Unit-I                                                                  

What is Analytics?- Descriptive Analytics– Diagnostic Analytics- Predictive Analytics- Prescriptive Analytics- What is Big Data?– –  Characteristics of Big Data – Volume-Velocity-Variety- Veracity-  Value Domain Specific Examples of Big Data – Web – Financial – Healthcare – Internet of Things – Environment – Logistics & Transportation – Industry – Retail

Unit-II

                Analytics Flow for Big Data – Data Collection- Data Preparation- Analysis Types- Analysis Modes- Visualizations- Big Data Stack -: Raw Data Sources- Data Access Connectors- Data Storage- Batch Analytics-  Real-time Analytics – Interactive Querying- Serving Databases, Web & Visualization Frameworks.

Unit-III

                Big Data Patterns- Analytics Architecture Components & Design Styles – Load Leveling with Queues- Load Balancing with Multiple Consumers- Leader Election- Sharding- Consistency, Availability & Partition Tolerance (CAP)- Bloom Filter- Materialized Views- Lambda Architecture- Scheduler-Agent-Supervisor- Pipes & Filters – Web Service – Consensus in Distributed Systems – MapReduce Patterns .

 Unit-IV:

NoSQL- Key-Value Databases- Amazon DynamoDB – Document Databases ᎓ MongoDB- Column Family Databases ᎓ Hbase – Graph Databases – Neo4j- Data Acquisition- Data Acquisition Considerations- Source Type- Velocity – Ingestion Mechanism. Publish – Subscribe Messaging Frameworks- Apache Kafka- Amazon Kinesis

Unit-V: