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Difference between Pig and Hive-The Two Key Components of Hadoop Ecosystem

ProjectPro

Generally data to be stored in the database is categorized into 3 types namely Structured Data, Semi Structured Data and Unstructured Data. PIG Hadoop Pig Hadoop was developed by Yahoo in the year 2006 so that they can have an ad-hoc method for creating and executing MapReduce jobs on huge data sets.

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Big Data Analytics: How It Works, Tools, and Real-Life Applications

AltexSoft

A single car connected to the Internet with a telematics device plugged in generates and transmits 25 gigabytes of data hourly at a near-constant velocity. And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. NoSQL databases. Apache Hadoop.

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The Good and the Bad of Hadoop Big Data Framework

AltexSoft

Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. a suitable technology to implement data lake architecture. As a result, today we have a huge ecosystem of interoperable instruments addressing various challenges of Big Data.

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Google BigQuery: A Game-Changing Data Warehousing Solution

ProjectPro

4) Business Intelligence A quick, in-memory analysis service called BigQuery BI Engine enables users to create dynamic, rich dashboards and reports without sacrificing performance, scalability, security, or the timeliness of the data. Google's Dremel is an interactive ad-hoc query solution for analyzing read-only hierarchical data.

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