7 data governance mistakes to avoid

These days, every data transaction is a business transaction. That’s why it’s vital to build a data governance framework that’s strong, secure, adaptable, and as error-free as possible.

7 data governance mistakes to avoid
Thinkstock

Most CIOs know that mishandled data can lead to financial, reputational, legal, and all sorts of other troubles. That’s why having a strong data governance policy, one that ensures security and compliance yet is also accessible and manageable, is a top priority for any organization that’s committed to data integrity and preservation.

Unfortunately, because data governance requirements and practices are still evolving, it’s easy for IT leaders to fall into pitfalls that, over time, can undermine even the best intended planning efforts. To keep your organization from falling into a trap that can render its data governance policy ineffective or even dangerous, keep an eye out for the following seven common mistakes that must be avoided at all costs.

1. Treating data governance as a technology project

Given data governance’s inherently fluid nature, policy development shouldn’t be viewed as a project that can be simply planned and released. A data governance policy that fails to keep pace with evolving requirements will ultimately fail. Worse yet, such a policy can be viewed as an annoying impediment to getting work done, leading teams to create their own workarounds.

Treat data governance as a business challenge, suggests Rajiv Mirani, CTO at cloud software and service provider Nutanix. Data is an asset that needs to be understood and protected by the organization, he says, “similar to the way many companies implement cash-handling processes, which are fully understood and accepted by the organization because they understand the importance of handling cash safely.”

To continue reading this article register now

Download CIO's Roadmap Report: 5G in the Enterprise