Hadoop Matters Blog

Big Industries' blog

Apache spark market survey

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Why Do I need a Data Lake?

What is a data lake?

A Data Lake is an enterprise-wide system for storing and analyzing disparate sources of data in their native formats. A Data Lake might combine sensor data, social media data, click-streams, location data, log files, and much more with traditional data from existing RDBMSes. The goal is to break the information silos in an enterprise by bringing all the data into a single place for analysis without the restrictions of schema, security, or authorization. Data Lakes are designed to store vast amounts of data, even petabytes, in local or cloud-based clusters consisting of commodity hardware.

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Data Governance in hadoop environments

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Belgium Cloudera User Group Meetup

Big Industries, as main sponsor of the Belgium Cloudera User Group, organised on Wednesday February 8th, 2017 a Meetup in our offices at Cronos in Kontich with Data Governance in Hadoop Environments as central topic.

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Five common hadoopable problems

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Apache Hadoop has evolved into the standard platform solution for data storage and analysis. Large, successful companies are increasingly adopting Hadoop to perform powerful analysis of their ever-growing business data.

Two key aspects of Hadoop have driven its rapid adoption by companies hungry for improved insights into the data they collect:

  • Hadoop can store data of any type and from any source - inexpensively and at very large scale.
  • Hadoop enables the sophisticated analysis of even very large data sets, easily and quickly.

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Five Common Hadoopable problems: part2

Hadoop gives companies the power to store and analyze information quickly, efficiently and at a lower cost than ever before. It's power and flexibility make it the perfect solution to problems that involve large, complex data sets, and that demand new approaches to processing and analysis.

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Five common hadoopable problems: part3

Hadoop gives companies the power to store and analyze information quickly, efficiently and at a lower cost than ever before. It's power and flexibility make it the perfect solution to problems that involve large, complex data sets, and that demand new approaches to processing and analysis.

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