Adding Data Governance Insights with Data Quality

Why Data Governance is top of mind

What we are seeing from previous years is the volume and the complexity of data is growing massively. Data is nearly doubling every two years along with the intricacy of it. Where we used to have internal sources, we are now working with data links or cloud data warehouses. Each source needs to be governed
because we are responsible for the data that is used to make decisions and drive business.

As data grows, we also see broader and deeper compliance regulations emerging, such as GDPR and CCPA. Looking at trends from Google, we can see that the term “data governance” has been searched more frequently over the last few years. So, how can we govern the data and also indicate that the data
is trustworthy?

Data Governance Needs Data Quality

For compliance reasons, we need to meet regulatory requirements to make business decisions. We need to make sure that we can trust the data and that our data policy will create a unique customer view.

Recent studies have shown that 35 percent of senior executives have a high level of trust in data living in big data environments. While 92 percent are concerned about the negative impact of those risks.

For example, GDPR has been in effect for two years and already there are 428 million dollars in fines as of December 2019. With CCPA coming into effect in the US, only 2 percent of the firms consider themselves fully CCPA compliant today. This poses a variety of risks that need to be resolved.

With data governance, you have trust that your data is in the right hands and the ability to provide insights across the organization.

Data governance

  • The set of policies, processes, rules, roles, and responsibilities that help organizations manage data as a corporate asset.
    Ensures the availability, usability, integrity, accuracy, compliance, and security of data by:
  • Putting trusted data assets in the right hands
  • Providing insight across the organization
  • Streamlining data management with repeatable practices

Data quality

The processes and rules that help ensure that data is “fit for use” in its intended operational and decision-making contexts.

  • Provides accuracy, completeness, consistency, relevance, timeliness, and validity of data by:
  • Assessing the current state of data quality
  • Putting rules in place to validate data in a constant form
  • Delivering insights on data to those who need it

Download this eBook to learn how Precisely Trillium’s data quality solutions provide robust, scalable data profiling for a complete view of your data quality, and out-of-the box integration with Collibra to support a broad range of governance needs.

eBook: Adding Data Governance Insights with Data Quality
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