Data Governance: Effective Strategies for Data-Driven Businesses

Only 30% of the data available in companies is used, mainly due to internal ignorance of the information available.

In the information age, data governance has become a fundamental pillar for organisations seeking to optimise their operations and maintain a competitive advantage in the marketplace. Implementing an effective data governance strategy not only ensures the quality and proper use of information, but also drives companies towards a truly Data-Driven model.

In this sense, PUE, Spanish technology leader in integrated solutions for consulting and implementation of Data, GenAI and Cloud projects, analyses the best practices and benefits associated with a robust and well-structured data governance.

Methodology and Technology: Two Essential Pillars

From a methodological point of view, it is essential to clearly define roles, responsibilities and owners of data assets within the organisation. Promoting the use of data, both internally and externally, is crucial. Measuring the use and quality of data through well-defined KPIs allows for accurate metrics that ensure that data is not only available, but that it is of high quality and used effectively.

From a technology perspective, the key is to use open, polyglot tools that can collect metadata from a variety of sources, detect changes and measure data quality. Automating these processes is vital to ensure efficient data governance in multi-technology or multi-cloud environments.

What are the most common mistakes?

However, as Sergio Rodríguez de Guzmán, CTO of PUE, says, “one of the most common mistakes organisations make when establishing data governance policies is the lack of measurement of data usage. Although generating a data catalogue is usually not problematic, promoting and measuring the use of this data is often overlooked. To avoid this mistake, it is crucial to implement practices that encourage active use and continuous evaluation of the impact and quality of data.”

Organisations that implement well-structured data governance gain several competitive advantages. Currently, it is estimated that only 30% of the data available in companies is used, mainly due to internal ignorance of the information available. With the right data governance policy, companies can significantly increase this percentage, becoming truly Data-Driven companies, enabling them to make more informed and strategic decisions.

Measuring and Evaluating Data Governance

To measure and evaluate the effectiveness of their data governance strategies, organisations must define and analyse specific KPIs. Observability of information is a key concept for successful data advocacy, and this is achieved by using technologies that enable complete and accurate visibility of data and its uses.

Hybrid environments and AI: the future of governance

Technologies such as artificial intelligence (AI) and machine learning play a crucial role in improving data governance. Generative AI, in particular, can understand and reason about the information available to companies, generating metadata, measuring the quality of the information, detecting anomalies and proposing solutions to the errors found.

Contrary to what one might think, a hybrid or multi-cloud infrastructure does not necessarily complicate data governance. Modern communications allow these environments to operate as a coherent whole. The key is to use appropriate tools that facilitate interoperability between different systems and clouds, ensuring smooth and efficient data governance.

Implementing an effective data governance strategy is essential for any organisation that aspires to be competitive in the digital age. By following methodological and technological best practices, avoiding common mistakes and taking advantage of emerging technologies, companies can ensure their data’s quality and optimal use, thus achieving a sustainable competitive advantage.