconds. Very few products can do that. Some queries are obviously more complex, but we're still talking about seconds and not hours.

Concurrency requirement

On top of this, there's a concurrency requirement and that’s a very big weak spot of a lot of products. Vertica is actually able to provide sufficient concurrency, and it’s never enough.

I do know that there's an upcoming release of Vertica 7, where this is going to be improved even further, but it’s quite acceptable right now. And it has to be fault tolerant, which means that it should be able to sustain a hardware failure on any of its nodes -- and it can do that.

Gardner: Tell us a bit about where you've built Vertica in terms of data centers. Are they your own? Do you have managed service providers? How are you managing your infrastructure that supports Vertica and then therefore your data processes?

Yudin: We own our own infrastructure. So these are not managed services. We actually once used managed services, but we've outgrown them. And Vertica runs on dedicated hardware.
This was driven by business requirements. We didn’t just decide that we needed this

We also have several other Vertica clusters that run on virtualized hardware, and even though it’s dedicated infrastructure, it’s really dedicated at the cloud level now. So call it private cloud. It's a buzzword. It's a mix of dedicated and virtualized. It's elastic scaling.

Gardner: And the transition. You mentioned that two years ago, you were searching for a product. How were you able to bring this on board and what sort of growth have you had as a result -- in terms of data volume, but also in your business, in terms of customers and overall business metrics of growth?

Yudin: This was driven by business requirements. We didn’t just decide that we needed this. So we started to undertake a very, very ambitious project -- Advertiser 3D. If you go to our website,, you can read more about it.

This is a very elegant, simple, and yet powerful, system to match and price traffic across a multitude of traffic sources. To deliver this product, we didn’t have a choice. We had to have a powerful analytical back-end data warehouse. That's when we started to evaluate products and chose Vertica.

Gardner: And have there been any other benefits of going to Vertica in terms of being able to increase the number of features, or have you been able to leverage the technology in new business opportunities in terms of what you can offer your customers, not just to have met the requirements, but perhaps whole new types of benefits?
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Yudin: Definitely. Our customers don’t know and don’t even care that we use Vertica on the back end. That’s probably why we won an HP award, because we integrated it into our overall solution very elegantly and seamlessly, but it obviously does a lot of heavy lifting on the back end.

And the project was successful and transformed our business. Our growth rates have accelerated over 50 percent on our core revenue and performance. Data-savvy marketers, and our clients started to see significantly double-digit improvement in ROIs.

Gardner: As Chief Technology Officer there, you've gone through a fairly significant change in your infrastructure and adoption, as you've just described. Looking back, are there any lessons learned that you could offer to others who are also running into a wall with their data infrastructure or looking for alternatives? Any thoughts on how you would advise them to make the transition?

Yudin: Definitely. The number one advice I would give anybody is don’t believe anything until you do two things: Try it yourself and get references from people who actually use this and whom you trust. That's very important.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.

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Wednesday, December 10, 2014

Creative Solutions in Healthcare improves client services and saves money using VMware vCloud Air hybrid cloud

The next BriefingsDirect innovator case study interview explores how a Texas healthcare provider has adopted cloud computing, and in doing so has both saved money and improved the quality of its many services.

Listen to the podcast. Find it on iTunes. Download the transcript.

 At the recent VMworld 2014 Conference in San Francisco, our moderator, Dana Gardner, Principal Analyst at Interarbor Solutions, interviewed Shawn Wiora, CIO at Creative Solutions in Healthcare in Fort Worth, Texas to learn more about the process of adopting cloud, and why cloud has benefited them as a complex organization.

Here are some excerpts:

Wiora: Creative Solutions in HealthCare is the largest independent owner and operator of skilled nursing facilities (SNFs), which are nursing homes, in the State of Texas. We also operate assisted-living facilities and we provide long-term care solutions, primarily in Texas.

We have about 6,000 employees. Many of them are nurses, and many of them are capturing data about our patients and our residents. Our residents are in the thousands and, as a private company, we're able to deliver solutions in the marketplace that are really geared toward lifestyle, care, nutrition, activities, and programs. That's why the company has been so successful -- we have this passionate care about our residents.

Gardner: Of course, healthcare is really changing in terms of how it's using IT and leveraging IT, and I suppose you're no different.

Wiora: That's exactly right. HealthCare has been ramping up in terms of IT, not only catching up with the industry, but in some cases, leading the forefront, especially when it comes to patient care and delivering innovative diagnosis and treatment programs over telemedicine and other types of electronic media.

Gardner:  Why has cloud computing been appealing to you with your requirements? What challenges were you trying to solve when you looked at the cloud model?

