Big Data Analytics Case Study

Data Discovery and preparation for faster insights with Pentaho

Pentaho Case Studies

Description

Metadata driven framework allows you to manage the data from a single point, centralizing various data formats and types, and making it available quickly and easily accessible to all authorized users across your enterprise for the business need.

Maintains an inventory of data assets through the discovery, description and organization of distributed datasets. Enable data stewards, data/business analysts, data consumers to find and understand relevant datasets for the purpose of extracting business value.

Challenge

  • Data is distributed across system and data grows in huge volume, it became difficult and challenging for the data scientist, analyst to discover the datasets available and spread across multiple data sources to share across the enterprise business users for their reporting, analysis and business needs.
  • Operations become slow because of too many systems with point-point integration and should be enabled to talk to each other for sharing data.
  • Users spend more time looking for data than getting value of it and any incremental data required for analysis is costly as data is not democratized. Unable to control who can discover approved or registered data sets.
  • Create dynamic filters for preview and export data to identify problems with the transactional data quickly. Apply filters on selected field values to preview/export data frequently on previously selected values.

Solution

  • Consolidating and streamlining the most commonly used data into a central point with an effective data control system by processing large volumes of data with provision of ready- to -use data immediately.
  • Provides a central metadata repository and portal for datasets, which includes both technical metadata and business glossary. The portal serves as search engine to help locate the datasets of interest which can be created as subset for export, sharing and storing for analytical needs.
  • Helps administrator to control the datasets views by appropriate request approval workflow for the business users and manage the lifecycle of the datasets for users.
  • Data hub lets you find the data you need and use it in the tools you choose. Your data stays where you want it and Data hub helps you discover and work with it where you want, with an intuitive user experience
  • Uncovers tribal knowledge around business terms to enable complete lifecycle management by bringing the business glossary directly where business users are making decision every day with fingertip clarity to drive better decisions.

Benefits

  • Reduced business user dependency on IT teams to create new reports and business insights for better decision. Acts as a semantic layer and lets business users to create their own data sets for self-service reporting and analytics.
  • Restricts data consumers from source changes by eliminating access to source system, still benefit from getting the right data access for usage. Any new views created will be immediately available in Data hub, without any transformation needed.

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