Collecting and Analyzing Multiple Data Sources for Business Intelligence

March 1, 2017

Waste Management Zaloni Case StudyZaloni created a data lake solution for Waste Management that is designed to collect and analyze massive volumes of data from multiple data sources for faster decision-making and improved business intelligence.

Finding Untapped Potential in Business Data

In the waste management business, competitive advantage is gained through the smart use of technology. Huge amounts of customer data are generated every day, and accessing disparate internal data sources and reaching insights can be a costly and lengthy process. Many external data sources and files have significant data formatting and preparation issues. Without a single data management platform that could handle the rising processing and reporting demands, Waste Management struggled to keep up with the massive amounts of disparate data they received daily. In fact, that data was not being accessed or used at all.

Removing Limitations of the Existing Data Warehouse

Zaloni was able to provide Waste Management with an efficient data lake solution that removed the limitations of the existing data warehouse, enabling time-saving local data processing and providing user-friendly data management and reporting capabilities that were impossible before.

Making Big Data Accessible By All

Today, Waste Management has a totally transformed IT department, one where vast amounts of disparate data have been brought together seamlessly into a single data management platform accessible across the company.

  • 20X the storage capacity at 50% of the cost of the previously planned upgrade
  • 1-year cost savings of $9M and 3-year cost savings of $15M
  • Performance: Increased throughput of 4X, enabling multiple pipelines of data to be processed in parallel
  • Scalability: New nodes can easily be added to the cluster on the fly to improve performance and increase storage capacity
  • Flexibility: By using a Hadoop-based solution, there is no vendor lock-in
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