Enterprise Data Platforms, American Express, VP: The Data Landscape is Evolving Continuously

Enterprise Data Platforms, American Express, VP: The Data Landscape is Evolving Continuously

(US and Canada) Purvi Shah, VP, Enterprise Data Platforms, American Express, speaks with Leonard Maganza, Chief Customer Officer, Syniti, about her patents and the approach to data management at American Express.

Shah says that she has been at Amex for about 10 years and currently leads the enterprise data platforms team. Responsible for the company’s global data ecosystem, Shah focuses on bringing data together across multiple systems, unifying the information so that it can be used and leveraged as a data asset to power customer experience.

Shah formerly served as the president of Customer 360, an enterprise asset and CRM for American Express, that allows Amex to understand customers and their relationships across the life cycle — from acquisition to servicing them and detecting credit and fraud risk.

The first patent she achieved over the past five years was for her role on  the merchant data products team. “Our global merchant sales team was spending too much time going to multiple different systems, pulling the data together to create insights. What we did was bring that data together using our big data ecosystem, and created dynamic insights for the sales team. And we made it so easy for them to simply drag and drop the information so they can spend more time with our merchants,” Shah says.

The second patent was on Customer 360. “Our customers and customer relationships are extremely varied. We have individuals like you and I, and businesses. So, how do we understand what relationships they have had or currently have? We have to take information across 15 different legacy systems and try to understand the discrepancy to come to the information. This is where we created the flexible framework to do that mapping across the variety of systems, processing millions of records,” she adds.

Amex has been investing in the big data ecosystem for over a decade. Shah says that the prime job is to consolidate and bring together data across multiple different systems globally, to ensure the right balance and controls, right data quality checks, and think about ways to scale these across the petabytes of data.

“More importantly, organizing it in the right way so that our end-users, which are both AI/ML users and our analytics data scientists across the board, can easily leverage that to create the insights to power the best customer experience, and to make decisions very quickly. We have created this ecosystem that allows thousands of our colleagues to do that very quickly across the board,” Shah explains.

Sharing an important lesson learned over the years, she says that the data ecosystem and the data landscape have changed and evolved and continue to do so.

“We value data very heavily and we sometimes don't necessarily put migration at the forefront. So we have lots of legacy systems that are still heavily used. That this is one area as a company we are focusing on. We call it ‘mission to decommission.’ That is, how do we simplify all of these data ecosystems that we have across American Express so that the users can go to one place to get information versus having to go to multiple data ecosystems,” she concludes.

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