Ishita Majumda, VP, Data Analytics Platform at eBay, shares how the online retail giant’s strategy for establishing data-driven business practices has evolved in recent months
Data democratization has become a hot topic in recent years. Increasingly, enterprises want to empower non-data staff to use data-driven insights and embed data-driven business practices across their whole organizations.
For many companies, data democratization initiatives start with delivering programs to improve the data literacy of non-technical staff. But in this week’s Business of Data podcast, eBay’s VP, Data Analytics Platform, Ishita Majumdar, shares how this alone has not been sufficient to entrench data-driven business practices at the e-commerce giant.
As many companies do in the early stages of data transformation, eBay established an internal analytics university. It provides a series of courses taught by Majumdar’s team. But over time, it became clear this academy was not driving change at scale.
“Everyone attended the classes and ticked all the boxes,” Majumdar explains. “But they were also saying the product manager’s job [for example] is so complicated that, if they must make the time to write these very complex SQL queries, it becomes a two-person job. That’s when I suggested we take the data where the user is.”
Making Data Accessible for Non-Technical Staff
Rather than focusing just on upskilling non-technical staff, Majumdar and her team are now also working to simplify its analytics tooling and provide platforms that are easier for ordinary workers to use.
“It fell on my team to do more than just deliver platforms for the analyst and data scientist communities,” she says. “One of the areas I'm concentrating most on this year is democratizing data for the non-tech savvy community. How can we make sure we build tools and platforms that are easy to access, understand and create charts and visualizations?”
She adds: “We will modify our tools based on the user, rather than pushing the user to modify themselves. Tools should be easy to use. Nobody needs a Facebook tutorial.”
“There should be an abstraction layer to translate the queries,” she continues. “But, as a user, I should be able to click two or three buttons or write a simple English query.”
Of course, Majumdar is being mindful not to take functionality away from staff members who want to master more advanced analytics tooling. But it’s this combination of developing new self-service platforms for non-technical staff and improving data literacy via eBay’s data academy that will form the backbone of the company’s data democratization programs in 2022.
“There are many people who would still like to do their own abstraction, they want to go deep, which is great,” she concludes. “I’m not taking that option from anybody. But most people don’t want to deal with that. So as a platform team, we’ll take care of it and give you the interface and visualization engine which can cater to your needs.”
Key Takeaways

Transform the culture around data. Many employees still see data as something used exclusively by data teams
Do what works best for the organization. When eBay’s data academy didn’t yield the expected results, Majumda’s team reviewed its approach to data democratization
Bring the data to the user. Developing self-service data platforms will make it easier for non-technical staff to harness data-driven insights