Going virtual

Wiora: It's an interesting story. About two years ago, the company was 100 percent physical in terms of its server infrastructure. Similar to many other long-term care facilities, we have to deliver new forms of compliance as it relates to HIPAA, the HITECH Act, and the NIST framework.

So if you take all those, in addition to the new apps that are being required of the organization, new types of health exchanges that we are involved with, the requirements were just escalating dramatically. So we started with a physical infrastructure and we looked at going virtual.

It was a wholesale change ramp-up. We took a big challenge by embarking on an initiative that allowed the company to go from physical to virtual, and at the same time, we went from premise-based to the cloud. We did that together.
Fortunately, we already had some really good experience with virtualization, but by no means did we have a program that was deploying across the server infrastructure. So we issued an RFP and we selected a group of vendors at the top of the pyramid. At that top was Azure, AWS, and VMware’s vCloud. We chose Microsoft Azure.
The team at the VMware understood what we were doing in terms of our timeline, our projects, and our applications that we are looking to move to the cloud.

We started a pilot with Azure, and it was really interesting. We're a Microsoft house, and the team chose Azure based on the fact that not only we were Microsoft house, but we had a number of initiatives that we wanted to move to the cloud, including Microsoft Exchange.

So, we started moving Exchange into the cloud with our Azure program. Then, we asked Microsoft to issue a document that indicated that they would support Exchange, their own software, in Azure, their own cloud, and guess what happened?

We did not get acknowledgment. Ultimately, they would not indicate that they would support their own software in their own cloud. We were flabbergasted. We just couldn't believe it.

We ended up pulling the plug on that project, on that initiative. We went back to the marketplace and we chose vCloud Air, and we quickly ramped up. That's the reason why this project has been so successful -- the ramp-up.

The team at the VMware understood what we were doing in terms of our timeline, our projects, and our applications that we are looking to move to the cloud. That's really where they differentiated, not only between Azure and AWS in terms of their on-boarding, because we did pilots on all those cloud infrastructures. VMware’s vCloud Air team had the best on-boarding process for any kind of IT project that I've been involved with in the past 20 years.

Had our back

It just really made the IT team at Creative Solutions in Healthcare, the company, just feel like those guys really had our back. They really cared about what was happening. They knew that we were under the gun, because we had done this Azure kind of cluster, and it was not even feasible for us to go down the path with our own infrastructure. It ended up being a great partnership.

Gardner: Shawn, tell me to what degree you're hybrid? Do you have an on-premises cloud virtualized set of applications? Do you have another set of applications? You've have opted to go into the public cloud, the vCloud Air. Is this something that you're still sorting out in terms of what goes where? How about the data? Is that also on-prem, and how you are factoring the hybrid approach?

Wiora: We're very deliberate with our cloud strategy. We started with a pilot of some core applications, got our feet wet in the cloud, and then we took that success that we had. Again, the on-boarding that we received in that process was really second to none.

That made the team feel very comfortable with moving other infrastructures. Now, we've moved our entire back-office infrastructure, our accounting, a number of custom apps, provisioning, and supply chain into the cloud with the vCloud Air.
That's what IT should be focused on: how do we ultimately deliver solutions that the other business units, and ultimately our patients, can appreciate.

We're are also in a hybrid environment, as you've indicated. We have servers throughout our facilities and servers at headquarters. We have other software-as-a-service (SaaS) models that we're interacting with. We're moving data from other providers back into our on-premise environment and then we're moving that into vCloud Air. There's a lot of hybrid going on right now.

Gardner: So that integration, management, and orchestration, being able to automate that, seems very important to you. You want to be able to set this up, have it run, and then devote your energy to all these new projects.

Wiora: Yes. That's really where the return is to the company, the shareholders, the board, and the management team. That's what IT should be focused on: How do we ultimately deliver solutions that the other business units, and ultimately our patients, can appreciate.

We're in the long-term care industry and we've been very successful in growing the company based on the passionate, caring model. The IT organization aligns its passion and care toward the patients.

Instead of being wrapped up with servers, virtualization, and all of the other things that VMware is the best at doing, we're outward-focused on the business units and the patients.

New product appeal

Who has more data than healthcare? There are some organizations that have a lot of data, but we track what our patients eat, what time they go to sleep, what they do during the day in terms of activity. We're talking each and every day across each and every facility, thousands of patients.
It is been game changing for the company. It is been game changing for our patients.

So VMware's Object Based storage is something that is in our future.

Gardner: So, one last area for adoption. You have talked about the on-boarding process, but there's also the end-user absorption of new approaches from IT. How this has gone in terms of your end users?

Have they noticed a change in the type of applications? Has it been something that they didn't notice? What's been that result at that end-user inception point when you made this transition to cloud?

