Multiplan

About This Customer

Multiplan
The most comprehensive provider of healthcare cost management solutions

Press Releases

News

Traditional RDBMS analytics can become very complicated and quite frankly, ugly, when trying to analyze semi or unstructured data. While NoSQL data stores like MongoDB can be great places to land these types of data, traditional analytics solutions still create the need to offload data to traditional reporting databases. In Pentaho 5.1, the Pentaho platform is meeting market needs, allowing users to directly analyze data in MongoDB. We have seen more accurate results with new analyses and are no longer constrained by having to only pull part of our data. We can now look across a more full set of data and govern our system of record to gain greater insights.
Chris Palm Lead Software Architecture Engineer, Multiplan

Use Case Overview

Business Challenges

  • Implement complete, end-to-end business analytics solution with strong ETL capabilities to build and govern their NoSQL Store
  • Develop Big Data integration and analytical tools that can connect to semi and unstructured data in its entirety
  • Utilize full analytics suite with a high degree of functionality and scalability

Pentaho Solution

  • Pentaho Data Integration with MongoDB to extract, transform and load portal data
  • Pentaho Analyzer to govern and analyze data inside of MongoDB without having to offload to traditional relational databases
  • Pentaho Business Analytics to create dashboards and reports by blending Big Data with traditional operations and web server data

Value Added

  • ETL process that assures data governance, quality and measure validation, result in more accurate analyses
  • Improved user view and insights that lower operational costs while improving user satisfaction
  • Fast delivery time to market with Pentaho Enterprise Services

Why Pentaho

  • Low total cost of ownership
  • High degree of functionality and scalability
  • Superior enterprise support and services
  • Analytics directly against Big Data