HP has been listening to the demands of businesses worldwide, and has developed innovative new products designed to assist with the collection, analysis and distribution of Big Data.
In an exclusive interview with IT in Canada, Martin Risau, SVP, analytics and data management, HP Enterprise Services and Dragan Rakovich, CTO, analytics and data management / Distinguished Technologist, HP Enterprise Services discuss the company’s Big Data plans, and how they change the face of the data-driven workplace.
IT in Canada: Why are more businesses adopting the data-driven model for their structure?
Risau: There is huge pressure to deliver better products and services that companies realize that they need to make this (decision) based on data and be agile about it. Secondly, there is also learning of what we have out of data-driven companies. If you think of the LinkedIns and eBays of the world, they have shown how, based on pure data, you can continuously bring better solutions to your customers. They were the first ones to adopt the newer tools we’re now bringing to the enterprise, and that is basically spanning this competitive pressure into the enterprise in order to deliver better products and services to their customers.
ITIC: Is cloud-based technology a factor for the data-driven model?
Rakovich: Absolutely. One of the reasons why we offer our customers multiple entry points into our services is to deliver software as a platform in our consumption-based platform services offering. We also offer Vertica, our high-performance analytics database and the Autonomy add-on service as part of our overall HAVEn offering. Part of our goal to market this platform as a service, which is directly related to our Helion cloud offering. We essentially run Helion and provide Big Data as a service.
MR: What our customers want is speed, choice and protection against technology obsoleteness. So it’s only natural that we offer cloud solutions. As an example for speed, we’re working with a huge automotive company on their data lab. They want to know much is in their data, and if they were to combine new data sources with external data sources, what could they do differently to optimize logistics, warranty or other topics. Cloud gives you ability to say to a customer, “Within two weeks, I can deliver you a cloud environment that can solve this problem.” We were unable to do this prior to (the introduction of) the cloud.
In terms of protection against technology obsoleteness, the industry is innovating with such high speed right now, which is great. But on the other side, this gives you a problem over what you should invest in. You might invest in something today, but maybe in a year from now, there will be better software and tools out there. With our cloud solutions, we’re basically taking away a big piece of that risk for the customer because we bring them the technology and the tools for this software, (along with) our service specialists to the table in order to do that quickly.
ITIC: How would this new strategy be cost-effective for businesses?
MR: When we (launched) HP’s Business Intelligence Modernization Services, which include data discovery, cloud capabilities, analytics and data management, we did it with our customers in mind, (and) we (included) the best of what we have. Data discovery is one of those services. With data discovery, you run the data lake and you have people who will test or make more data available. It’s cost-effective because you don’t need to hire a Hadoop specialist in order to set up a data lake; we will include this as a service for you. As Dragan said, in a private cloud, we can do this very (quickly). Two weeks translates immediately in cost savings because you don’t need to think about what kind of Hadoop distribution or version you should use. We keep it current and we (determine) with the customer how relevant that data is, and how fast we can do it.
The combination of cloud and SaaS and the pressure on speed translates to cost effectiveness for the customer. Lastly, we have 1,200 data scientists and analysts available in our organization, and not every company is ready to invest in that skill set until they know what kind of business value they can drive with it. We’re bringing those kinds of specialists to the table in the managed services so that customers can decide how much value they can unlock in their organization. They then have the choice of whether they want to hire (third parties) or have the data managed by us.
ITIC: Is the implementation of the data-driven model generally a seamless process for IT managers?
DR: In this industry, we’ve done work within the business intelligence and data warehousing spaces in the past 20 years. We always profess how we manage Embedded BI and deliver on the promise of providing value to businesses. I don’t think it actually happened until the prominence of analyzing social media and telematic data that a truly new business model and leveraging of Big Data emerged.
Martin mentioned that data-driven companies such as eBay, Amazon and LinkedIn have fully leveraged that model. In our mind, the data-driven (model) requires technology adoption and change, but it also requires cultural change within the company in order to fully leverage it for the business benefits. Our hybrid data management approach and architecture are geared to deliver both improvements and optimization for the current BI and data warehousing environments. As well, they will help IT managers deploy new Big Data analytic technologies to take advantage of the new forms of data and enable their enterprises to improve their products and services, as well as develop new (ones) based on the information and analytics they obtain from these new sources of data.
ITIC: Big Data has been on the minds of many businesses lately. Why is that?
MR: Companies realize that they can unlock business value with new sources of data. On the other side, data is exploding and available, and the volume and velocity of the data is expanding. When we think what is available for companies, we sometimes call it “dark data” because companies are not using it. For example, in the telecom industry, they thought they had a problem with their cell phone coverage, and they had data available that they didn’t use before, namely dropped call data that they had not analyzed in a systematic way.
We worked together with this telecom company, and jointly, we were able to identify that a big portion of the dropped calls came from three different operating versions of cell phones; the company didn’t have a coverage problem in terms of cell towers. The carrier was able to work with the cell phone provider to fix this issue with the operating systems. If they hadn’t done this, they would have invested a significant amount (of money) to build new cell towers rather than getting to the core of the problem. This is an instance you often find in organizations where existing data is not utilized, but we now have new data sources available in order to enrich this data, most notably social data.
ITIC: What does the future hold for Big Data adoption?
MR: If you think about the Internet of Things, there will be a big differentiation of companies that will lead, and (others) will lack in this field. It will be absolutely key to be at the forefront of what the future holds. We’re looking at tapping seamlessly into huge amounts of data, so if we’re thinking about the IoT, we will examine how (businesses) will be able to use all of the data that will be available, and how (they) can turn this into better products and services for (their) customers. That is what counts, and the technology (provides) exciting opportunities to combine and bring new (types) of data into the fold. This has enabled us to catch the next wave of rapid and fundamental business innovation, and over the next five to ten years, we will evolve in order to make those innovations possible.
DR: I believe the source of competitive advantage for companies has moved from analyzing the internal performance data, which we did with BI and data warehousing. It still has to be done because almost every company has some level of good performance management. It’s not at the same level as it was in the early-to-mid 90s. The source of competitive advantage is moving to those companies that can analyze Big Data and take full advantage of those analytics to impact either their operational processes, or be more relevant to their customers. That’s why there is so much interest in Big Data today.
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