Wiora: It is been game changing for the company. It is been game changing for our patients. Instead of being fearful about approaching IT, the business units are coming to IT, and they know that we can ramp up applications very quickly.

We just ramped up our maintenance application in a couple of days. In the past, that would have taken months of planning. The business unit laughed. They just looked at IT and said, "You have to be kidding. This is up and running already?"

Advice for others

Gardner: That's a strong testament. How about advice for other organizations that are beginning that RFP process, that are thinking about cloud, looking at the different approaches, the different providers? Any words of wisdom in hindsight that you could offer now that you have been through that process?

Wiora: Absolutely. Who wants to reinvent the wheel? If I'm looking at going to the cloud for the first time or if I am looking at enhancing my hybrid cloud environment, I would suggest you look at TCO.

Look at what your labor costs are. Look at who the A-Team is in the industry for virtualizing. Look at what the roadmaps are and look at which vendors really don't care what you put in your cloud infrastructure. There are vendors. as we talked about earlier, that really have the ability to approve or disapprove what you put in there.

I'd look at that, but you have to look at TCO and look at partnering with an organization that can help you easily ramp up. Then, I think you look at how you want to run your IT organization. If those things make sense to you, then I would suggest you look at vCloud.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: VMware.

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Wednesday, December 3, 2014

HP launches Haven OnDemand to deliver big data services suite in the cloud

The next BriefingsDirect big data news analysis discussion examines some major announcements made at the HP Discover conference this week, the debut of HP Haven OnDemand, a new set of analytics-in-the-cloud services.

Our panel of users and experts unpacks the details from Barcelona, and explores the implications of the delivery of cloud-based HP Vertica OnDemand and HP IDOL OnDemand components within the HP Haven OnDemand suite.

Listen to the podcast. Find it on iTunes. Download the transcript.

To learn more about how big data changes everything via these new HP cloud offerings, we're joined by Fernando Lucini, Chief Technology Officer for HP Big Data; Howard Brown, Founder and CEO of RingDNA, based in Los Angeles, and Neal Holley, Operations Director at GateWest New Media Ltd., based in Bristol, UK. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Fernando, we've heard quite a bit of news the last few days at the HP Discover 2014 Conference in Barcelona, and HP Software General Manager Robert Youngjohns delivered the details Tuesday about HP OnDemand. Let's look at this from the big picture. Why are data and analytics, combined with the cloud-hosting model and delivery model, such a good fit? Why is this an important milestone for the cloud?

Lucini: It's exciting in a number of ways. If you think about what we've launched, we recognized early that our customers, our partners, and developers out there were going to consume technologies in a new way. This is something that the industry all agreed on. We were just early birds in this and we recognized that it's all going to be about on-demand consumption, self-service, speed, elasticity, and all those nice things.

So in some respects, the industry wants to consume things in this fashion. We recognize it, and then the next step for us is to think about the people and what they're going to do with these kinds of services.

You can think about it in two different ways. You have the people out there in the real world who are creating applications on top of very rich information, and that's the mobile apps that we all use. It's the applications to look at both human information, as well as business information, or very structured information, creating applications that do that. We have that persona and we really wanted to make sure that that developer had all the right tools in that model on-demand, self-service.
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The other part of the equation is the world of the data warehouse, where we have very large amounts of information. We're traditionally applying analysis, but in this new generation, we need the tools that can do this at a bigger scale, can do it quicker, and can be more flexible. This is our Vertica technology and the same kind of on-demand, self-service needs are out there. So the second part of our answer to the question for industry is that we'll provide you an on-demand way to serve that particular purpose.

The announcement comes from a number of good reasons. It provides the market with an answer to both of these peoples' needs. It does so in an incredibly elastic fashion and it does it with incredible richness. It has quite a unique degree of depth and variety.

If you look at the IDOL OnDemand functionality, there are new APIs that you can explore and use with the freemium model.

If you look at the Vertica OnDemand space, it allows you to manage whatever size warehouse you need in an incredibly elastic and transparent way, but still on-demand.

There’s so much to tell. It’s such an exciting time for the industry, and being in HP, leading the charge, is pretty, pretty impressive and important.

Great importance

Gardner: Clearly, this isn't news just for one part of an IT organization. This seems to have a great importance for data scientists, IT operators, developers, even line of business users of business intelligence (BI).

So let's look at this a little bit from the perspective of the IT operator. This is something that's a cost issue in many respects and broadens the use of something like IDOL and Vertica to a much larger market. With it being in the cloud, you don't need to set up your data center and you don’t need to have those capital expenditures.

Let’s start at the top, where we're talking about this as a cloud model. Why does this broaden the market for data and analytics?

