How Globe Testing Helps Startups Make Leap to Cloud- and Mobile-First Development

Transcript of a BriefingsDirect discussion on how Globe Testing pushes the envelope on Agile development and applications development management using HP tools and platforms.

Listen to the podcast. Find it on iTunes. Get the mobile app for iOS or Android. Download the transcript. Sponsor: HP.

Dana Gardner: Hello, and welcome to the next edition of the HP Discover Podcast Series. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator for this ongoing sponsored discussion on IT innovation and how it’s making an impact on people's lives.

Gardner

Once again, we're focusing on how companies are adapting to the new style of IT to improve IT performance and deliver better user experiences, as well as better business results.

Our next innovation case study interview highlights how Globe Testing, based in Madrid, is helping startups make the leap to cloud-first and mobile-first software development. We'll hear how Globe Testing pushes the envelope on Agile development and applications development management using HP tools and platforms.

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To learn more about modern software testing as a service we're joined by Jose Aracil, CEO of Globe Testing, based in the company's Berlin office. Welcome to Briefings Direct, Jose.

Jose Aracil: Hi. How are you Dana? Thank you.

Gardner: I'm great. First tell us a little bit about Globe Testing. Are you strictly a testing organization? Do you do anything else? And how long have you been in existence?

Aracil

Aracil: We're a testing organization, and our services are around the Application Development Management (ADM) portfolio for HP Software. We work with tools such as HP LoadRunner, HP Quality Center, HP Diagnostics, and so on. We've been around for four years now, although most of our employees actually come from either HP Software or, back in the day, from Mercury Interactive. So, you could say that we're the real experts in this arena.

Gardner: Jose, what are the big issues facing software developers today? Obviously, speed has always been an issue and working quality into the process from start to finish has always been important, but is there anything particularly new or pressing about today's market when it comes to software development?

Scalability is key

Aracil: Scalability is a big issue. These days, most of the cloud providers would say that they can easily scale your instances, but for startups there are some hidden costs. If you're not coding properly, if your code is not properly optimized, the app might be able to scale -- but that’s going to have a huge impact on your books.

Therefore, the return on investment (ROI) when you're looking at HP Software is very clear. You work with the toolset. You have proper services, such as Globe Testing. You optimize your applications. And that’s going to make them cheaper to run in the long term.

There are also things such as response time. Customers are very impatient. The old rule was that websites shouldn't take more than three seconds to load, but these days it's one second. If it's not instant, you just go and look for a different website. So response time is also something that is very worrying for our customers.

Gardner: So it sounds like cloud-first. We're talking about high scale, availability, and performance, but not being able to anticipate what that high scale might be in any given time. Therefore, creating a test environment, where you can make the assumption that cloud performance is going to be required and test against it, becomes all more important.

Aracil: Definitely. You need to look at performance in two ways. The first one is before the app goes into production in your environment. You need to be able to optimize the code there and make sure that your code is working properly and that the performance is up to your standard. Then, you need to run a number of simulations to see how the application is going to scale.

You might not reach the final numbers, and obviously it's very expensive to have those staging environments. You might not want to test with large numbers of users, but at least you need to know how the app behaves whenever you increase the load by 20 percent, 50 percent, and so on.

The second aspect that you need to be looking at is when the app is in production. You can't just go into production and forget about the app.

The second aspect that you need to be looking at is when the app is in production. You can't just go into production and forget about the app. You need to carry on monitoring that app, make sure that you anticipate problems, and know about those problems before your end users call to tell you that your app is not up and running.

For both situations HP Software has different tools. You can count on HP Performance Center and HP Diagnostics when you're in preproduction in your staging environment. Once you go live, you have different toolsets such as AppPulse, for example, which can monitor your application constantly. It's available as software as a service (SaaS). So it's very well-suited for new startups that are coming out every day with very interesting pricing models.

Gardner: You're based in Berlin, and that's a hotbed of startup activity in Europe. Tell us what else is important to startups. I have to imagine that mobile and being ready to produce an application that can run in a variety of mobile environments is important, too.

Mobile is hot

Aracil: Definitely. Mobile is very hot right now in Berlin. Most of the startups we talk to are facing the same issue, which is compatibility. They all want to support every single platform available. We're not only talking about mobile and tablet devices, but we're also talking about the smart TVs and the wide array of systems that now should support the different applications that they're developing.

