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Course Name : Big Data Analytics Course Code : ITDB405 Pre Requisite : ITDB303-Fundamentals of Big Data Credit Hours : 3 Passing Grade : C Level: B.Tech No. of Theory Hrs: 1 No. of Practical Hrs : 4 Goal: To adequately prepare the students to offer the best practices in big data analytics and to provide them with the tools, techniques and industry accepted methodologies for data analytics. Objectives: Upon completion of this course, the students should be able to: 1. Investigate the big data analytic techniques for useful business applications. 2. Explore an open source software to perform exploratory Data Analytics 3. Work with a NoSQL document database model Outcomes Methodologies Upon completion of this course, the students should be able to: 1. Explore the fundamental concepts of big data analytics Theory 2. Devise the statistical concepts such as descriptive statistics, probability theory, test Practical of significance etc and their application in business 3. Perform basic analytical techniques such as data exploration, data Practical preparation and data visualization using R 4. Use visualization techniques in R 5. Perform sentiment analysis using R Practical 6. Illustrate the basic concepts of MongoDB such as schema design, data Practical querying, insertion, updating, deletion, etc 7. Use R to analyze a MongoDB database Practical Software & Hardware Tools: RStudio, MongoDB Text Book: 1) Vignesh Prajapati, “Big Data Analytics with R and Hadoop”, Packt Publishing Ltd, 2013 Reference Book: 1) M.Michael, M. Chambers, Ambiga Dhirai, “Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses”,Wiley,2013,ISBN-13: 978- 1118147603 2) Norman Matloff,” The Art of R Programming: A Tour of Statistical Software Design”,No Starch Press,2011,ISBN-13:978-1593273842 3) Rick Copeland, “MongoDB Applied Design Patterns” , O'Reilly Media,2013, Ebook ISBN: 978- 1-4493-4003-2 (Safari online book)
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