Lucini: Go back to this IT operator. This guy or gal has always wanted to provide their business with the tools. There was an element there where these guys want to provide the analysis capabilities, they want to have the ingestion and the features, but it’s a tough thing, as you very well put it. There is capital expenditure, maintenance, and training.

As the differentiator here, the move is that the acceleration is going to be immediate. Let’s use simple examples, I want to be able to take video and do face recognition, extract license plates, extract behaviors, or listen to voice and do something, I want to do that and I don’t want the burden of all the science that goes behind doing these things.
IT operators are going to be incredibly happy that they can provide the business with what the business needs at a lower cost and get outcomes quicker.

This IT operator is going to say, "No problem. Here’s the link. You pay this as you go. Enjoy." And that's as complex as it gets. So the acceleration is going to be immediate, which translates almost immediately to create more and more applications and doing more and more analysis, which is what we all want, at a lower cost point in shorter times.

IT operators are going to be incredibly happy that they can provide the business with what the business needs at a lower cost and get outcomes quicker.

Gardner: This should be of interest to large enterprises that might want to augment their current warehouse approach and strategy. It also sounds like for those organizations that may have been too small or didn’t have the budget to set up their own on-premises data warehouse, they now have an opportunity to walk right into a deep, powerful analytics capability.

Lucini: It democratizes the whole idea of analytics. You want to make it as democratic as possible. Size isn't necessarily important with regards to intelligence, interest, having something to say, or having something to analyze. It’s all about making it democratic, and the cloud really helps in that.

It's also about giving functionality that wasn't accessible to some of these guys. We're talking about very advanced analysis -- technologies for video, voice, or text analysis, let alone warehousing. It’s now available to everybody. They can go in there, test it out, play with it, see how valuable it is to them, and stop dreaming about the value, but make the value. Then, if that’s what they need, they can just start paying as they go and getting on with their lives.

General availability

Gardner: Let’s dig into a little of the details. HP announced Haven OnDemand on December 2, with general availability coming in Q1 2015, so pretty rapidly. Vertica, that’s the one that's coming up first and then IDOL OnDemand is currently available as a freemium model, as you mentioned, on an early access basis, but will be generally available in a few months later into 2015.

What else should we know about the pricing here? Why is this compelling not only as an OPEX versus a CAPEX, but with pricing that is very compelling and attractive.

Lucini: Indeed. In some respects, because you're removing the necessity to open the hardware and to scale it up, we're also providing economies of scale in what we're doing. In HP Cloud Services, we have an amazing cloud that we can go to elastically, and everybody gets advantage of this.

If you think about it, ultimately in one of these models, you get a lot of people come in, have a look, play, investigate, understand, and learn. Then, you get a smaller percentage that actually commit, do the greater applications, and run their warehouses.
You should be in a position where you understand exactly what you're using and what you are paying for it, and it should allow you to toggle back and forth on that need. It’s pretty cool.

It balances out and it allows us to have a lower price point. It also allows us to charge as we go. It allows us a pay-as-you-go model. It all works out. Over time, we'll understand more and more what people want. This is being done in a very collaborative fashion, listening to the market for on-demand.

In the very beginning, we have been very Net Promoter Score focused. I challenge anybody to get yourself a login, and you'll see the Net Promoter kick in.

All the analysis is very much linked to what you want to do, what’s important for you, what’s being used most, and what gives us the most economies. That drives us to be more competitive.

It’s very transparent. It’s very clean. You should be in a position where you understand exactly what you're using and what you are paying for it, and it should allow you to toggle back and forth on that need. It’s pretty cool.

Gardner: As for the actual cloud that this is running on, is there a choice with that or is this starting out on HP Helion Cloud, the HP public cloud. What's the roadmap for the public-cloud infrastructure that this operates on? 

Lucini: At the moment, this is running in HP Cloud Services, which is Helion based of course. It is all designed on top of Helion. So the roadmap for it in the next few courses will be that it will be deployed in any Helion implementation. As long as you have Helion, you can deploy the services underneath.

Of course, Helion is a flavor of OpenStack. So you have the ability to use this in other flavors of OpenStack, but we're principally focused on Helion. We're principally focused on the Public HP Cloud Services and the private Helion implementations with our colleagues from Enterprise Services.

No difference

In some respect in the next year it should be a choice for you to go public cloud for what you need to do. If you're a developer and you just want to create your own app, the private-versus-public doesn’t make a difference to you.

Corporate may want to use this inside a firewall. As you know, in HP we have some of the largest corporates out there. If you're one of these guys and have the need to have that privacy you can install Helion and run these services of top of Helion. Following the HP philosophy, it’s a matter of what the client requires and we'll achieve that.