So being able to test on multiple operating systems and platforms and being able to automate as much as possible is very important for them. They need the tools that are very flexible and that can handle any given protocol. Again, HP Software, with things such as Unified Functional Testing (UFT), can help them.

Mobile Center, which was just released from HP Software, is also very interesting for startups and large enterprise as well, because we're seeing the same need there. Banking, for example, an industry which is usually very stable and very slow paced is also adopting mobile very quickly. Everyone wants to check their bank accounts online using their iPad, iPhone, or Android tablets and phones, and it needs to work on all of those.

Most of the startups we talk to are facing the same issue, which is compatibility. They all want to support every single platform available.

Gardner: Now going to those enterprise customers, they're concerned about mobile of course, but they're also now more-and-more concerned about DevOps and being able to tighten the relationship between their operating environment and their test and development organizations. How do some of these tools and approaches, particularly using testing as a service, come to bear on helping organizations become better at DevOps?

Aracil: DevOps is a very hot word these days. HP has come a long way. They're producing lots of innovation, especially with the latest releases. They not only need to take care of the testers like in the old days with manual testing, automation, and test management. Now, you need to make sure that whatever assets you're developing on pre-production can then be reused when you go in production.

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Just to give you an example, with HP LoadRunner, the same scripts can be run in production to make sure that the system is still up and running. That also tightens the relationship between your Dev team and your Operations team. They work together much more than they used to.

Gardner: Okay, looking increasingly at performance and testing and development in general as a service, how are these organizations, both the startups and the enterprises, adapting to that? A lot of times cloud was attractive early to developers, they could fire up environments, virtualize environments, use them, shut them down, and be flexible. But what about the testing for your organization? Do you rely on the cloud entirely and how do you see that progressing?

Aracil: To give you an example, customers want their applications tested in the same way as real users would access them, which means they are accessing them from the Internet. So it's not valid to test their applications from inside the data center. You need to use the cloud. You need to access them from multiple locations. The old testing strategy isn't valid any more.

For us, Globe Testing as a Service is very important. Right now, we're providing customers with teams that are geographically distributed. They can do things such as test automation remotely, and that can then be sent to the customers so they are tested locally, and things such as performance testing, which is run directly from the cloud in the same way as users will do.

And you can choose multiple locations, even simulating the kind of connections that these users are using. So you can simulate a 3G connection, a Wi-Fi connection, and the like.

Other trends

Gardner: I suppose other trends we're seeing are rapid iterations and microservices. The use of  application programming interfaces (APIs) is increasing. All of these, I think, are conducive to to a cloud testing environment, so that you could be rapid and bring in services. How is that working? How do you see your customers, and maybe you can provide some examples to illustrate this, working toward cloud-first, mobile-first and these more rapid innovations; even microservices?

Aracil: In the old days, most of the testing was done from an end-to-end perspective. You would run a test case that was heavily focused on the front end, and that would run the end-to-end case. These days, for these kinds of customers that you mentioned we're focusing on these services. We need to be able to develop some of the scripts before the end services are up and running, in which case things such as Service Virtualization from HP Software are very useful as well.

For example, one of our customers is Ticketmaster, a large online retailer. They sell tickets for concerts. Whenever there's a big gig happening in town, whenever one of these large bands is showing up, tickets run out extremely quickly.

Their platform goes from an average of hundreds of users a day to all of a sudden thousands of users in a very short period of time. They need to be able to scale very quickly to cope with that load. For that, we need to test from the cloud and we need to test constantly on each one of those little microservices to make sure that everything is going to scale properly. For that, HP LoadRunner is the tool that we chose.

We need to be able to develop some of the scripts before the end services are up and running.

Gardner: Do you have any examples of companies that are doing Application Development Management (ADM), that is to say more of an inclusive complete application lifecycle approach? Are they thinking about this holistically, making it a core competency for them? How does that help them? Is there an economic benefit, in addition to some of these technical benefits, when you adopt a full lifecycle approach to development, test, and deployment?

