How to future-proof your data governance strategy
Leo Nikles, BI Consultant at PBT Group
In today’s data-driven world where data volumes are rapidly expanding and data ecosystems are becoming increasingly intricate, having a robust data governance strategy in place is paramount. I have seen the challenges that companies face when it comes to managing data controls and mitigating its potential risks.
In this blog, I will examine the importance of data governance, discuss several of the considerations for curating an effective strategy, and the role that AI can play in ensuring compliance with ever-changing regulations.
The dangers of neglect
When it comes to a data strategy, one of the key risks that organisations face is the failure to implement comprehensive data governance practices. Data governance requires active participation from all stakeholders. Often, individuals do not fully grasp its significance or how it applies to various data streams.
Therefore, to ensure success, it is crucial to manage and educate employees, making data governance a part of their daily routines and overall business operations. Additionally, measuring data governance effectiveness through key performance indicators (KPIs) helps foster a culture of accountability and encourages adherence to governance principles throughout the business. Data governance must not be viewed as a temporary fix but as an ongoing practice that covers the entire lifecycle of data, including its description, lineage, and eventual destruction.
Top considerations for a robust data governance strategy
1. Aligning business and IT: The success of a data governance strategy relies on aligning business and IT departments. Both business and IT must understand the importance of any given project while also getting the necessary buy-in from executives. Once the organisation makes data governance a measurable objective, people involved in the project can integrate it into their daily duties while also getting a sense of ownership and responsibility.
2. IT infrastructure and tools: Implementing an effective data governance strategy often requires investments in acquiring metadata tools and creating centralised platforms for sharing business glossaries, accessing policies, and providing system support. While the cost of metadata tools can be substantial, they are a vital component of a robust data architecture, enabling companies to gain insights into their data and its behaviour.
3. Fail-safe mechanisms: Building fail-safe mechanisms within the data governance framework is crucial to mitigate risks. This can include measures like data separation, centralised catalogues, and contextualising content. By implementing these safeguards, an organisation can ensure that data is protected, controlled, and used appropriately across various business units and projects.
The role of AI
AI is poised to play a significant role in helping businesses stay abreast of evolving regulations and ensure data governance compliance. As more employees engage with data, there is a need to upskill them and provide access to a platform where they can seek answers and explanations related to data governance policies.
AI-powered systems can remove the human element of uncertainty and misinformation, allowing users to obtain accurate and timely information. Furthermore, AI has the potential to facilitate compliance with both local and international regulations, particularly for companies with global operations. By leveraging AI capabilities, companies can obtain faster responses to regulatory queries while minimising the risk of errors or oversight.
While companies are starting to recognise the importance of data governance, its successful implementation often hinges on having executive buy-in.
It is therefore imperative for business leaders to understand the value of data governance and actively drive its adoption within the organisation. With this executive support, data governance can be established as a fundamental step toward a comprehensive data strategy, benefiting the organisation as a whole and ensuring its ability to harness the power of data effectively.
In an era of escalating data volumes and complex data ecosystems, future-proofing your data governance strategy is a necessity. By acknowledging the risks of inadequate data governance, considering key factors in strategy curation, and harnessing the potential of AI, organisations can proactively address challenges, comply with regulations, and unlock the true value of their data.
Executive buy-in remains the linchpin for successful implementation, propelling data governance from an individual’s initiative to a company-wide imperative. Embracing data governance as an essential element of the business landscape paves the way for a data-driven future where businesses can thrive by harnessing the power of their data.