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An easy upgrade from Netezza to the IAS brings major benefits for Capitalogix

Product Marketing Manager for Data Lake & Hortonworks Partnership, IBM

Capitalogix is a hedge fund, but it’s really a data science firm in disguise. They work to understand and exploit capital markets by building custom data science models that can analyze massive amounts of data from as many sources as possible. Capitalogix’s need for high-performance analytics and data science on a single platform led them to transition from Microsoft SQL Server to Netezza and finally to the new IBM Integrated Analytics System (IAS). The IAS combines data science, analytic workloads and hybrid cloud capabilities into a single, game-changing platform for Capitalogix.

iOLAP is a professional services firm focused on big data and analytics. They helped Capitalogix transform their infrastructure and migrate to the IAS platform. We sat down with Chris Jordan, CEO of iOLAP, to discuss the migration, what it means for Capitalogix and how IBM was able to support them in this upgrade.

What was iOLAP’s role in the migration from Netezza to the IAS?

Chris Jordan: IBM offered to do the migration for Capitalogix with our assistance. So our combined global team worked together. It went off pretty quickly and easily. It took about eight to ten weeks to do it all. A lot of the effort in the migration was taking their user-defined functions and rewriting them to work in Spark on the data science part of IAS. 

It's a big decision to change platforms. There has to be a pretty good payoff to switch over. What was the big impetus for making those moves—first to Netezza and then to the IAS?

Chris Jordan: The primary reason for the migration from Microsoft SQL Server to Netezza was performance. The system that they had built in SQL Server was very difficult to maintain. They launched many instances of SQL Server to simulate parallel processing, which they had to do [for] the back testing that they needed […] In Netezza we were able to combine all of that into a single database and increase performance by a magnitude. It made the single source a single system for all of the data regardless of the market that they were trading and analyzing, we were able to combine it onto a single database and get the performance that they needed.

Q: And then why move to the IAS?

Chris Jordan: It was important that the migration wouldn't be terribly difficult, and that definitely makes the decision easier. But the real drivers for going to IAS were the combination of the data science with the analytic workload, as well as the hybrid cloud capability that allows them to deploy on premise and in the cloud on the same code base. To be able to do that was kind of game-changing for Capitalogix.

Q: What other companies were you looking at and ultimately why did you stick with IBM?

Chris Jordan: When Capitalogix decided to consider the migration from Netezza to IAS, they thought it was prudent to evaluate other vendors. They looked at Yellow Brick and they looked at Amazon Web Services. Ultimately, the migration effort from Netezza to IAS proved to be much less than they expected from either of those providers and the functionality that they would get from IAS was superior. That capability from Netezza to IAS is nearly 100 percent and it makes the migration effort relatively simple and straightforward.

I believe anyone that's currently deployed on a Netezza system should be looking to migrate to IAS. The benefits that you get by combining the data science platform with the analytics platform and the hybrid data management component far outweigh the work.

Discover how smooth the transition from Netezza to IAS can be with this migration guide.

When I spoke with Howard [Getson, CEO of Capitalogix] he mentioned the importance of having an analytics appliance with cloud connectivity. Why is that so key?

Chris Jordan: With the cloud readiness of IAS, we don't have to make a decision up front about whether we want to deploy on-premises or in the cloud. We can deploy in one and migrate to the other, either direction—it doesn't matter. So I don't have to start my conversation with asking how I want to deploy the system, I just start building the system on whatever I currently have. And if there's a reason to be in the cloud or a reason to be on-premises, I can still go to that area. With the software code base being identical, whether it's deployed on-premises or the cloud, we can go from one to the other for whatever reason comes up in the future. If we suddenly decide the cloud's not right for us, we can go back to on-premises. If we suddenly decide we don't want to be on-premises, we need to be in the cloud, we can do that too, without a migration. Today, IBM is the only solution that offers that flexibility.

What's impact of having the data science tools being embedded within IAS?

Chris Jordan: Having the data science environment right there and embedded on IAS enables the data scientists at Capitalogix to experiment. They don't have to move data around from environment to environment to go built a new model, to test a new model or to back-test. They spend weeks testing models. To be able to quickly and easily create a new model, test it and see if it has validity is of great value to them. Upgrading to the IAS enables the data scientists to really experiment with what they're thinking about in the data and what they're seeing in the data rather than having to learn the complexities of a data science system. So they're able to derive more value much more quickly.

Learn more about IAS’s data science capabilities in this paper.

How valuable is it to Capitalogix to have so many different deployment options, whether that's on-premises or an appliance, public cloud, private cloud and so on? 

Chris Jordan: The hybrid data management approach is very important to Capitalogix. They want to be close to the processing, they want on-premises servers where they're able to work closely on those systems without having to move data up into the cloud or back again. But the ability to use the same code base in the cloud enables them to do disaster recovery, to do development on environments that aren't on-premises for them, as well as to launch quickly and easily new development environments to do testing.

Capitalogix’s experience is similar to many others who have made the upgrade to the hybrid, flexible, and data science focused IBM Integrated Analytics System. Read more about how Capitalogix gains competitive advantages as well as some thoughts on transformation from CEO Howard Getson. 

To learn more, read IDC’s recent report on data warehouse appliances and IAS: Delivering Hybrid Analytics at the Speed of Business.” Or discuss your data warehouse needs with an IBM expert by setting up a no-cost, one-on-one consultation.