Five Pillars of Data Governance – Implementation
What is Data Governance Implementation?
Actionably, a data governance plan can configure the corporate philosophy of data acquisition, management and archiving. It’s a cultural influence that requires both IT and Business sides of the company to come together to determine data components and the rules that govern this data across applications. From the implementation side, a data governance framework touches practically every part of the data administration process down to the individual technologies, data models and databases.
How do I Implement Data Governance in my Organization?
The following are components of an effective data governance strategy, which business entities can utilize, to empower decision makers to get the most out of their big data projects. This helps to maximize data insights and achieve the most value from big data. Organizations can help key stakeholders trust their data insights by taking the following five steps to data governance.
1. Make Data a Business Asset
Keep a logical strategy behind the company’s data initiatives instead of going after point solutions bound to data governance process or data quality. A fundamental question that should be answered while developing this strategy is: How do you make data a business asset to drive informed decision making?
2. Conduct Training Sessions
Conduct a broad data and analytics training for all levels of the organization’s management. Management does not necessarily need a comprehensive understanding of big data, big data technologies or advanced analytics, but they should be aware of the fundamentals and foundations of these concepts in order to ask the right questions to their data analysis teams.
3. Introduce Definitions
Construct simple definitions for the use of data throughout the firm using metadata and data dictionaries. A common and familiar language is critical for understanding insights and creating persistent and rational outcomes. This is particularly crucial for businesses that operate globally.
4. Carefully Grant Access
Recognize which individuals and departments should have relevant access to the organization’s data. As more data is available, it should not be speculated that every member of the firm has access to it. Some individuals or teams may only need access to specific high levels of data while others may want unfiltered data in order to conduct their own analysis. Effective consent and security depends on granting the access right.
5. Explore Data Storage
Organizations should determine how data can be stored with a new attitude so the data infrastructure is fit for purpose. Businesses should research and explore different storage platforms that can support the wide range of organizational data needs.
Why is implementation important?
A growing number of organizations, notably larger ones, see big data as highly important to their firms. Companies report satisfaction with their big data, particularly in attaining new customers and finding new sources of revenue. Nonetheless, decision makers can still be unconvinced of the insights being presented to them. Decision makers might dismiss insights if they don’t fully understand the analytics tools and complicated methodologies behind the outputs and visualizations. They may also reject insights if they don’t trust the data supporting the analysis.
‘Implementation’ of Data Governance enables the decision makers of an organization to trust its data. A vital role for a Chief Data Officer (CDO) is to build the organization’s data as a strategic, trusted asset. The CDO helps an organization manage the availability, usability, integrity and security of its data.