Collecting and Analyzing Multiple Data Sources for Better, Faster Business Intelligence

March 1, 2017

A leading waste management company was looking for ways to support faster decision-making and develop new waste solutions for customers, including solutions to achieve zero waste goals. 

Before the data lake: The company struggled to manage the massive amounts of disparate customer data it received daily – and realized the data was not being accessed or used at all. It was expensive and time-consuming to access and process data from the company’s data warehouses. In addition, many external data sources and files had significant data formatting and preparation issues. 

With the data lake: The company was able to meet increased demand from the company’s leadership team for reporting. The more user-friendly, responsive and cost-effective solution enabled the customer to collect and analyze massive volumes of data from multiple data sources for faster and more accurate decision-making.

Results: The company realized 20x the storage capacity at 50% of the cost of the previously planned upgrade. It saved $9 million in the first year and estimated $15 million in cost-savings over three years. Also, the customer quadrupled the throughput rate, enabling multiple pipelines of data to be processed in parallel. 

 
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