Getting Started Data Governance Tools and Best Practices
What is Data Governance?
Data Governance is the process and management of data availability, usability, integrity and security of data used in an enterprise. Data Governance includes all the steps from storing the data to secure it form any mishap. Data Governance is not just only about technology. Responsible for the particular data asset along with the technology.
Data Governance is used in an organization at a maturity level to make sure critical and vital data is managed and protected. Data Governance gives clarity of the information which helps in defining the Decision-Making processes around data. Data Governance is a strategic, long-term process. Data Governance is essential for Finance and Insurance organizations especially those that have regulatory compliance. These organizations are required to have formal data management processes to govern data throughout its lifecycle. Data governance can also enable the authorization on the based of classified data to the particular users.
Benefits of Data Governance
- To improve data quality.
- Helps in understanding the data and show the data lineage.
- Helps in adopting Regulatory Compliance.
- Improve the capabilities of Decision-Making by data.
How Data Governance Works?
Data Governance includes many concepts such as Data Quality, Data Policies, Business Process Management, Regulatory Compliance, Risk Management, Business Policies. An organization needs to define the business process before adopting the Data Governance model.
Why Data Governance Matters?
The organization also need to make sure the safety of all data called Data Security, effective data masking of personal data (like SSN, passwords), and compliance with new data protection and privacy laws like GDPR(General Data Protection Regulation).
An effective Data Governance can provide a solution to handle this kind of problems. Data Governance provides a complete audit report of who did what with which data. Easier for the organization to trace if something went wrong.
How to Adopt Data Governance?
While selecting the Data Governance, the organization needs to find where improvements required in the system. Firstly, choose some specific dataset and then further implement for all the dataset.
After choosing the dataset and the problem, define roles, responsibilities, and process to different teams. The duties can be understanding data, cleaning the data, data transformation or enrichment, and at the end monitoring. There should be one team for each of the process. This step also helps in improving the data qualities. Any particular dataset and dataset owner will be responsible for the data integrity and provide the technology to ensure the integrity of the assets remains high.
After the integrity and all process, an organization must change the culture of the organization to be master data-based rather than transaction data-based. Finally, a feedback mechanism which helps in the improvement of the process. The users using the Data Governance framework have rights to raise any feedback.
Best practices for Data Governance
Target big start with small: Data Governance is an iterative process, so everyone needs to define the phases or iteration which requires in very first go. Data Governance starts with the people, data policies and culture and data stewardship can be targeted. It can take many steps to reach a maturity scale. Start by highlighting a few issues or problems moving it to a more significant level.
To choose data stewardship wisely: Choosing a data steward depends on the stage of underdevelopment Data Governance program, so the organization needs to select this carefully.
Data Governance Tools
- Apache Atlas - Apache Atlas is the governance and metadata framework for Hadoop. It supports several Hadoop components to manage metadata in a central repository. The metadata events are captured and stored in the metadata store then these metadata events can be classified using tags. These tags can be further used to enforce security policies by Apache Ranger.
- Alation Data Catalog - Alation data catalog provides users with a single source of reference for the multiple data sources which helps in discovering and finding the data which users need. Alation data catalog helps in automating governance tasks, like updating data dictionaries and educating users on good governance practices, providing collaboration features for sharing information.
- SAP Master Data Governance - SAP Master Data Governance is a repository-oriented Data Governance tool designed to support an enterprise to meet needs like data quality and data policy management. An organization can identify and manage critical data assets by using metadata and glossary terms used to establish data policies and rules, define data ownership, and easily trace data lineage.