Trusting big data

Perspective on data governance as a customer analytics investment

Many companies are investing significant amounts in customer analytics to drive their business and seek new ways to offer value to their customers. However, much of the potential value of that investment is at risk because data governance practices have not kept pace with the ways in which data is being used.

Defining the governance objective

As companies expand, they need higher levels of trust in their datasets and require confidence in their data governance framework. Those that are able to convey assurance to this extended enterprise can gain a competitive advantage with a trusted customer analytics program. Recognizing that your customer data needs to follow a structured data life cycle is the first realization for many companies in establishing a suitable control environment.

In this report, we explore the leading practices at each phase in that life cycle including:

  • Data sourcing
  • Analysis
  • Dissemination
  • Culmination
Trusting big data

Potential value

With the investment in customer big data programs growing, the potential value add for companies that get this right is significant. Companies that underinvest or delay their investment in their control environments over customer big data, threaten that investment. The companies that will ultimately succeed with customer big data are those who have a strategic and proactive framework that can get consistent and more reliable insights while carefully protecting that data.

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