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3 Critical Data Capabilities for Your Data Governance Solution

Authors Photo Precisely Editor | August 25, 2022

Data is an essential business asset for any organization, regardless of size or industry. There are countless ways organizations can leverage their data assets to gain a competitive advantage and offer greater value. However, regardless of business size, any success hinges upon data consumers fully understanding what data means from a business context and having the ability to accurately gauge the quality of data capabilities – that’s where data governance comes into play.

Generally speaking, data governance is the formal orchestration of people, processes, and technology to enable an organization to leverage their data as an enterprise-wide business asset. Fundamentally, it’s about increasing the understanding of data to serve the requirements of everyone in an organization. A data governance program should cultivate a culture of open communication and collaboration among diverging lines of business and IT resources.

When embarking on your data governance journey, the solution you choose needs to have a set of data capabilities that enables you to achieve a comprehensive view of all data assets. Data governance, of course, is a piece of the puzzle – but data integrity and analytical capabilities are what tie it all together.

Why data governance matters

Data governance can break down the communication barrier between IT and business. It accomplishes this by engaging all parties across the enterprise to create an inventory of available data, designate data owners and stewards, track data lineage and usage, and clearly define data, business terms, synonyms and business attributes.

With a comprehensive picture of your organization’s data environment, users can quickly identify the risks associated with data usage across various business applications, gain valuable insights about customers, and achieve operational efficiency.

In addition, data governance can assess and score data quality levels across the entire data supply chain, increasing business user trust of data to enhance business decisions and improve outcomes. Machine learning algorithms can then be layered into data governance to automatically detect potential data defects and continuously monitor for data integrity improvement.

Read the eBook

Six Components of Successful Data Governance

Read our eBook to learn how most organizations understand that their business assets should include investments in technology, people, and infrastructure.

Successful data governance requires more than just spreadsheets and disparate tools. It requires a comprehensive solution suite to maximize the potential of an organization’s data assets.

The data capabilities checklist for your software suite

To ensure successful data governance, organizations need a comprehensive solution suite with three critical capabilities:

  1. Data governance capabilities, as we’ve covered, help clearly define varying roles and responsibilities among data owners, stewards and business users to provide all stakeholders and consumers with a full view of their data landscape. Business users can then easily define data policies and associated business terms, track data lineage and manage all aspects of their data assets.
  2. Data integrity capabilities to conduct data quality checks such as data profiling, consistency, conformity, completeness, timeliness, reconciliations, visual data prep and machine learning to verify the integrity of data and ensure continued trust among business users.
  3. Analytical capabilities and machine learning algorithms for self-learning, to continuously enhance data quality.

By integrating varied tools containing the right data capabilities, the solution suite can foster a complete understanding of an organization’s data history – enabling data owners, stewards and consumers to effectively manage, share, and utilize data to create a positive business impact.

To sum up, untrustworthy data makes users hesitant to leverage those assets for analysis, preventing the extraction of analytical insights that support critical business decisions. Even worse, making decisions based on untrustworthy data can lead to missed opportunities, operational miscues, unsatisfied customers, decreased revenue, and reputational damage.

Realizing maximum returns on data requires a complete understanding of it from a business context. To achieve that, you need data governance to improve your data’s integrity, usability, and reliability, and to ensure data remains beneficial to the organization.

For more on data governance and data capabilities, read our eBook Six Components of Successful Data Governance to learn how most organizations understand that their business assets should include investments in technology, people, and infrastructure.