Technuf has in-house expertise to build data analytics related applications using the scientific algorithms for Big Data using open source framework. Heterogeneous data coming from different sources to make business sense out of them is a big challenge. Technuf team used the following methodology to overcome these challenges and built optimized business intelligence applications to provide an executive level dash board view of the organizational bottom line. This critical capability is essential in making intelligent business decisions.
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Handling Big Data

Challenge 1

Conveying big data stored in heterogeneous and different-in-nature data sources (e.g. legacy systems, web and scientific data repositories, stream networks and social networks) into a structured and well interpretable format.

Solution

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Implementation of the ETL layer.

Challenge 2

Managing, processing and transforming extracted structured data repositories in order to derive Business Intelligence (BI) components like diagrams, plots, dashboards for decision making and actionable information.

Solution

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Implementation of the Business Intelligence layer.

Managing Scientific Data

The Technuf Way

Why HADOOP?

HADOOP is the solution

  • It runs MapReduce tasks
  • It uses Hadoop Distributed File System ( HDFS ) for file oriented, distributed data management operations.
  • MapReduce is the core.
  • It is a MAD System!

MAD?

  • Magnetism – capabile of attracting all data source
  • Agility – capabile of adapting to evolving technologies and engines
  • Depth – capable of managing data analytics

HADOOP is MAD!

Why HIVE?

HIVE is the Business Intelligence aspect of analytics

  • Hive is a B.I. system for querying and managing structured data o hop of HADOOP’s HDFS
  • Diagrams, plots, dashboards and many more!
  • HiveQL runs MapReduce jobs immersed into SQL systems.

The Bigger the Better!

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