Big Data Analytics
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Big Data Analytics Syllabus — Unit-wise Content
The official GTU curriculum for Big Data Analytics (subject code 3712313) as prescribed for ITAC · Semester 1 divides the course into 4 units, covering 46 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (3712313)Unit 1 What is big data, why big data, convergence of key trends, unstructured
- industry examples of big data
- web analytics
- big data and marketing
- fraud and big data
- risk and big data
- credit risk management
- big data and algorithmic trading
- big data and healthcare
- big data in medicine
- advertising and big data
- big data technologies
- introduction to Hadoop
- open source technologies
- cloud and big data
- mobile business intelligence
- Crowd sourcing analytics
- inter and trans firewall analytics
Unit 2 Introduction to NoSQL, aggregate data models, aggregates, key-value and
- document data models
- graph databases
- schemaless databases
- materialized views
- distribution models
- master-slave replication
- peer peer replication
- sharding and replication
- sharding in MongoDB
- relaxing consistency
- version stamps
- map- reduce
- partitioning and combining
- composing map-reduce calculations
Unit 3 Data format, analyzing data with Hadoop, scaling out, Hadoop streaming,
- Hadoop pipes
- design of Hadoop distributed file system (HDFS)
- HDFS concepts
- Java interface
- data flow
- data integrity
- file-based data structures
Unit 4 MapReduce workflows, unit tests with MRUnit, test data and local tests,
- anatomy of MapReduce job run, classic Map-reduce
- failures in classic Map-reduce and YARN
- job scheduling
- shuffle and sort
- task execution
- MapReduce types
- input formats
- output formats
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