Regulatory and privacy threats have been under the spotlight since the initial adoption of the EU General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). It’s not surprising since data privacy revolves around how data is shared with third parties and how information is legally collected and stored.
As businesses protect the security of customer, vendor and employee data, organizations that are not compliant face costly fines, penalties and even lawsuits.
With increased regulations, data-driven organizations continue to refine their data privacy strategy, spending countless hours trying to understand the location of their data, which data is subject to privacy requirements and how to collect and aggregate data for reporting.
As part of that effort, organizations require a more efficient, standardized method to document compliance-related activities. That’s where data governance comes in.
Data governance is an enterprise framework that aligns people, processes and technology, helping data users delivers visibility into data.
Data governance identifies the data owners responsible for ensuring data quality, regulatory compliance and data usage. Identifying ownership verifies that someone is responsible for the data’s origin, definition, business attributes, relationships, dependencies and more.
Governance also assigns data stewards to oversee data analysis, produce reports for users and answer data questions. There are usually various owners for different types of data, but most critical is making sure that the organization collaborates across the enterprise to agree on ownership and terminology.
Promoting collaboration across IT and different departments to establish agreement on standard data definitions and domains is critical to creating an integrated data catalog.
With data stored across different data sources, a data catalog serves as a dictionary of knowledge about the organization’s data and processes to manage and consume data. Data catalogs arrange data into a simple, easy-to-understand format so all data users can consume and use it.
From a privacy standpoint, a data catalog helps manage data privacy and protection requirements by letting IT, chief data officers and compliance officers catalog and manage regulatory requirements. These policies and requirements are then connected with affected data assets such as business terms, reports and processes. These relationships are displayed to the user in a visual impact analysis diagram.
All this information is crucial to track. However, the data catalog must present impact analysis and data lineage diagrams in appropriate ways for both technical and business users to easily consume.
Data lineage documents and illustrates data’s entire end-to-end journey. Once information is ingested and begins to travel through systems, format, function and quality levels change. Lineage documents how data flows through different systems and platforms, creating an audit trail for data’s lifecycle. Business users track different views of data throughout the data supply chain by following business lineage.
However, to determine the full impact regulatory policy has on various data environments, organizations must also track technical data lineage.
Technical data lineage visualizes the complex details of a particular piece of data and the physical locations where it resides. Technical lineage helps illuminate the impact regulatory policy has on various data environments by identifying where personal or protected data may reside and how that data changed over time. This knowledge empowers the organization to ensure sensitive data remains private.
To protect and manage data assets and ensure compliance and data privacy, organizations require an automated data intelligence platform that brings data governance, data catalog and data lineage together.
With audit controls and data monitoring to track required actions, security protocols and retention policies, organizations with the right platform can provide automatic alerts for potential violations to ensure privacy and compliance. The same platform facilitates an audit of financial processes to detect and eradicate compliance, operational and reporting gaps. Users can visually display these processes and connect related business terms, reports and rules to the appropriate steps so everyone has a common understanding of affected data assets.
Data governance that includes a data catalog and data lineage provides accountability for data ownership and the ability for organizations to know where data is located and how it is being used. As a result of putting governance practices in place and using the appropriate tools, organizations improve the security and transparency of data usage, keep private information private and have a strategy for achieving data privacy compliance.
Are you looking to easily handle data privacy and complex regulatory requirements? Listen to the webinar, Data Lineage to Ensure Regulatory Compliance
Do you want to learn about how data governance helps business users collaborate effectively, develop new internal processes and procedures that efficiently manage, protect and report data? Visit our blog post, What is Data Governance