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IT Innovation | August 27, 2018

The New Data Capitalist

By: Paul Sonderegger

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Data is the real capital that’s driving the new digital economy. Just consider any successful social media platform or consumer web service: these companies may be short on facilities and capital equipment, but they’re rich in intellectual property, thanks to their ability to slice and dice their proprietary reserves of data capital for competitive advantage.

Established companies can see similar opportunities, but only if they learn to unlock the full value of their information reserves. Unfortunately, that’s far too rare. Insights into new business opportunities remain hidden because internal data consumers want new combinations of data and analyses not found in standard reports and dashboards. This is the unseen data that’s hiding inside every company.

How can enterprises bring data capital out of hiding? Chief data officers (CDOs) should use the cloud to create centrally managed data exchanges that make accessing authoritative datasources easier and then provide modern analytics that enable individual departments, workgroups, business analysts, and data scientists to harvest data for their unique requirements. These exchanges must also be hyperscalable to accommodate exploding volumes of data and demand for analyses. In the process, CDOs become data capitalists—visionaries who ensure that the data the company generates can be used to its highest value.

When successful, this move yields impressive results. One large retail and investment bank I spoke with generated about US$200 million for its credit card operations thanks to the cross-selling analyses it derived from a central, multipetabyte Hadoop cluster.

Tools for a Data Exchange

In addition to a forward-thinking CDO, enterprises need a mix of new technologies and existing tools used in new ways to unlock the full value of their data.

The cloud is key. It provides a dynamic resource for managing and analyzing large volumes of diverse information. It’s also designed to scale quickly, so large and small companies alike can serve sudden rises in new data consumers. For example, creating scalable object datastores or Hadoop clusters in the cloud relieves CDOs of having to estimate how data or subsets of analytical results will grow over time. Clouds essentially act as unlimited, elastic, globally available computers.

Analytics based on AI let enterprises compound the value of their data. For example, data scientists at an ecommerce site may create an algorithm for identifying new upselling opportunities. But after an initial spike in order sizes, the gains may plateau because of competitive responses and other factors. Scalable IT resources enable companies to handle the order surge, avoid a financial hit when transactions level off, and be ready for a rebound. For example, the algorithm developers may feed performance data into the data exchange and use associated AI applications to make more-accurate predictions about what types of offers will boost results in the future. This, in turn, creates a growing, continuously improving data asset based on proprietary information that competitors can’t match.

In addition to new tools, modern versions of traditional technology, such as relational database management systems, can help generate new data capital. For example, with Oracle Log Analytics Cloud Service, part of Oracle Management Cloud, CDOs can easily track who is adding and updating data to the exchange, as well as where most data queries are originating from. Better visibility into dataflows reveals what data is in highest demand so database administrators know which columns or tables should be made easier to access to encourage more-effective use of data.

Finally, to bolster data governance while setting data free, CDOs can catalog metadata from almost any source, including relational and Hadoop stores, with tools such as Oracle Data Integration Platform Cloud. This solution traces the lineage of data and what transformations have been applied to it, so managers know how and where sensitive data is being used, which is essential for complying with the General Data Protection Regulation (GDPR) and other data regulations.

There is still a surprisingly high number of large and small companies that haven’t learned how to unlock the full value of their data capital. That’s a problem for some, but it also means competitive opportunities for others when their CDOs transform themselves into data capitalists and have tools that can scale for success.

Photo of Paul Sonderegger courtesy of Brett Winter Lemon/The Verbatim Agency.

Paul Sonderegger is Big Data Strategist at Oracle. Previously, he was chief strategist at Endeca, a leading provider of unstructured data management, web commerce, and business intelligence solutions. Endeca was acquired by Oracle in late 2011. Before joining Endeca, Paul was a principal analyst at Forrester Research, specializing in search and user experience design. He holds a Bachelor of Arts degree from Wake Forest University.

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