Data & Analytics in the modern day and age are the eyes of the business to tread carefully into the unknown. As the data guides the business, the necessary levers/decisions are exercised by the leaders to make the best of the trend illustrated by the data.
In this blog I am trying to exhibit a model, which tries to encapsulate and surface a holistic view of data & analytics landscape in one view for the business.
This brings more collaboration within the business, and in the uptake of the work churned out by the data enablement team.
Expanding on the same, in recent years I have started adopting the concept “Field of Vision” in organising the data assets within the business, and its associated reporting and analytics.
Below is a summary for a fictitious organization (FMCG), Data & Analytics Overview

From the above the key points to note are as follows:
- Business is comprised of multiple departments, and each department has a leader/decision maker for its own space, Identifying them is critical to this process
- For each department, identifying the data assets is the next important step, and its not necessary the source for that asset belongs to that department (Field of Vision)
- The data asset once tagged, can be used in other departments via leveraging multiple other reporting platforms catered to the audience needs.
- The advanced ML concepts and algorithms being applied to these data assets again catered for the department audience
- The multiple reporting capabilities must be associated with the data assets to re-use the existing and available options to be expanded to other teams
- The above grid only presents the “Current” picture of the data analytics capability, not the “Proposed”
The above diagram illustrates a “Data & Analytics Overview” for the business, where user from any area of the business can visit and work out the availability of data asset in the company, its associated analytics availability relative to the reporting platforms.
This alleviates the problem where the teams are working in silos, and nurtures the creativity and supporting the term “Data Democratization“.
Now this is not an overnight process, and the overview can be quite complex for any organization in terms of data sets, varying analysis on same dataset. But cramming all at once into the document, keeping it as a living document and I highly recommend for any teams to cross-collaborate and improve the uptake of your work.
Start small and then expand upon. This is just an idea in practice which yields a lot of value in my work and past.
The above is a culmination of concepts from data catalogue, data mesh and other practicing techniques and a blend for efficient working.
I hope it helps in your working too and happy to share experiences with the readers.