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  1. Introduction to introduction to “Big Data Analytics: Big Data, Scalability and Parallel Processing, Designing Data Architecture, Data Sources, Quality, Pre-Processing and Storing, Data Storage and Analysis, Big Data Analytics Applications and Case Studies.”

  2. Understand fundamentals of Big Data analytics. Investigate Hadoop framework and Hadoop Distributed File system. Illustrate the concepts of NoSQL using MongoDB and Cassandra for Big Data. Demonstrate the MapReduce programming model to process the big data along with Hadoop tools. Use Machine Learning algorithms for real world big data.

  3. Introduction to Big Data Analytics: Big Data, Scalability and Parallel Processing, Designing Data Architecture, Data Sources, Quality, Pre-Processing and Storing, Data Storage and Analysis, Big Data Analytics Applications and Case Studies.

  4. Introduction to Big Data Analytics: Big Data, Scalability and Parallel Processing, Designing Data Architecture, Data Sources, Quality, Pre-Processing and Storing, Data Storage and Analysis, Big Data Analytics Applications and Case Studies.

  5. Test. 18CS72- Big Data Analytics. Lecture Notes & Text Book. CopyRight@2016 Dr. Harish Kumar B T, Associate Professor, Dept of CSE, Bangalore Institute of Technology, Bengaluru-04. Google...

  6. Jan 24, 2023 · Understand fundamentals of Big Data analytics. Investigate Hadoop framework and Hadoop Distributed File system. Illustrate the concepts of NoSQL using MongoDB and Cassandra for Big Data. Demonstrate the MapReduce programming model to process the big data along with Hadoop tools.

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  8. Download VTU CBCS notes of Big Data Analytics 17CS82 – 15CS82 VTU CBCS Notes for 8th-semester computer science and engineering, VTU Belagavi. Solution Manual to Big Data Analytics 17CS82 VTU CBCS Question Bank. Module 1 – Hadoop Distributed File System and Map Reduce Programming.