Aracil: To give you an example of economic benefit, we did a project for a very large startup, where all their systems were cloud-based. We basically used HP LoadRunner and HP Diagnostics to look at the code and try to optimize it in conjunction with their development team. By optimizing that code, they reduced the amount of cloud instances required by one-third, which means a 33 percent savings on their monthly bill. That’s straight savings, very important.

Another example is large telecommunication company in Switzerland. Sometimes we focus not only on the benefits for IT, but also the people that they are actually using those services. For example those guys that go to their retail shops to get a new iPhone or to activate a new contract.

If the systems are not fast enough, sometimes you will see queues of people, which turns into lower sales. If you optimize those systems, that means that the agents are going to be able to process contracts much quicker. This specific example will reduce to one-fifth of the time by using Performance Center. That means that the following Christmas, queues literally disappear from all those retail shops. That turns into higher sales for the customer.

Gardner: Jose, what about the future? What is of interest to you as a HP partner? You mentioned the mobile test products and services. Is there anything else particularly of interest, or anything on the big data side that you can bring to bear on development or help developers make better use of analytics?

Big data

Aracil: There are a number of innovations that are coming out this year that  are extremely interesting to us. These are things such as HP AppPulse Mobile, StormRunner, both are new tools and they are very innovative.

When it comes to big data, I'm very excited to see the next releases in the ALM suite from HP, because I think they will make a very big use of big data, and obviously they will try to get all the information, all the data that testers are entering into the application from requirements. The predictive test and the traceability will be much better handled by this kind of big data system. I think we will need to wait a few more months, but there are some new innovations coming out in that area as well.

Gardner: Alright, nothing really stays the same for very long in test and development, does it?

Aracil: Definitely not.

Gardner: Okay, well thanks very much. We've been hearing about how Globe Testing is helping startups to make the leap to cloud-first and mobile-first software development. And we have heard also how Globe Testing has helped to push the envelope on Agile and development management for those organizations that it works for.

Reduce post-production issues by 80 percent
Download the HP white paper
Build applications that meet business requirements

So I'd like to thank our guest, Jose Aracil, CEO of Globe Testing, based in Berlin. Thank you.

Aracil: Thank you very much, Dana.

Gardner: Thank you too to our audience, for joining this special new style or IT discussion. We've explored solid evidence from early enterprise adopters and startups on how big data and development efficiencies help change everything for IT, for businesses, for governments as well as for you and me.

I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this ongoing series of HP-sponsored discussions. Thanks again for listening, and come back next time.

Listen to the podcast. Find it on iTunes. Get the mobile app for iOS or Android. Download the transcript. Sponsor: HP.

Transcript of a BriefingsDirect discussion on how Globe Testing pushes the envelope on Agile development and applications development management using HP tools and platforms. Copyright Interarbor Solutions, LLC, 2005-2015. All rights reserved.

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ECommerce Portal Avito Uses Big Data to Master Just-in-Time Ad Fraud Detection

Transcript of a BriefingsDirect discussion on how a Russian ecommerce and search engine site leverages big data analytics to identify fraud.

Listen to the podcast. Find it on iTunes. Get the mobile app for iOS or Android. Download the transcript. Sponsor: HP.

Dana Gardner: Hello, and welcome to the next edition of the HP Discover Podcast Series. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator for this ongoing sponsored discussion on IT innovation and how it’s making an impact on people’s lives.

Become a member of MyVertica
Register now
And gain access to the Free HP Vertica Community Edition.

Our next innovation case study interview highlights how Avito, a Russian eCommerce site and portal, uses big data technology to improve fraud detection, as well as better understand how their users adapt to new advertising approaches.

Gardner

To learn more about how big data offers new insights to the eCommerce portal user experience, please join me in welcoming Nikolay Golov, Chief Data Warehousing Architect at Avito in Moscow. Welcome.

Nikolay Golov: Hi.

Gardner: Tell us a little bit about your site and your business at Avito. It sounds like the Craigslist of Russia.

Golov: Yes, Avito is a Russian Craigslist. It's a big site and also the biggest search engine for some goods. We at Avito have more searches, for example, from iPhones than Google or Yandex. Yandex is a Russian Google.

Golov

Gardner: Does Avito cover all types of goods, services, business-to-business commerce?

