Dataware for data-driven transformation

Self-Service Data Exploration on Semi-Structured Data

New analytical insights are the fuel for future business growth and ideation of new business opportunities. Whether you’re a line of business manager, IT manager or analytics leader, self-service analytics is a key business initiative. The data driving these new analytics is increasingly semi-structured in nature, such as JSON and different types of files being stored in Hadoop and NoSQL systems.

The MapR Data Exploration Quick Start Solution enables business analysts and data analysts to conduct analyses on larger and more diverse sets of data faster and formulate new hypothesis quicker than before. IT organizations can fulfill their promise of delivering analyses to business users faster and more efficiently.

Key business benefits include:

  • Rapid time-to-value: Business analysts and data analysts can query any dataset—without waiting for data modeling and schema development.
  • Efficiency with easy governance: IT can avoid unnecessary ETL cycles and schema maintenance activities and still ensure governance.
  • Reuse existing investments: Organizations can leverage the existing SQL talent base as well as their investments in BI and visualization tools.

What's Included?

software

Software

Trial subscription of MapR Converged Data Platform Enterprise Premier for the duration of the quick-start.

professional services

Professional Services

3-10 weeks of engagement with MapR Professional Services Engineers and Data Scientists (Duration varies based upon the particular quick start.)

certification

Certification

2 Academy Pro Subscriptions including Certification Exams.

The solution template in the Quick Start Solution includes workflows to ingest, process and visualize data stored in Hadoop using Apache Drill. Installation and configuration of the MapR cluster is included within the scope of this Quick Start Solution.

Key solution capabilities

  • Data Ingestion: Workflows to ingest the various data sources to be brought into the cluster.
  • Data Aggregation: Identification and implementation of business logic to process and aggregate data that has been ingested.
  • Data Access: Query data via ad-hoc queries and visualizations with a BI tool of choice.

Self-Service Data Exploration Template

To learn more, read the Data Exploration Quick Start Solution Solution Brief.

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SOLUTION BRIEF
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