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Data governance for next-generation platforms

Companies must adapt their data governance program to the reality of data explosion and disruptive technologies

Today’s explosion of data—and the insights revealed—is not only highly valuable to organizations from a strategic standpoint, but also it presents challenges in storage, management, and adherence to regulatory and legal requirements. Developing an effective data governance program for the next-generation platforms staged to manage this landscape is essential to harness the data’s potential and to help minimize risks.

Data is significantly changing the game in today’s world

Pulling as much of that data into a single place and organizing it so advanced digital technologies can serve up insights can put innovative companies at the significant advantage of being able to see what others can’t. For decades, many organizations spent their time, money, and resources on defenses and procedures designed to not only keep external cyber adversaries out of their networks but also manage access internally.

Many organizations are realizing they don’t know—much less have control over—what data exists within the enterprise, where it sits, and how it is being used across business units, geographies, or with third parties. New disruptive technologies such as cloud, big data, and IoT bring even greater data complexity. Data governance and its driving change should be top of mind for every C-level executive.

Data governance capability enhancements

What makes a stellar data governance program in the new world of data?

Data governance of tomorrow is not only about maximizing the value of data for operational effectiveness, decision making, and regulatory requirements, but also about minimizing the risks associated with poor data management. Well-established data governance capabilities for traditional platforms is a solid starting point for bringing next-generation platforms under the enterprise data governance umbrella.

However, the increased scale and complexity of the enterprise data architecture requires enhancements across the four key data governance pillars:

  • Processes, policies, standards, and procedures: Standards—including metadata management, data quality, data security, data architecture, and data modeling—define the rules required to ensure the data fits the purpose. Processes and procedures provide the details about how the standards will be executed.
  • Organization, roles, and responsibilities: Companies must carefully define formal internal bodies, roles, and responsibilities to facilitate, oversee, and perform business procedures as well as prevent misuse.
  • Technology and tool capabilities: New tools can help manage data governance proactively, scaling capabilities to manage massive amounts of data. The technology can both manage metadata, data quality, workflow and security and integrate with next-generation platforms.
  • Metadata content (or data catalog): It’s about cataloging the business, technical, and operational characteristics of data and it’s instrumental in managing, overseeing, and measuring tomorrow’s data governance processes.

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Want the most out of your data?

A solid data governance program helps companies to understand, manage, and leverage the information potential of the data stored and processed by next-generation platforms. Successful implementation of data governance across the entire data landscape—with traditional and next-generation platforms—will likely determine which organizations will emerge as market leaders. They will be the ones making data-driven decisions.

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