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Swimming in Data

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17 June 2019
Joan McGowan

Data Lakes in Banking

Data is a recurring topic in Celent’s conversations with CIOs. The broad ask by CIOs is to be able to derive insights from a wide variety of data in different formats and deliver this insight to the business side. Core to this effort is to consolidate and extract data into and from a single source. Enter data lakes.

There are 3 compelling reasons that justify investment in a data lake:

  1. Ability to more easily extract more value from data
  2. Data lakes provide value as critical enablers, allowing the organization to tap into new use cases and insights
  3. Data lakes effectively democratize access to information, enabling an organization to act far more quickly on data-driven insights

But it’s not all plain sailing. In my report Swimming in Data: Data Lakes in Banking, I answer 3 key research questions:

  1. Why do banks need a data lake?
  2. What are the potential applications of data lakes?
  3. What does a bank need to take into consideration to get started with a data lake?

I compare uses of data warehouses with data lakes, provide examples of top line use cases, and I look at lessons learned from 5 early adopters in the banking industry.

A data lake is an enabler but not a panacea

Data lakes comprise only the data infrastructure and require an application layer to drive the benefits, therefore, there are additional considerations depending on the application needed. For example, to enable real-time calculations the infrastructure would need to be scalable. Moving the data lake into the cloud is one way to ensure this. Caution is required if your data lake operates across silos, which is often the case in banks. If the investment and ownership lie with a specific business, banks must be careful not to create multiple data lakes, each with a different purpose, principles, and user groups. And, the most critical building block for success when launching an initiative in the data space — especially when it involves artificial intelligence, is adapting the culture of the organization.

Data remains at the top of banks’ agenda, and technologies such as data lakes will continue to gain traction in the industry. Celent will continue to follow the progress of the banking industry in this domain and we look forward to saying more on this topic in future research.

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