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Data Governance: Mastering the organization's usages

By Sushmita Rai, 3rd Eye Advisory Ltd
Data governance: Mastering the organization's usages

Data Governance: Mastering the organization's usages

Data governance is not just about technology, rather it's all about people taking responsibility for the information assets of their organization by looking at the processes they use to interact with information. It can be described as a process which roots out business and compliance risk by increasing oversight. It helps organization in many ways to combine and integrate information in the form of data from vertical and horizontal lines of the business into a single source of truth. It helps to tie effective information policy to business strategy and makes business better. Although the need for data governance has never been greater, initiatives in many organizations or business institutions that have bogged down in bureaucracy, and other organizations have not even started because they have been daunted by what can seem like an overwhelming task. The more the people, applications and data involved, bigger the challenge and the need. If any business institution or organizations are searching for the process that could suit their immediate and long term needs and budget, then they must adopt an incremental approach.

The requisite for Data Governance enables organizations to access the full value of data while protecting that data from risk. Data is undoubtedly growing across all areas of the enterprise on the average, at the rate of 1.5 to 2.5 times a year. Laws regulating the use of data and associated compliance issues are also growing. For instance, in the U.S, the 2002 Sarbanes-Oxley Act can result in fines and even prison sentences for noncompliance to external reporting requirements. Data quality, master data management (MDM), and data migration initiatives are booming as a result of huge growth in data, demand and regulation. With the proliferations of data initiatives, the specific need for data governance increases to ensure the requirements of the enterprise. For example, data across the enterprise needs to be properly defined as "customer" or "product", in a way that suit individual organizations and before more applications and initiatives created. The data governance technique not only improves the operational efficiency but also improves application effectiveness and minimizes risk. Effective and efficient data governance creates a framework for the use of big data that fits each individual enterprise.

Many organizations and business institutions implementing an incremental approach to prove business value and build a sustainable program for data governance, avoiding the pitfalls of both over and under reaching. The following steps using a repeatable technological framework ensure effective data governance:

  1. Prioritize areas for business improvement
  2. Availability of information assets
  3. Create roles, responsibilities and rules
  4. Ensure and improve information asset integrity
  5. Establish an accountability infrastructure
  6. Conversion to a master data-based culture
  7. Develop a feedback mechanism for process improvement

Data governance technique not only delivers the right information to the right people at the right time, but it also helps in delivering the information in the right way to the users and in a way that works with the data framework for the whole organization. The following are the most common barriers to success for data governance initiatives:

  • Organizational -
    Different groups within an organization must communicate and coordinate well with one another
  • Data quality, MDM, and data migration integration -
    Applications and data must speak to one another, and this must be addressed up front and planned for in any integration initiative
  • Accountability and ownership of data -
    People must be held accountable for information assets and supported with technology to ensure the integrity of the assets

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Article by: Sushmita Rai, 3rd Eye Advisory Ltd
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