Driving Impact through Data Excellence

By Abhinav Shukla, VP, Digital and Data Platforms, Fidelity Investments India

“Data is the new oil” goes the cliché. However, the ability of a business team to use data to derive meaningful value demands leadership and foresight. A structured approach that addresses common challenges, leverages best practices, and avoids common pitfalls is essential to achieving data excellence.

Often, challenges arise from data that is incomplete or not in a format suited to specific purposes. Data may also be disjointed or housed in siloed platforms. In many cases, different terms are used for similar data types, making it difficult to aggregate information across systems and applications to build a comprehensive view. The absence of unique identifiers for user interactions often becomes a missing link in tracking a user’s journey across applications. As a result, efforts to optimise user experience, remove friction, or improve efficiency may be sub-optimal when based on an incomplete understanding of user behaviour. It is therefore essential to align, integrate, and organise the data ecosystem to achieve superior outcomes.

The most important step in embarking on the journey to data excellence is defining a clear vision. A leader’s ability to articulate this vision is critical in galvanising the team and elevating data as a strategic priority. Team members must be fully aware of and aligned with this vision to break down silos and work collaboratively.

The next key enabler is a common platform to bring data together. A value-driven platform approach can help minimise risk while ensuring efficiency and scalability. Teams should identify key use cases and collate the data required to generate actionable insights. Cloud-based data lakes and warehousing platforms enable rapid pilots and testing of assumptions before scaling solutions.

Another critical component of a robust data ecosystem is a well-defined data taxonomy. This structured, hierarchical model establishes a standardised vocabulary and logical relationships that improve data discovery, enhance quality, and strengthen governance. It plays a vital role in understanding user requirements and designing tailored solutions. A common vocabulary also enables more effective end-to-end insights for analytics teams.

The final key element is data governance. This is often overlooked, yet it is essential for ensuring data security, regulatory compliance, and efficient data usage. When data is properly classified at the design stage, it becomes significantly easier to protect it as it flows across multiple IT systems. Leveraging industry-standard tools to catalogue and classify data can improve productivity while reducing risk. Building organisational awareness of the importance of data governance is equally critical.

In summary, a thoughtful and tailored approach that incorporates industry best practices can unlock the true value of data. Organisations that invest in alignment, integration, taxonomy, and governance will be better positioned to drive meaningful impact through data excellence.