Hadoop Matters Blog

Eleven years after its founding, Cloudera fulfilled its name in a big way with the launch of Cloudera Data Platform (CDP), its new flagship data platform that allows customers to securely manage and govern their data while deploying analytic and AI applications in a platform-as-a-service (PaaS) approach on the cloud.

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In recent years, the cloud has offered a scalable, versatile, and efficient environment for big data workloads. In this blogpost we explore how companies are deploying Cloudera Enterprise for running production Hadoop workloads - ETL, BI, advanced analytics, Spark - on Microsoft Azure, with enterprise-class data security and governance.

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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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