Gardner: It sounds as if this has been made of, by, and for a hybrid cloud model over time.

Lucini: Correct. Most of our big customers are hybrid, and we're delighted to serve them.

In the meantime, as they o go into a mode of using this stuff on Helion inside of the firewall, they'll still get all the elasticity that Helion provides them. They'll still get all the simplicity that REST and Web Services OnDemand provides them, and the flexibility that Vertica OnDemand provides them for scalability In some respects, there is no downside. There is absolutely no downside to anything that’s happening here. It’s just a matter of choice.
In terms of pricing, I think we're competitive. The features and functions are worth the spend.

Gardner: We'll get to our use cases and the examples of how this is being used shortly, but I just want to look at the competitive landscape. A big player out there, of course, in the public cloud is Amazon Web Services, and Amazon has what’s called It's their data warehouse in the cloud. How does what HP has announced compare and contrast to Redshift? Why is it a worthy competitor and is this price comparable?

Lucini: Of course, guys out there and everybody listening might know Vertica is a leading product in the analytics space and in the warehousing space. So we're coming  at this already as a leader proven inside the firewall.

You get all of the economies, flexibility, and features that Vertica provides; the Flex Zones, all of the optimizations, and the incredible scaling growth factors; and you get it in an on-demand package.

Just because we now have an on-demand version, these things don’t go away. It's quite the opposite. They're immediately available. In that respect, I think we have a strong proposal against Redshift, because you have all the features and functions, not only just the database itself. 

In terms of pricing, I think we're competitive. The features and functions are worth the spend. Our customer base, our history, and our legacy certainly prove that to be the case. Little by little, more and more of the features will seep in, and more customers will start to get comfortable with using it. We already have a few out there in beta land.

We're going to compete. Because of the features, the Flex Zones and other things, we'll carve our own space as well.

What is the differentiator?

Gardner: One of the things that seems unique to me, Fernando, is the IDOL OnDemand being so broad in terms of the types of media, content, information, and data that can now be brought into what’s essentially the type of analytics engine you would only think of for structured information. So it's the best of the structured analytics and high-performance environment, with that breadth and depth of the various types of content. Is that a differentiator in your opinion?

Lucini: Absolutely. I call it everything on-demand. As you notice, I tend not to differentiate between BOD and IOD. The whole philosophy was that we deal with unstructured, structured, and semi-structured information every day to build what we need for our businesses. So why should we see this differently?

If I happen to have an image, it's an image. If I happen to have a file, it's a file. If I happen to have an Excel sheet, it's an Excel sheet. All of these things are materially important. So let’s give our application developer and our data analyst a way to consume all this.

We have the connectors in the cloud, ways for you to suck information into the platform. We have the ability for you to index them and analyze them. We have some protected APIs for you to have a play around with.
It's as broad in analytics as possible. At the same time, it's still market leading in every single one of those APIs.

We have text-mining APIs. Obviously, this is a platform for us. So even though we're using the word Vertica and IDOL, underneath IDOL OnDemand, we have Vertica powering some of our features for user management. All our billing and other APIs are coming up.

It's all about giving the application developer all the tools. What the data is, isn't necessarily important. What's important is that they can process it, use it, extract as much value from it as possible, and make their business successful.

So you are absolutely right. It's as broad data-wise as possible. It's as broad in analytics as possible. At the same time, it's still market leading in every single one of those APIs, which is pretty cool stuff.   
Learn about big data analytics in the cloud
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Gardner: Now, when you're able to bring all sorts of information and media together, when you're able to tap web services, social media, when you're able to create a sentiment engine and a search engine capability, you're really starting to develop intelligence in new ways.

It seems to me, you can gain insight into markets, prospects, competition, customer inclinations, and directions. It's really about bringing more of a data-driven aspect to a business in ways that had really been sort of an art before, something that was not always by experience, but was by gut instinct.

Before we go to our use cases, how are we really changing a business environment here? Are we talking about a data-driven approach? Are we giving the type of tools that will move a marketing organization, for example, from guesswork into a scientific approach to how they make decisions?

Testing instincts

Lucini: You put it very nicely. We're moving into a world where we're allowing instincts to be tested, and tested quickly. In the past, we had a lot of clever professionals in the marketing world making educated guesses about what’s going on, what I like and don’t like, what you like and don’t like, or what’s popular and what’s not.

We're opening the door for businesses to take data, take a sample of it or take it all, it's their choice, whatever that may be, and in whatever varieties they come, to test out their theories, to see if this theory is correct.

I used to call it the CIO conundrum, where the CIO thinks they've got something and it becomes very difficult for them to prove if they do or don’t, and then they question the results when they get them.

