Data Governance (Part 1)

As data continues to grow at an exponential rate, the value of data governance is becoming increasingly critical to facilitate digital transformation which enables competitive data-driven decision-making.?According to Cisco, around 5 quintillion bytes of data is generated everyday which drives the need for data governance solutions to ensure “that an organization’s information assets are formally, properly, proactively, and efficiently managed throughout the enterprise to secure its trust and accountability.”?Consequently, the Data Governance Market which was valued at USD 1.81 billion in 2020 is projected to be worth USD 5.25 billion by 2026.

Does your organization have data governance in place??In this part 1 of a 2-part article, I describe data governance, data policy, data governance frameworks, goals, and strategy.?In the next article, I will cover a 4-Step Data Governance Model, data governance best practices, data governance maturity model, and data governance tools features.

What is data governance?

Data governance is the method of identifying important data in the entire organization, safeguarding its high quality, and improving its value to the business.

What is data governance policy?

A data governance policy outlines how organizational data will be managed and controlled.?This comprises of several areas including:

Data quality – ensures data correctness, accuracy, ad consistency.

Data availability – ensures that data is available and easy to utilize by the users.

Data usability – ensures clear data structure, description, and documentation, as well as easy search and retrieval.?Data must also be compatible with the tools used by the organization.

Data integrity – ensures data preserves its essential properties during storage, conversion, transmission, and view across different platforms.

Data security – ensures data classification based on sensitivity and defining processes for data protection.

Data Governance Frameworks

Data governance structure helps organization determine roles and responsibilities and facilitates decision.?There are three types of frameworks:

1.?????Command and control – few employees act as data stewards who take on data governance responsibilities.

2.?????Traditional – many employees volunteer as data stewards while a few serves as critical data stewards with additional responsibilities.

3.?????Non-invasive – recognizes people as stewards base on their work and its relation to data.?Everyone who creates and modifies data becomes a data steward for that data.

Important elements of data framework include funding and management support, user engagement, and data governance council.

Standards which can help formulate a data governance framework include COBIT, ISO/IEC 38500, and ISO/TC 215.

Data Governance Goals

Data and information governance help achieve organizational goals such as:

• SOX, Basel I/II,?HIPAA,?GDPR compliance
• Data value maximization and re-use
• data-driven decision making
• Data management cost reduction

Data Governance Strategy

A data governance strategy describes the content of an organization’s data governance framework. It explains the following data properties for each set of organizational data: physical storage, access, definition of important entities (e.g. customer, vendor, transaction), data structure, current and desired quality of the data source, purpose of data, and data requirements to meet the goals.

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Tina

References

Imperva.com (n.d.). Data Governance.?Retrieved at https://www.imperva.com/learn/data-security/data-governance/#:~:text=Data%20Governance%201%20Data%20Governance%20Frameworks.%20A%20data,...%204%20A%204-Step%20Data%20Governance%20Model.%20

mordorintelligence.com (n.d.).?DATA GOVERNANCE MARKET - GROWTH, TRENDS, COVID-19 IMPACT, AND FORECASTS (2022 - 2027). Retrieved at?https://www.mordorintelligence.com/industry-reports/data-governance-market