Golov: On Avito, you can sell almost anything that can be bought in the market. You can sell cars, you can sell houses, or rent them, for example. You can even find boats or business jets. We right now have about three business jets listed.

Gardner: So quite a diversity. What are your big data needs? It sounds as if in a country as large as Russia -- with that many goods and services -- you have a high-volume-of-data issue.

Size advantage

Golov: The main advantages of Avito is firstly its size. Everybody in Russia knows that if you want to buy or sell something, the best place for it is Avito. It’s first.

Second is speed. It is very easy to use it. We have a very easy interface. So we must keep these two advantages. But there are also some people who want to use Avito to sell weapons, drugs, and prohibited medicines. It's absolutely critical for Avito to keep it all clean, to prevent such items from appearing in the queries of our visitors.

We're growing very fast, and if we use moderators we'll have to increase our expense on moderation in a linear progressions as we grow. So, the only solution to avoid a linear increase in expenses is to use automation.

Gardner: In order to rapidly decide which should or should not be appearing on your site, you’ve decided to use a data warehouse that provides a streaming real-time data automation effect. Tell me what your requirements are for that technology?

Golov: We have various requirements. For example, we need to be able to perform fast fraud detection. The warehouse has to have very little delay. Hours are not permitted, it must be 10 minutes, no more.

Our data warehouse has to be big. It has to store months, possibly years, of data.

Second, we have to have data for long periods of time to learn our data mining algorithms, to create reports, and to analyze trends. So our data warehouse has to be very big. It has to store months, possibly years, of data. It has to be fast, or only slightly delayed, and it has to be big.

Third, we're developing very quickly. We're adding some new services, and we're integrating with partners. Not long ago, for example, we added information from Google AdWords to optimize banners. So the warehouse must be very flexible. It must be able to grow in all three ways.

Gardner: How long have you been using HP Vertica and how did you come to choose that particular platform?

Golov: Well over a year now. We chose Vertica for two two main advantages. First, speed of load and data. The I/O speed provided by Vertica is awesome.

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Second is its ability to upgrade, thanks to the commodity hardware. So if you have some new requirements that require you to increase performance, you can just buy new hardware -- commodity hardware -- and its power just increases.

It’s great and it can be done really fast. Vertica was the winner.

Measuring the impact

Gardner: Do you have a sense of what the performance and characteristics of Vertica and your data warehouse have gotten for you? Do you have a sense of reduced fraud by X percent or better analytics that have given you a business advantage of some sort? Are there ways to measure the true impact?

Golov: During last year, Avito grew really fast. We have a moderation team of about 250 persons at the beginning of this process. Now, we have the same moderation team, but the number of items has increased two-fold. I suppose that's one of the best measures that can be used.

Gardner: Fair enough. Now, looking to the future, when you're working in a business where your margins, your business, your revenue comes from the ability to provide advertisement placements, improving the performance and the value on the actual distribution of ads and the costs associated is critical.

In addition to rapid fraud detection and protection, is there a value from your analytics that refines the business algorithms and therefore the retail value to your customers?

We're starting few more products. The main aim of them is to create our own tool for optimizing the directions of advertising.

Golov: We're creating more products. The main aim of them is to create our own tool for optimizing the directions of advertising. We have banners, marketing campaigns, and SMS. So we've achieved some results in our reporting and in fraud prevention. We'll continue to work in that direction, and we are planning to add some new types of functionality to our data warehouse.

Gardner: It certainly seems that a data warehouse delivers a tactical benefit but then over time moves to a strategic benefit. The more data, inference, and understanding you have of your processes, the more powerful you can become as a total business.

Golov: Yes. One of my teachers in data warehouses explained the role of data warehouses in an enterprise. It’s like a diesel engine inside a ship. It just works, works, and works, and it’s hot around it. You can create various tools to increase it, to make it better.

But there must always be something deep inside that continuously provides all of the associated tools with power and strong data services from all sides of the business.

Gardner: I wonder for others who are listening to you and saying, "We really need to have that core platform in order to build out these other values over time." Do you have any lessons that you have learned that you might share. That is to say, if you're starting out to develop your own data warehouse and your own business intelligence (BI) and analytics capabilities, do you have any advice?

