MCA E3009
Big Data Analytics
Notes are on their way.
For now, use the syllabus outline to see what this subject covers.
Syllabus topics
Introduction to Big Data Platform – Challenges of Conventional Systems - Intelligent data analysis – Nature of Data - Analytic Processes and Tools - Analysis vs Reporting. [Q-2]
Notes will be added here.
Syllabus: supplied PDF, page 30.
Syllabus topics
Introduction To Streams Concepts – Stream Data Model and Architecture - Stream Computing - Sampling Data in a Stream – Filtering Streams – Counting Distinct Elements in a Stream – Estimating Moments – Counting Oneness in a Window – Decaying Window - Real time Analytics Platform(RTAP) Applications. [Q-2]
Notes will be added here.
Syllabus: supplied PDF, page 30.
Syllabus topics
Real Time Sentiment Analysis- Stock Market Predictions. [Q-1]
Notes will be added here.
Syllabus: supplied PDF, page 30.
Syllabus topics
History of Hadoop - the Hadoop Distributed File System – Components of Hadoop Analysing the Data with Hadoop- Scaling Out- Hadoop Streaming. [Q-2]
Notes will be added here.
Syllabus: supplied PDF, page 30.
Syllabus topics
Developing a Map Reduce Application -How Map Reduce Works -Anatomy of a Map Reduce Job run - Failures-Job Scheduling -Shuffle and Sort – Task execution - Map R educe Types and Formats - Map Reduce Features Hadoop environment. [Q-1]
Notes will be added here.
Syllabus: supplied PDF, page 30.
Check your university’s syllabus for the topics covered in your exams.