Data governance is often a painstaking, tedious, manual process. With automated metadata management, it doesn’t have to be.
Data governance is often a painstaking, tedious, manual process. With automated metadata management, it doesn’t have to be.
The European Union’s General Data Protection Regulation (GDPR) worries compliance teams at many companies with a presence in Europe. The rules are more stringent than those in the U.S., and failure to comply can make it difficult to do business in the lucrative European market. One of the fundamental aspects of GDPR compliance is data governance.
Data governance is the process by which enterprises understand and control their data:
• Sources of the data
• Data transformations from source to various systems and processes
• Data use in reports and dashboards
Data governance is the first step in the business challenge of ensuring regulatory compliance.
Especially in large organizations with many sources of data and multiple interconnected systems and applications, data governance is no easy task. Business intelligence (BI) professionals responsible for implementing and maintaining a data governance program must be able to trace the data that flows through the company’s systems and be able to show where every number on every report and dashboard came from and how it got there.
This ability becomes especially important in light of GDPR and other regulations. Enterprises must be able to show that their customer data is protected everywhere it exists, whether at rest or in transit from one system to another. Without a robust data governance environment, this task is nearly impossible.
Data governance was once a painstaking, tedious, manual process. BI professionals needed to know where all the data sources were and all the systems that touched the data. They also had to discover and catalog all the metadata at the database, table, and column levels. When things change (as they constantly do in large enterprises), BI professionals may be completely unaware until someone calls them to report a discrepancy.
The power of Octopai’s metadata management automation is changing all that. These tools
offer many advantages to BI groups:
• Automated metadata discovery, cataloging, and tracing
• Visual data lineage – see the path a piece of data takes from source to destination,
including ETL processes, middleware, calculated columns, and more
• Audit trails and what-if analyses display the causes or effects of changes to metadata, ETL
specifications, and calculations on downstream reports and dashboards
Further, with data traceability, BI professionals can partner with the IT team to ensure that
sensitive data is protected at all times, no matter where it goes in the enterprise.
Octopai’s automated tools can benefit the organization as a whole:
• Provide an audit-ready environment in which the business can confidently demonstrate compliance with GDPR, PCI-DSS, and other government regulations or industry standards
• Significantly reduce the time and cost of metadata discovery, cataloging, and tracing while increasing accuracy and completeness
• Quickly locate and fix data errors that manifest themselves as discrepancies in reports, dashboards, and key performance metrics
• Give business users and management peace of mind that the company’s data environment is under control
