Abhishek Ravi, CIO, Dream11, CIO News, ET CIO

Today, enterprises need to accelerate their digital transformation journey. For that, they must leverage the power of data. Robust data architecture can be the biggest differentiator among organizations in a post-pandemic world. This can add a competitive edge to their efforts.

Abhishek Ravi, CIO, of Dream Sports, discusses the ways to create a data architecture that will fuel digital acceleration for enterprises.

ETCIO: What makes more sense, a top-down approach or a bottom-up approach as far as data is concerned?

RAVI: This is a very pertinent question. Data is a part of organizational culture. However, the culture of your team as a whole needs to have the ability to ask the ‘why’ questions.

I think it is the question of being able to convince whether you are alone in the room or with 50 people in the room- the decision needs to be made, on the basis of what the data says. . No amount of data will be enough for making decisions. There, you also need to be data-informed, where the data is indicative enough along with that 1 percent of gut instincts. This helps to bring out the innovation aspect and keeps it going.

ETCIO: What are the necessary steps to create a data architecture?

RAVI: Technology, process, and people (TCP) is the foundation for data architecture. When people mention data architecture, they think there is a technology that I have on board, but it’s not that. It starts with technology, and leads to process and ultimately to people, where it probably needs to be consumed by your stakeholders correctly to consume the right data and make the right decisions. As a result, the journey begins with data ingestion by the person who is self-serving himself or herself to make the correct call at the right time because time is of the essence in technology. So, technology, people, and process are the aspects where you have to define your way of doing things to make it easy for data access to the person who is required to make calls.

The other part is determining one’s core and non-core factors. When things become significant enough, such as data policies evolving, responsible data usage and compliance become required components of your data architecture design. It is vital to differentiate where your compliance moisture lies and to what extent you can be assured that you’re compliant with a particular region or the state of the law. Thus, that becomes important when designing the data architecture concerning technology, people, and processes. So, you have to put all these things into the 360-degree ambrite.

ETCIO: What is often missed in building a resilient data architecture strategy?

RAVI: – One critical aspect that is missed is that the data architecture is a shared responsibility. So, for every team in your company, be it finance, HR, technology products, data science, or data analysis, you think of all teams as stakeholders and shareholders. All are equally responsible for giving feedback, iteration cycles, security maintenance, and compliance maintenance. It’s not the other team’s job unless that mindset evolves that the data architecture you are using is going to be lope sliding, and would not be the right architecture to evolve.