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Shattering the Data Governance Myth

An independent study reveals that big data needs agile information integration and governance

Program Director, Analytics Platform Marketing, IBM

A recent IBM-commissioned study conducted by Forrester Consulting* shatters the myth that data governance is an innovation killer and a drag on business progress—especially in the realm of big data. In fact, the study finds, “a lack of competency and success with IIG can actually hinder the ability to develop, roll out, and get value from big data investments.”

Information integration and governance (IIG) is “playing a significant role to move big data from the realm of possibility to the reality of business outcomes,” according to the study, which was conducted in July 2013. Forrester surveyed 512 business sponsors, IT practitioners, and business intelligence (BI) professionals from across the globe to learn about their IIG practices and plans. The study found that organizations were not bypassing integration and governance practices to accelerate their business results, but instead were “embracing” IIG and looking to it as a critical success factor for a range of big data–related initiatives.

What is information integration and governance?

IBM defines IIG as a unified set of capabilities that brings together data from varied sources for diverse targets, manages its quality, and maintains master data for multiple domains. The capability set also secures and protects data, manages it across its lifecycle, and facilitates information-based collaboration across business and technical teams. Organizations are taking advantage of these capabilities to increase the value of data for information-intensive projects such as big data and analytics, application consolidation and retirement, security and compliance, 360-degree views, and many other outcomes.

The Forrester study explores the current status of IIG at organizations around the world to identify organizational priorities and concerns related to big data and IIG and to learn how IIG is being implemented to support big data. The study found that respondents were focused first on securing their data, but other aspects of IIG including data integration, data quality, and master data management were also gaining significant traction.

Which data types need governance?

In addition, although respondents felt that different types of data required different levels of governance, they indicated that data of all types should be governed in some way (see figure). The data types requiring the highest levels of control were customer data, product data, and planning, budgeting, and forecasting data—while the least governance was deemed appropriate for social network data and unstructured external data.

Shattering the data governance myth
Source: “Big Data Needs Agile Information and Integration Governance,” a commissioned study conducted by Forrester Consulting on behalf of IBM, August 2013.

Respondent opinions on different levels of governance for all data types

 
The study also found that an understanding of context helps to unlock the value of big data. One important contextual aspect is data lineage—where and when data originated and how it has changed over time. And an equally important aspect of context is the usage plan—where and how the data is intended to be used within the organization. Usage plans have a major impact on the level of governance required and the level of confidence that is needed if the data is to have value to the organization. According to the Forrester study, “Context helps organizations master a wider set of internal and external data and to encompass data that is less structured but highly descriptive of customers, interactions, and other market information.”

As for the technology needed to automate governance, the study found that big data initiatives expose a tooling gap. To manage the security, data quality, and delivery requirements at big data scale, organizations find that they need technology that goes beyond the pockets of solutions they already have in place for specific data and particular use cases. As they determine where to begin to address the gaps, data profiling tools emerge as the top choice and reflect a keen interest in getting a good understanding of the available data.

How can the potential of big data be unlocked?

The Forrester study on behalf of IBM concludes that a few guiding principles for agility in IIG can go a long way toward helping organizations unlock the potential of their big data. In a nutshell, organizations can apply the following three principles:

  • Move ahead with IIG in stages aligned with big data initiatives and associated analytic capabilities and goals.
  • Govern and prioritize data governance based on the context of the data itself and its intended use.
  • Incorporate IIG into development and testing phases as well as projects in production.

IBM recently announced a number of innovations in IIG that help organizations unlock potential by building confidence in big data through capabilities that automate integration, visualize data context, and make governance increasingly agile. To learn more about those innovations, be sure to read related IBM Data magazine articles that provide details of these advanced capabilities.

Download the commissioned Forrester study to learn more comprehensive details behind the survey responses, analysis, and recommendations. If you have a question, please post it in the comments.

Big Data Needs Agile Information and Integration Governance,” a commissioned study conducted by Forrester Consulting on behalf of IBM, August 2013.

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