JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

BIG DATA ANALYTICS LAB

M.Tech I Year II Semester (R22)

Course Objectives:

  • 1. The purpose of this course is to provide the students with the knowledge of Big data Analytics principles and techniques.
  • 2. This course is also designed to give an exposure of the frontiers of Big data Analytics

Course Outcomes:

  • 1. Use Excel as a Analytical tool and visualization tool.
  • 2. Ability to program using HADOOP and Map reduce
  • 3. Ability to perform data analytics using ML in R.
  • 4. Use cassandra to perform social media analytics

List of Experiments:

  • 1. Implement a simple map-reduce job that builds an inverted index on the set of input documents (Hadoop)
  • 2. Process big data in HBase
  • 3. Store and retrieve data in Pig
  • 4. Perform Social media analysis using cassandra
  • 5. Buyer event analytics using Cassandra on suitable product sales data.
  • 6. Using Power Pivot (Excel) Perform the following on any dataset
  • a) Big Data Analytics
  • b) Big Data Charting
  • 7. Use R-Project to carry out statistical analysis of big data
  • 8. Use R-Project for data visualization of social media data

TEXT BOOKS:

  • 1. Big Data Analytics, SeemaAcharya, Subhashini Chellappan, Wiley 2015.
  • 2. Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today’s Business, Michael Minelli, Michehe Chambers, 1st Edition, Ambiga Dhiraj, Wiely CIO Series, 2013.
  • 3. Hadoop: The Definitive Guide, Tom White, 3rd Edition, O‟Reilly Media, 2012.
  • 4. Big Data Analytics: Disruptive Technologies for Changing the Game, Arvind Sathi, 1st Edition, IBM Corporation, 2012.

REFERENCES:

  • 1. Big Data and Business Analytics, Jay Liebowitz, Auerbach Publications, CRC press (2013)
  • 2. Using R to Unlock the Value of Big Data: Big Data Analytics with Oracle R Enterprise and Oracle R Connector for Hadoop, Tom Plunkett, Mark Hornick, McGraw-Hill/Osborne Media (2013), Oracle press.
  • 3. Professional Hadoop Solutions, Boris lublinsky, Kevin t. Smith, Alexey Yakubovich, Wiley, ISBN: 9788126551071, 2015.
  • 4. Understanding Big data, Chris Eaton, Dirk deroos et al., McGraw Hill, 2012.
  • 5. Intelligent Data Analysis, Michael Berthold, David J. Hand, Springer, 2007.
  • 6. Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics, Bill Franks, 1st Edition, Wiley and SAS Business Series, 2012.

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