Improved decision making and cost savings using self-service analytics

Saved operating cost of $1 M annually for a leading food distribution company by building a cloud-based data lake and scalable data platform to aid advanced analytics and user-based exploratory analysis

Business challenge
The client, an industry leader in US food logistics services, was challenged with outdated internal data systems and off-the-shelf solutions which were unable to scale up to meet the organizations growing data science needs. The client wanted to remove dependency on the current third-party platforms and build an in-house system to understand the computations behind their key business metrics and needed the flexibility to build newer metrics more rapidly.

After on-boarding users to the new tool, the client is now able to track and control utilization and performance of the in-house platform in the most cost and time efficient manner, with lead time dramatically reduced from weeks to days. There has also been an annual saving on operational expenses by $1 million.

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