We want them to be able to test this out. If they have an opportunity with their voice data and they think there's massive value in the voice data and they want to cross-correlate it to the social presence, do it, and let the data speak for itself.
It's very exciting stuff, because there is a real change in the industry, and we all have to adapt to it.

It's now no longer difficult. Just go into the platform, put the voice in there, put the text in there, use the analytics tools, give us our enterprise resource planning (ERP) warehouse. We'll do the queries and we'll create what we call combinations -- which is everything coming together as one -- and test the value.

Now, it no longer matters that this is not a very large project with very large budget. It will prove out the case. We have a next generation of proving things out and being capable of proving things out.

That might lead you to a very interesting onsite project with our tools, where you're inside a firewall, but you have proven it out. Or it might take you to a very interesting on-demand implementation. Either way you perform the testing or the proving or the thinking in a much more practical way.

It's very exciting stuff, because there is a real change in the industry, and we all have to adapt to it.

Gardner: Let's learn how some people have been using this already to change their business. Let's go first to RingDNA. Howard Brown, tell us a little bit about your company, what you do, and then how you've been using Haven OnDemand from HP?

Brown: RingDNA is a comprehensive sales acceleration platform that allows companies to create high-performance sales teams by combining powerful communications tools with prospect or customer DNA. That's a combination of marketing data, social data, customer relationship management (CRM) data, and account history, and pulling that all together to allow a sales rep to perform sales faster.

Data for inside sales

Gardner: It’s almost as if you're putting the tools of a data scientist in the hands of a salesperson without them having to be a scientist, to get all sorts of information to make the best call on a call in real-time on an inside sales basis.

Brown: You've got it. It's applying a scientific approach to sales. It's taking all of the data that exists out there which can be truly overwhelming, prioritizing it, and making it contextual to make sales much more effective.

Gardner: And this cuts across communications, as well as data, applications, and web services. Is that correct?

Brown: Absolutely. We apply both a theory-testing model and set of communication tools. When a RingDNA customer walks in in the morning, they know exactly who they should be calling, who they should be emailing or texting, and prioritizing the messages so that they know exactly who to call, how to reach out to them,  and what to say.
What HP IDOL OnDemand has provided us is the ability to test all kinds of theories, because every business we work with tends to have a different theory of what a hot prospect may be.

What’s so exciting is that you can start to understand buyer intent from marketing data from past interactions with your customers. We can look at voice transcripts and sentiment analysis and have a whole new way of determining who the right prospect is, how we should be contacting them, and with what messages.

Gardner: So it's up to your organization to take the best of technology, data, and analytics and empower those inside salespeople. It sounds like it's been up to HP to take the best of its technology in the cloud model and analysis to empower you. How, in fact, has HP empowered RingDNA with your early access use of HP Haven OnDemand?

Brown:  It's been truly game-changing. You nailed it when you talked abut taking business information and human information and combining those two. What HP IDOL OnDemand has provided us is the ability to test all kinds of theories, because every business we work with tends to have a different theory of what a hot prospect may be.

They can simply and easily test those theories using RingDNA and HP IDOL OnDemand. If there are buying signals, like someone visiting a website and downloading a whitepaper in combination with other factors, such as that person viewing web pages or maybe tweeting about their product or service, we can look at that buyer’s sentiment through HP IDOL OnDemand.

We're taking a bunch of this data, processing it through IDOL, and making our reps that much more productive and that much more powerful.

Gardner: One of the things you're doing is you are joining and bringing together very disparate data and information and tidbits of analysis. Is HP IDOL OnDemand doing that for you? Are you doing that? How do you make those joins that bring all that information together? Is the cloud the key to doing that?

Cloud is key

Brown: The cloud certainly is the key. We couldn’t deliver the type of product and service we do today without the cloud. RingDNA is all about accelerating a sales team’s ability to close deals. The last thing you want is to negatively impact those teams.

The cloud model means we can quickly implement a RingDNA process within an organization, bring in all that contextual data, bring in all that metadata, and make that rep that much more productive without negatively impacting their workflow.That’s critical to any business today.

It’s one thing to be able to deliver information. It’s another thing to be able to deliver information and insight without negatively impacting the business. Let's face it, in this  day and age, we can’t afford to slow down. With tools like IDOL OnDemand and RingDNA, you’re not slowing down teams. You're actually accelerating them beyond what you ever thought was possible.

Gardner: Fernando, as you're listening to Howard, is there anything about the way that RingDNA is using Haven OnDemand that you think highlights some specific benefits or values here. Are they a poster child for a certain type of way in which you can use Haven OnDemand?
With IDOL OnDemand coming on stream, we’ve found that we had a whole world of options opened up to us.

