Challenges that can be resolved with Data Governance

Compliances and government rules can be a big problem for many companies today, since the number of standards has grown they have become more complex. Regulations such as the LGPD have an emphasis on data and soon more standards in this regard will appear. With GDPR already in place in the European Union, other countries have sought similar standards to keep user data safe and regulate the activity of companies that collect, process and store this data.

Identifying data considered personal and validating this data through an entire supply chain can guarantee, in addition to compliance, the resolution of other data challenges in the organization, such as problems with Data Governance.

An efficient application of Data Governance is able to serve multiple functions in an organization, such as compliance with more than one rule in a single application, find personal data of users, contribute to the creation of a data-driven culture in the organization and solve several problems with data simultaneously.

For investment in a Data Governance application to be optimized, it needs to solve some problems:

• Compliance with rules and regulations
  There are internal rules and there are government regulations, and they all have to be enforced. Many also require a sophisticated level of monitoring, where you need to know exactly what information needs to be reported, who to report to and where this information is found, and this is perfectly possible with a robust Data Governance application.
• Data security
  Users should not spend their time searching for the correct information or questioning the data, but rather analyzing the data to reveal meaningful business insights. The ideal Data Governance scenario is able to document rules, common definitions, data lineage, catalog data, and share glossaries to provide answers to data users while the number of problems with data integrity decreases, meaning the intent is provide accessibility and understanding for more frequent use of the data.
• Lack of understanding of data assets
  It is not uncommon for users to draw different conclusions from information that is not unified, generating doubts and discussions. If your organization is wasting time and resources with constant explanations of the meaning of the data, since IT staff need to constantly explain meanings and ways of using data to business teams, Data Governance is ideal. Dictionaries, glossaries and simple self-service tools, in addition to the collaborative culture, are able to improve understanding and increase use in the organization.
• Decentralized data
  In a Data Warehouse initiative, for example, organizations spend a lot of time defining meanings, what the data source is, and what kind of transformation they will need to go through the mapping process. If these data are not governed simultaneously, it is possible that all this information will expire quickly. With the application of Data Governance, this metadata can be captured and organized during the construction of this Data Warehouse.
• Unidentified fault points
  When a project freezes or shuts down on behalf of individual team members – whether for short or long periods, Data Governance is required. With it, it is possible to identify isolated points of failure, such as this type of absence, and repair with agility. Documenting critical information through a Data Governance application provides enterprise-level access to technical and institutional knowledge to ensure that projects are flawless and that vital information losses are prevented.

Of course, the occasions of using Data Governance go much further, and its value is undeniable, after all data challenges are in every organization. With a comprehensive Data Governance framework, organizations can proactively manage and mitigate data problems, and resolve them before business is impacted.

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