Be flexible

Golov: First, you have to be flexible. If you ask a business about changing, they'll tell you that they can’t. It will be absolutely this, every time. And in two months, it will still change. If you're not ready to change using your data warehouse to get needed data and analytics, it would be a disaster. That's first.

Second, there always will be errors in data, there will be gaps, and it's absolutely critical to start building a data warehouse together with an automated data quality system that will automatically control and monitor the quality of all the data. This will help you to see the problems when they occur.

If you're not ready to change the ratio of your data warehouse to get such data, it would be a disaster.

Gardner: I'm afraid we'll have to leave it there. We've been discussing how Avito, a large e-commerce portal and super retail site in Moscow, has been deploying a data warehouse and BI capability to not only prevent fraud, but also to grow its business through a better understanding of its customers and processes.

So, a big thank you to our guest, Nikolay Golov, Chief Data Warehousing Architect at Avito. Thank you so much.

Golov: Thanks a lot.

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Gardner: And I'd like to thank our audience as well for joining us today for our special big data innovation discussion.

I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this ongoing series of HP-sponsored discussions. Thanks for listening, and come back next time.

Listen to the podcast. Find it on iTunes. Get the mobile app for iOS or Android. Download the transcript. Sponsor: HP.

Transcript of a BriefingsDirect discussion on how a Russian ecommerce and search engine site leverages big data analytics. Copyright Interarbor Solutions, LLC, 2005-2015. All rights reserved.

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GoodData Analytics Developers Share their Big Data Platform Wish List

Transcript of a BriefingsDirect podcast on how and why cloud data analytics provider GoodData makes HP Vertica an integral part of its infrastructure.

Listen to the podcast. Find it on iTunes. Get the mobile app for iOS or Android. Download the transcript. Sponsor: HP.

Dana Gardner: Welcome to the next edition of the HP Discover Podcast Series. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator for this ongoing sponsored discussion on IT innovation and how it’s making an impact on people’s lives.

Once again, we're focusing on how companies are adapting to the new style of IT to improve IT performance and deliver better user experiences, as well as better business results.

Become a member of MyVertica
Register now
And gain access to the Free HP Vertica Community Edition.

Our next innovation case study interview highlights how GoodData has created a business intelligence (BI)-as-a-service capability across multiple industries to enable users to take advantage of both big-data performance as well as cloud delivery efficiencies.

To learn more we are here with a panel consisting of Tomas Jirotka, Product Manager of GoodData. Welcome, Tomas.

Gardner

Tomas Jirotka: Hello. It's great to be here.

Gardner: We are also here with Eamon O'Neill, the Director of Product Management at HP Vertica. Welcome, Eamon.

Eamon O'Neill: Thanks, Dana.

Gardner: And Karel Jakubec, Software Engineer at GoodData. Welcome.

Karel Jakubec: Thanks. It's great to be here.

Gardner: Let’s we start with you, Tomas. Tell us a bit about GoodData and why you've decided that the cloud model, data warehouses, and BI as a service are the right fit for this marketplace?

Jirotka: GoodData was founded eight years ago, and from the beginning, it's been developed as a cloud company. We provide software as a service (SaaS). We allow our customers to leverage their data and not worry about hardware/software installations and other stuff. We just provide them a great service. Their experience is seamless, and our customers can simply enjoy the product.

Jirotka

Gardner: So can you attach your data warehouse to any type of data or are you focused on a certain kind? How flexible and agile are your services?

Jirotka: We provide a platform -- and the platform is very flexible. So it's possible to have any type of data, and create insights to it there. You can analyze data coming from marketing, sales, or manufacturing divisions no matter in which industry you are.

Gardner: If I'm an enterprise and I want to do BI, why should I use your services rather than build my own data center? What's the advantage for which your customers make this choice?

Cheaper solution

Jirotka: First of all, our solution is cheaper. We have a multi-tenant environment. So the customers effectively share the resources we provide them. And, of course, we have experience and knowledge of the industry. This is very helpful when you're a beginner in BI.

Gardner: So, in order to make sure that your cloud-based services are as competitive and even much better in terms of speed, agility and cost, you need to have the right platform and the right architecture.

Jakubec

Karel, what have been some of the top requirements you’ve had as you've gone about creating your services in the cloud?

