The Strategic Imperative of Data Governance for Enterprise Data Platforms   

By Direnc Uysal | @intelia | August 15


As Chief Technologist at intelia, I am fortunate to have been granted a behind-the-scenes look into enterprise use of data and how organisations that are truly data driven decision makers succeed. One thing stands out as a recurring theme – addressing data governance and having it embedded into how the organisation approaches data – technically but more importantly in a process and people sense.

When using enterprise data platforms, data governance has to be a foundational step. Companies must not tack on governance as an afterthought, but consider it as a framework with which to model and run a platform, any other model will only see platforms struggle to ensure both efficacy and usability.

Unified Data Governance empowers you to command your data, enhance operational effectiveness, and reduce data-related risks and compliance issues. Amidst the excitement surrounding Generative AI and the widespread adoption of Machine Learning solutions in businesses, the significance of data governance has surged.

Gartner’s 2023 Top Strategic Technology Trends reports that 85% of enterprises will combine human expertise with AI, ML, natural language processing (NLP), and pattern recognition to help augment foresight, increasing worker productivity by 25% in 2026 (1).

The winners in the AI race will be those who have data & AI governance at the forefront – implementing processes, technology and supporting organisational structures to ensure they have control and can operationalise their models.


Data Governance: What is it?

To derive valuable insights and make well-informed decisions, embracing the practice of data governance within their enterprise data platforms is the key to a successful strategy for organisations. So, firstly, what is data governance? Data governance is the art of managing, safeguarding, and optimising an organisation’s data assets.

With a structured framework in place, it enables a comprehensive understanding of available data, ensures consistent access with appropriate restrictions, and addresses regulatory requirements from a centralised, well-managed platform. This practice fosters a shared language across data assets, enabling lucid discussions surrounding data and insights.

Why is data governance so important?

Effective data governance is a crucial tenant to any data-driven organisation. Why? It ensures the quality of data by maintaining accuracy and consistency, enabling reliable decision-making. Secondly, data governance plays a vital role in safeguarding sensitive information and protecting against data breaches, ensuring data security. Thirdly, compliance with relevant laws and industry standards is achieved through data governance, minimising legal and financial risks.

As well as this, it facilitates accessibility and integration from diverse sources, leading to comprehensive insights. Transparent data management practices are promoted, allowing stakeholders to understand data processes clearly. With trustworthy data, organisations can make confident, data-driven decisions, enhancing efficiency and productivity. Ultimately, effective data governance fosters a culture of accountability and insights, positively impacting overall business performance.

By 2026, enterprises that have adopted AI engineering practices to build and manage adaptive AI systems will outperform their peers in the operationalising AI models by at least 25%(2).

Data governance is going to be extremely important in Machine Learning and Generative AI approaches – being able to explain how your model came up with the answer is going to be critical to embed trust and address regulatory needs – Europe is leading the charge with an active approach to AI governance.

Common Data Governance Challenges Faced:

  • Teams unable to identify what data is available and how to get access to that data
  • Complex and often overlapping compliance requirements around the classification, handling, deletion and treatment of data across the organisation
  • Issues with quality across source systems and consumer systems – not being able to identify these issues until it’s too far downstream and not being able to actively remediate them
  • Inability to audit access against data assets – who has accessed what and when? – especially when a breach occurs
  • Definitions for specific business terms varying across business teams and resulting in inconsistent metrics, reports and business discussions

Key functionality required for data governance:

  • Data Catalogue: An encompassing repository granting complete visibility into an organisation’s data assets, fostering transparency and accessibility.
  • Business Glossary: A universal dictionary defining data asset meanings, ensuring consistency and clarity across all data-related conversations.
  • Data Access Policies: A well-established process for granting data access, bolstering data security and compliance.
  • Data Lineage: A technical representation of data flow and transformation, facilitating traceability and accountability.
  • Data Quality: Mechanisms to measure and address data quality issues in source data, such as missing values or mismatched types.
  • Data Compliance: A centralised approach to manage and track regulatory requirements across data assets.
  • Data Processes/Workflows: Forums to streamline decision-making, manage impact, and seamlessly embed governance throughout the organisation.

What can be done:

The benefits of data governance are far-reaching, as highlighted in intelia’s Benefits of Data blog. As discussed in the blog, implementing data governance, organisations can maximise data utilisation, and establish a solid foundation for data-driven decision-making.

Initiating a successful data governance journey means assessing your organisation’s current maturity level. Identifying pivotal aspects requiring immediate attention and prioritising seamless implementation is vital. By collaborating with experts at intelia, you can navigate the process and access tailored solutions catering to your organisation’s specific needs.

Ensuring strong data governance within enterprise data platforms means shaping a future where data becomes an unparalleled transformative force, propelling your business to new heights! 🚀📊


Source: Gartner’s 2023 Top Strategic Technology Trends, 2022. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally. All rights reserved.

Source: IDC FutureScape: Worldwide Artificial Intelligence and Automation 2023 Predictions, doc #US49748122, October 2022