Lucini: Certainly they understand that they need to use tools to solve their problems and they go ahead and do it. In that respect, it’s great to see. There are a bunch of things we could learn as an industry from them in terms of seeing the opportunity of mixing two pieces of data, how these things collide, and how we get them to customers. I would challenge anybody to check them out because ultimately the end result is key, and I think everybody would be impressed.

Gardner: Let’s go to our next example. We're also joined by GateWest and Neal Holley. Neal, tell us a little bit about GateWest, what you do, and how you’ve been using HP Haven OnDemand.

Holley: We're HP Autonomy partners and have been since about 2002. During that time, we have deployed and maintained many IDOL-based systems. We provide a lot of support services to our clients on an annual basis. We also provide user interfaces to the core engine, our internal development team.

As well as enterprise search, we also specialize in knowledge management (KM). We have a couple of products addressing the management of knowledge, particularly within law firms, and recently we launched an application for the iTunes App Store providing mobile access to IDOL OnDemand, and we see this part of our strategy of what we’ve termed Mobile KM.

Gardner: Tell me a bit more about the iTunes App Store app. What is it called, and how did you use IDOL OnDemand to build it?

Holley: The app is called KnowGate and it was developed in direct response to the offering of IDOL OnDemand. Over the years, we’ve found that IDOL on-premise had a large cost of entry. Obviously, with IDOL OnDemand coming on stream, we’ve found that we had a whole world of options opened up to us. We were very surprised how straightforward it was to take the standard tools for producing the iPhone apps and iPad apps and interface them with IDOL OnDemand.

Great performer

It’s given us that opportunity to bring the technology that we've worked with for so many years and found to be such a great performer and hold the audience that we’ve always wanted to bring it to. The offering has allowed us to do that through its low cost of entry. As Fernando said, it’s democratizing the tools of the very large corporates that we've traditionally worked for.

Gardner: Help me to better understand this. There is no easier way to adopt a technology than to download it for a few dollars from the app store and instantly fire it up on your mobile device. If I were to download that app today, what would I be able to do with it? Who is the typical user? What is the function that that they would gather from it?

Holley: The typical user is predominantly a business user. The first instance is that you would be able to access your KM, your valuable documents or your key information that you need whether in a law firm, or whether it's engineering specifications or your latest contracts.

That’s the first element of it. The second element is being able to actually capture knowledge while on the move and being able to take information from an email or take a photograph of a document, OCR it, and then be able to ingest that into IDOL OnDemand and share it with the rest of your organization.
So it really opens up that kind of ability, and of course, once it’s shared it becomes valuable.

So it really opens up that kind of ability, and of course, once it’s shared it becomes valuable.

Gardner: Very interesting. Fernando, we're seeing with GateWest, this joining of the cloud model with the mobile model. How is that accelerating the use of analytics? That is to say, an application that can gather data and information and extend it to the cloud and then the cloud can create an analytics value and then send it back to that mobile device? How are you seeing that as a powerful new way of broadening the use and value of analytics in general?

Lucini: If you think about it, mobility is everywhere. We all create mobility and mobility apps for everything you have. I'm sure you guys walk around with a mobile device.

We have to be very clear that all of our consumers, even if it's enterprise-consumers versus consumer-consumers, all become little data analysts. We're all much better versed on information than we ever were.

Now you see 18 year-old kids or 20 year-old kids coming out of university and their ability to manage information in their devices, in their environment, is incredible. You no longer have a situation where you can associate analytics from mobile.

Mobile apps are mostly about analytics with some description, certainly about adding value to the data that a user asks you to create it. When I say "create it," I mean create it indirectly, create it by the motion on your wrist, versus you directly writing something down. So you get these two sources of data.

But it's certainly now such a rich space. Let me give you an example. You can take what's coming out of the back of a device, which is probably machine-driven, all the stuff that really the machine produces. You can put that in Vertica OnDemand and that will be your warehouse for doing the analysis on that: What am I doing, when, how, for how long, all that kind of jazz.

Creating context

At the same time, I'm producing the information directly from my mind. I'm creating context, I'm writing, I'm speaking, or I'm recording, whatever the case may be. Now, IDOL OnDemand can deal with that.

Anybody creating a mobile app is not going to want to have a hard server-based infrastructure, because the whole point of mobility is that it is distributed. It is a distributed computing model.

Those are kind of solutions that are on demand, in the cloud, elastic, pay-as-you-go kind of things. They're perfect for this generation, whether it's enterprise or not. The kind of partners we have are guys who understand that their intelligence and the value they add is not necessarily that they know a tool, but that they are the experts in their space and they know how to balance Vertica OnDemand.

