BITM Big Data and Analytics

bitmsemester 8Elective

The course covers different concepts of big data technologies, including an overview and challenges of big data, big data analytics, Hadoop and NoSQL systems, data lakes, and big data applications.

semester photo

Chapter Wise Notes Question Banks Syllabus Chapter Wise Questions Viva Practical

Unit 1:Overview of Big Data

Introduction. Types of Data. Evolution of Big Data. Big Data Characteristics. Big Data versus Data Warehouse. Advantages and Disadvantages of Big Data. Obstacles in Utilizing Big Data. Impact of Big Data.

Unit 2:Challenges of Big Data

Introduction. Big Data Integration. Storing Big Data. Maintaining Data Quality. Analysis of Big Data. Security and Privacy Management. Accessing and Sharing.

Unit 3:Big Data Analytics

Introduction. Applications of Big Data Analytics. Types of Big Data Analytics. Comparison of Data Analytics Stages.

Unit 4:Hadoop and NoSQL Databases

Introduction to Hadoop. Components of Hadoop Ecosystem. Data Storage Component. Data Processing Component. Data Access Component. Data Management Component. Apache Spark. Introduction to NoSQL Databases. Types of NoSQL Databases. Key-Value, Column-Oriented, Document Oriented and Graph-Based Databases. BASE Model. Advantages and Disadvantages of NoSQL Databases.

Unit 5:Data Lakes

Introduction. Data Lake Architecture. Usage and Challenges. Advantages and Disadvantages. Lake House. Difference between Data Warehouse, Data Lakes, and Lake Houses. Best Practices.

Unit 6:Big Data Applications

Big Data for Healthcare. Big Data Analytics of Fraud Detection. Big Data Analytics of Social Media. Novel Applications.