Do enterprises need a chief data scientist?

Do enterprises need a chief data scientist?

Summary: Enterprises are increasingly focused on using big data and analytics to help them better understand both the requirements of their customers, trends and patterns of customer activity and this requires a different approach. Dell says that this trend means that enterprises need a new type of leader, a chief data scientist, to help ask the right questions, in the right way and drive the transition to the data-driven enterprise.

TOPICS: Big Data

Dell's Darin Bartik, executive director of product management for Dell Software’s Information Management solutions, and Bob Fine, director of Dell Compellent product marketing, spent some time with me talking about the trends the company has seen and what it is doing about them.

The impact of Big Data

Dell's customers increasingly are turning to the use of big data toola and analytics to learn more about the requirements of their customers, the patterns of customer activity, and use what they learn to drive better utilization of their resources. The goal, of course, is helping the customer see the company as a trusted partner that provides just the right mix of products and services.

Are today's BI and transactional systems obsolete?

Dell would point out that today's transactional and business intelligence systems are based upon the strong belief that the enterprise knows the right questions to ask and what to do with that data once it is obtained. So, today's workloads are designed to gather the data needed to answer those alreay-known questions and produce volumes of detailed reports to help people answer those questions. Today's rapidly changing world, Dell would point out, means that many of the old questions no longer are useful. They would also point out that the original assumptions, that is the questions being asked, are no longer the right questions to ask.

The emergence of the data scientist

Dell would assert that success today means asking different questions in different ways. Dell also suggests that this means that enterprises really ought to institute a new leadership position, the chief data scientist, to help guide the use of big data tools, software defined everything (data centers, storage, networking and workloads), and virtualized, converged systems.

It is now a requirement, Dell woud point out, to be able to look across all of the enterprise's operational data, regardless of which business unit's workloads collected that data or what format the data is in, to see new patterns of customer requirements and behavior. This means the intelligent use of virtual systems, networks, storage and analytical software. This, Dell would suggest, means that the enterprise needs someone to take on the role of facilitating the conversation between the business and systems analysts and between traditional business units and IT. Dell calls this role a data scientist.

Dell suggests that it has the tools and expertise to make this position and approach feasible.

Dell, however, faces competition from many suppliers who are saying similar things and appear to offer tools that can be pressed into service to achieve the same qoals. The long list of competitors range from HP, IBM, Microsoft, Oracle, Cisco and many others. Dell needs to demonstrate that it has the tools and expertise to help customers use big data and the software defined world to their advantage.


Topic: Big Data


Daniel Kusnetzky, a reformed software engineer and product manager, founded Kusnetzky Group LLC in 2006. He's literally written the book on virtualization and often comments on cloud computing, mobility and systems software. In his spare time, he's also the managing partner of Lux Sonus LLC, an investment firm.

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  • Asking the right questions

    If this all sounds like gobbledegook to you, take the time to watch the 2011 Brad Pitt movie Moneyball. It's basically about what happens when a small-market baseball team (the Oakland A's) decides to actually listen to its data guy. The things he thinks are important, and the questions he seeks the answers to, are nothing like those from the professional scouts and others who have been around baseball for years.

    I don't think there's an MLB team today that doesn't have a "data scientist."
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