Jakubec: The priority was to be able to scale, as our customers are coming in with bigger and bigger datasets. That's the reason we need technologies like Vertica, which scales very well by just adding nodes to cluster. Without this ability, you realize you cannot implement solution for the biggest customers as you're already running the biggest machines on the market, yet they're still not able to finish computation in a reasonable time.

Gardner: I've seen that you have something on the order of 40,000 customers. Is that correct?

Jirotka: Something like that.

Gardner: Does the size and volume of the data for each of these vary incredibly, or are most of them using much larger datasets? How diverse and how varied is the amount of data that you're dealing with, customer by customer?

Jirotka: It really depends. A lot of customers, for example, uses Salesforce.com or other cloud services like that. We can say that these data are somehow standardized. We know the APIs of these services very well, and we can deliver the solution in just a couple of days or weeks.

Some of the customers are more complex. They use a lot of services from the Internet or internally,  and we need to analyze all of the sources and combine them. That's really hard work.

Gardner: In addition to scale and efficiency in terms of cost, you need to also be very adept at a variety of different connection capabilities, APIs, different data sets, native data, and that sort of thing.

Jirotka: Exactly. Agility, in this sense, is really curial.

Gardner: How long you have been using Vertica and how long have you been using BI through Vertica for a variety of these platform services?

Working with Vertica

Jirotka: We started working with Vertica at the beginning of the last year. So, one and a half years. We began moving some of our customers with the largest data marts to Vertica in 2013.

Gardner: What were some of the driving requirements for changing from where you were before?

Jirotka: The most important factor was performance. It's no secret that we also have Postgres in our platform. Postgres simply doesn’t support big data. So we chose Vertica to have a solution that is scalable up to terabytes of data.

Gardner: We're learning quite a bit more about Vertica and the roadmap. I'd like to check in with Eamon and hear more about what some of the newer features are. What’s creating excitement?

O'Neill

O’Neill: Far and away, the most exciting is about real-time personalized analytics. This is going to allow GoodData to show a new kind of BI in the cloud. A new feature we released last year in our latest 7.1 release is called Live Aggregate Projections. It's for telling you about what’s going on in your electric smart meter, that FitBit that you're wearing on your wrist, or even your cell-phone plan or personal finances.

A few years ago, Vertica was blazing fast, telling you what a million people are doing right now and looking for patterns in the data, but it wasn’t as fast in telling you about my data. So we've changed that.

With this new feature, Live Aggregate Projections, you can actually get blazing fast analytics on discrete data. That discrete data is data about one individual or one device. It could be that a cell phone company wants to do analytics on one particular cell phone tower or one meter.

That’s very new and is going to open up a whole new kind of dashboarding for GoodData in the cloud. People are going to now get the sub-second response to see changes in their power consumption, what was the longest phone call they made this week, the shortest phone call they made today, or how often do they go over their data roaming charges. They'll get real-time alerts about these kinds of things.

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When that was introduced last year, it was standing room only. They were showing some great stats from power meters and then from houses in Europe. They were fed into Vertica and they showed queries that last year we were taking Vertica one-and-half seconds. We're now taking 0.2 seconds. They were looking at 25 million meters in the space for a few minutes. This is going to open up a whole new kind of dashboard for GoodData and new kinds of customers.

Gardner: Tomas, does this sound like something your customers are interested in, maybe retail? The Internet of Things is also becoming prominent, machine to machine, data interactions. How do you view what we've just heard Eamon describe, how interesting is it?

More important

Jirotka: It sounds really good. Real-time, or near real-time, analytics is becoming a more-and-more important topic. We hear it also from our customers. So we should definitely think about this feature or how to integrate it into the platform.

Gardner: Any thoughts, Karel?

Jakubec: Once we introduce Vertica 7.1 to our platform, it will be definitely one of features we will focus on. We have developed a quite complex caching mechanism for intermediate results and it works like a charm for Postgres SQL, but unfortunately it doesn't perform so well for Vertica. We believe that features like Live Aggregate Projection will improve this performance.

Gardner: So it's interesting. As HP Vertica comes out with new features, that’s something that you can productize, take out to the market, and then find new needs that you could then take back to Vertica. Is there a feedback loop? Do you feel like this is a partnership where you're displaying your knowledge from the market that helps them technically create new requirements?

