Data Governance tools for Splunk

List of data governance tools

Data governance is a strategy of handling data within an organization. It is a set of rules, policies, standards, practices etc. which main purpose is to ensure data has a high quality and integrity, is safely stored and there are no ambiguities in meaning of common terms. Applying this strategy is a long process, engaging whole organization, especially IT and data consuming departments. There are certain data governance tools which helps applying these theoretical plans in real life.

Talend Data Fabric

Talend Data Fabric combines data integration, integrity, and governance in a single, unified platform. It simplifies data quality and security with built-in functionality for making sure your insights are trusted, governed, and actionable.

Access control: No
Business Glossary: Yes
Change history: No
Commenting/Community: Yes
Data Catalog: Yes
Data Classification: Yes
Data Lineage: Yes
Data Mapping: Yes
Data Profiling: Yes
Data Quality Management: Yes
Support for workflow: Yes
Web Access: Yes

Data governance software is a broad category of solutions which main purpose is to:

• Develop and maintain common data language,
• Ensure compliance with law regulations,
• Track data lineage,
• Assign roles and responsibilities,
• Improve data quality.

As data governance is more of a framework which should be adjusted to each organization separately, there is no one tool that suits all companies. Some may require business glossary or data catalog, while others will benefit more from advanced data lineage. Although there are vendors that provide all-in-one data governance tools platform, in some cases it may be better to select more specialized software that will cover only part of the mentioned requirements. Some examples of such tools are:

• Data dictionaries,
• Data modelers,
• Business glossaries,
• Data policies managers,
• Sensitive data discovery tools,
• Law compliance software,
• Data quality tools.

Implementing data governance framework is not an easy process yet benefits coming from it make it good investment. Common data understanding is one of the greatest outcomes which improves clear communication between departments and leads to precise analytics. It is not uncommon for IT data teams to not understand what they are working on, what KPIs are or what some terms mean. With data governance software, business users can easily share their knowledge with engineering teams.

Better data quality and assigned responsibilities for each piece of information is another game-changer for many organizations – any data discrepancy can be quickly identified and reported to the right person. From the formal point of view, data governance tools will help complying with law regulations such as European GDPR or Indian PDPB.

In the end, an outstanding example of poor data governance. In 1998/99 NASA launched Mars Climate Orbiter worth $125 million. Sadly, when approaching Mars orbit, team on the Earth lost contact with the satellite. The reason was dull - one team used metric system, while another used imperial system of inches, feet and pounds what led to wrong calculations of satellite trajectory. Although most of organizations will not send a robot to Mars it is still very important to ensure that common practices and terminology are followed within an organization in what listed data governance software can help.