Data Governance Framework, Goals, Principles, and Benefits

January 13, 2022 0 Comments

In this tough competitive and fast-paced environment data governance is a must for every business. Digitalization has offered the chance to capture an extensive amount of internal and external diversified data. These compiled data need some kind of regulations to manage the risks, reduce the cost, and maximize their value. This is where data governance helps.

What’s data governance?

It is a compilation of processes, policies, roles, metrics, and standards that ensures the efficient and effective use of gathered data. It enables businesses to attain their goals. The established policies, duties, and processes ensure data quality and security.

A well-designed data governance strategy from EWsolutions covers the tactical, strategic, and operational responsibilities and duties across the organization. The data governance consultant team designs a framework that supports your company’s data management strategy.

Data governance framework

  • Data architecture
  • Data storage & operations
  • Data modeling & design
  • Data integration & interoperability
  • Data security
  • Reference & Master data
  • Documents & content
  • Metadata
  • Data warehousing & BI {Business intelligence}
  • Data quality

Data governance goals

Goals help to establish methods and standard processes, set responsibilities, as well as integrate, store, and protect the business data. The major goals need to be to –

  • Lessen the risks
  • Implement compliance
  • Establish internal policies on how to use the data
  • Increase data value
  • Enhance external & internal communication
  • Reduce cost
  • Persist risk management & optimization

Data governance principles

  • Integrity – Every participant has to be honest and helpful in discussing the limitations, options, impacts, and drivers of data-related decisions.
  • Transparency – All the participants and auditors must be aware of how and when the data-related rules and regulations were introduced in the processes.
  • Auditable – All the data governance-related processes, decisions, and regulations need to be reviewable. They need to have supporting documentation that complies with the auditing needs.
  • Accountability – The accountability for cross-functional data governance policies and processes needs to be clearly defined. It must even define who is responsible for the stewardship activities.
  • Flexibility – The program has to support enterprise data standardization. Even support reactive and proactive change management activities for data value references and the use of metadata and master data.

Data governance benefits

  • Make better decisions with comprehensive support from consistent and unchanging data made available across the company.
  • Clear rules for the changing data and processes help IT and businesses become more accessible and responsive.
  • Offers central control mechanism and reduces data management’s overall costs.
  • The ability to reuse the data and processes helps to increase efficiency.
  • Data processes documentation and data quality enable us to make decisions with confidence.
  • Improved data regulation compliance.

Data governance is an element of the overall data management discipline. Data governance is all about the roles, policies, and processes to ensure accountability for and data asset ownership. On the other hand, data management discipline involves shaping, describing, and governing data assets across the technical and organizational boundaries to enable business insight, promote transparency and improve efficiency.