I have my machine or business information and I need to do something important with that. I have my human information and anything in between, and it's the understanding of how this information adds values to people’s lives and how they execute them that’s he key.
The beauty of our OnDemand infrastructure is that it was created for everyone. It was created for our customers and it was created for ourselves.

So it's a really important moment. Mobile is the linchpin of much of what's going on around this that makes sense. If you look at any company today, there's no chance that they won't have a mobile intent.

At the same time, we have a lot of hackathons in OnDemand. I can tell you that 90 percent of the products that are created as a result of hackathons are mobile. It kind of speaks for itself.

Gardner: I know. The combination of the cloud-delivery model, analysis on demand, or as a service and the mobile device is just creating entirely new opportunities to add value as a consumer and as a company. It's really flipping many businesses around.

Let’s look at a particular business when we think about the impact of this new series of models and how they interact. I'm thinking about the IT organization in a company, in an enterprise.

With HP Software having a very broad portfolio of applications, many of which are designed and geared towards those IT organizations and developer organizations in companies, how can Haven OnDemand with that analysis-as-a-service capability be brought to bear on other HP software applications focused on IT organizations?

Lucini: The beauty of our OnDemand infrastructure is that it was created for everyone. It was created for our customers and it was created for ourselves. Not to unveil too many wonderful things, but there will be a number of announcements of our own tools, which will be powered by OnDemand. And we made a distinction of what is on demand versus what we call core. It’s our language to speak about our internal use versus our external use.

Organizational tools

These are tools that help the IT organizations.We have tools for backup, where the on-demand model will add great flexibility to what the IT operators can do with the information and how they can serve the legal compliance and partner infrastructures.

We have uses of OnDemand for a wider HP software family where they provide analytics, both for security as well as operational systems, and things like that. So it's a very democratic tool. We recognize that the world of information pivots on two things, and that’s why we created a platform.

It pivots on our ability to incredibly scale up and analyze structured information and semi-structured information. That’s why we have a Vertica core engine. We recognize that human beings create information and so we have our IDOL infrastructure.

And it's these two things together that every single one of our internal partners, IT, our own software product that tender to IT as well as external customers only to leverage this product. And then in some cases it goes very heavily one way, or very heavily another, you have a very, very strong warehouse.
All of our internal partners look at us and say that they're coming at it either from very human or from very machine, or actually in most cases, both.

You always have that road-map of possibility to get you to the other side, either more heavily toward IDOL or Vertica. You can really start, for example, with a Vertica OnDemand warehousing cloud, make it super-flexible, and put information in Flex Zones, really massage that data, don’t be upset by schemas,  and then work as you go, and scale up.

At the same time, think of what if you need some enrichment, what if you need to take some information that’s coming in and asking to say take in your social feed. So I need to take a voice feed and text information, classify it, and put it into my Flex Zones. That is available, and in the opposite direction, it’s exactly the same.

All of our internal partners look at us and say that they're coming at it either from very human or from very machine, or actually in most cases, both. This is the roadmap to get them to take advantage of both in the same platform. So you can see, it's very, very compelling for our internal partners to use, and we are delighted to serve them.

Gardner: I'm seeing a great deal of flexibility on the applicability of this. We've seen from RingDNA how this can help an inside sales organization do things they just could never have done before.

We have seen from GateWest how this is essential to bringing knowledge management and document management to a whole new level by combining the best of cloud and mobile devices.

Then, as you're now saying, we're only scratching the surface about how IT organizations can use the cloud and the analytics as a service for improving their application lifecycle management, their business service management, or their application development test. So it's really an exciting time.

I'm afraid we are about out of time for today’s discussion, but there's a lot more that people can learn at in terms of Haven OnDemand. Let’s just end with one more peek into the future. Fernando, what might we expect next? Where do you think Haven OnDemand will go in the near future in terms of a new type of business value?

Disrupting markets

Lucini: Let me just say that we're going to disrupt a bunch of markets. We're going to be looking to take over some markets out there that have been very traditionally on premise and we're going to try to democratize it. You can guess that we're going to take the world of video and voice and we are going to make that very democratic.

There are going to be lots of interesting things coming out where we're going to allow our customers to create their own APIs and extend the platform themselves. So there is a lot of that to look forward to.
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We'll also be extending our Vertica OnDemand presence, getting more-and-more customers in there and getting more modes, using more of our Vertica technology to add functionality in a REST kind of way, in a web-service kind of way to the on-demand picture, and adding more and more APIs just to reflect the richness of a platform. So it's clear to everyone that this is only the beginning of an amazing story. So there are quite a lot of APIs, but there are many, many more to come. So there is quite a lot to look forward to.

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