Jakubec: Definitely, it's a partnership and I would say a complex circle. A new feature is released, we provide feedback, and you have a direction to do another feature or improve the current one. It works very similarly with some of our customers.

Engineer-to-engineer exchanges happen pretty often in the conference rooms.

O’Neill: It happens at a deeper level too. Karel’s coworkers flew over from Brno last year, to our office in Cambridge, Massachusetts and hung out for a couple of days, exchanging design ideas. So we learned from them as well.

They had done some things around multi-tenancy where they were ahead of us and they were able to tell us how Vertica performed when they put extra schemers on a catalog. We learned from that and we could give them advice about it. Engineer-to-engineer exchanges happen pretty often in the conference rooms.

Gardner: Eamon, were there any other specific features that are popping out in terms of interest?

O’Neil: Definitely our SQL on Hadoop enhancements. For a couple of years now we've been enabling people to do BI on top of Hadoop. We had various connectors, but we have made it even faster and cheaper now. In this most recent 7.1 release, you can now install Vertica on your Hadoop cluster. So you no longer have to maintain dedicated hardware for Vertica and you don’t have to make copies of the data.

The message is that you can now analyze your data, where it is and as it is, without converting from the Hadoop format or a duplication. That’s going to save companies a lot of money. Now, what we've done is brought the most sophisticated SQL on Hadoop to people without duplication of data.

Gardner: Tomas, how does Hadoop factor into your future plans?

Using Hadoop

Jirotka: We employ Hadoop in our platform, too. There are some ETL scripts, but we've used it in a traditional form of MapReduce jobs for a long time. This is really costly and inefficient approach because it takes much time to develop and debug it. So we may think about using Vertica directly with Hadoop. This would dramatically decrease the time to deliver it to the customer and also the running time of the scripts.

Gardner: Eamon, any other issues that come to mind in terms of prominence among developers?

O’Neill: Last year, we had our Customer Advisory Board, where I got to ask them about those things. Security came to the forefront again and again. Our new release has new features around data-access control.

We now make it easy for them to say that, for example, Karel can access all the columns in a table, but I can only access a subset of them. Previously, the developers could do this with Vertica, but they had to maintain SQL views and they didn’t like that. Now it's done centrally.

They don’t want have to maintain security in 15 places. They'd like Vertica to help them pull that together.

They like the data-access control improvements, and they're saying to just keep it up. They want more encryption at rest, and they want more integration. They particularly stress that they want integration with the security policies in their other applications outside the database. They don’t want have to maintain security in 15 places. They'd like Vertica to help them pull that together.

Gardner: Any thoughts about security, governance and granularity of access control?

Jirotka: As we're a SaaS company, security is number one for us. So far, we have some solutions that work for us, but these solutions are quite complex. Maybe we can discover new features from Vertica and use that feature.

Jakubec: Any simplification of security and access controls is a great new. Restriction of access for some users to just subset of values or some columns is very common use case for many customers. We already have a mechanism to do it, but as Eamon said it involves maintenance of views or complex filtering. If it is supported by Vertica directly, it’s great. I didn’t know that before and I hope we can use it.

Gardner: Very good. I'm afraid we’ll have to leave it there. We've been hearing how GoodData, based in San Francisco, a BI service provider, acts as a litmus test for how a platform should behave in the market, both in terms of performance as well as economics. They've been telling us their story as well as their interest in the latest version of HP Vertica.

So a big thank you to our guests, Tomas Jirotka, Product Manager at GoodData; Eamon O’Neill, Director of Product Management at HP Vertica, and Karel Jakubec, the Software Engineer at GoodData.

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And also a big thank you to our audience for joining this special new style of IT discussion. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this ongoing series of HP-sponsored discussions. Thanks for joining, and don’t forget to come back next time.

Listen to the podcast. Find it on iTunes. Get the mobile app for iOS or Android. Download the transcript. Sponsor: HP.

Transcript of a BriefingsDirect podcast on how and why cloud data analytics provider GoodData makes HP Vertica an integral part of its infrastructure. Copyright Interarbor Solutions, LLC, 2005-2015. All rights reserved.

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