Data governance

Data governance is the process of managing the availability, usability, integrity, and security of the data in enterprise systems, based on the internal data standards and policies that control data usage. Effective data governance ensures that data is consistent and trustworthy. The data governance process enables organizations to ensure that high-quality data exists during the lifecycle of the data. Data governance implements data access rules and policies to improve data security.

Data governance also manages the data lifecycle, which is a sequence of stages that a particular unit of data goes through from its initial generation or capture to its eventual archival or deletion. Traditionally, organizations focused on management of the data scattered around various data assets to meet tactical goals, with less emphasis on strategic business needs. Now organizations are starting to recognize the benefits of well-organized and well-classified data, to get a profound visibility on data as a strategic asset.

Data privacy compliances like the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR) require that the organizations put in place appropriate measures to protect and manage customer data, because customers have the right to know if their personal data is being stored, sold, or disclosed.

The GDPR's primary aim is to give individuals control over their personal data and to simplify the regulatory environment for international business by unifying the regulation within the EU. The CCPA states that a consumer should know if their data is being stored by an organization, and consumers can request to delete their personal information. Without a well-defined data governance framework in place, it is challenging for organizations to know all the places it stores customer information to comply with CCPA or other consumer privacy acts. Violations may lead to legal implications and fines or penalties.

A well-defined Data Catalog makes it easier to identify customer data distributed across various data assets, as a Data Catalog tags data and builds relationships between data attributes, enabling the organization to adhere to existing and future data regulatory compliances.

An organization’s multiple business units collect customer communication channel preferences by email, phone call, or text message. The Data Catalog collects metadata associated with all the data stores which handle customer communication preferences. Using the Data Catalog, the organization’s business units can combine all the different rules for customer communication and interact effectively with customers, elevating satisfaction and trust.