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Home / Syllabus / B.Sc. (Data Science) / TY BSc Data Science / Semester 5 / Data Engineering

B.Sc. (Data Science) Data Engineering Syllabus - Mumbai University

This is the TY BSc Data Science syllabus under NEP 2020, in force from the academic year 2026-27. The University still sets the earlier Choice Based papers alongside it for ATKT candidates, so check which scheme your exam form names before you revise.

Data Engineering Syllabus.pdf
Major · Semester 5 · TY BSc Data Science · 2 credits · 50 marks

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Syllabus for Data Engineering

Major · Semester 5 · TY BSc Data Science · 2 credits · 50 marks

Module I: Foundations, Data Architecture, and Data Generation

  • 1. Foundations and Building Blocks: Data Engineering Overview What is Data Engineering? Roles and Responsibilities of a Data Engineer Data Engineering Skills and Activities Data Engineers in an Organization 2. Data Engineering Lifecycle: Concept of Data Engineering Lifecycle, Stages of the Data Engineering Lifecycle, Major Undercurrents Across the Lifecycle, Importance of Data Pipelines and Workflow Management 3. Designing Good Data Architecture: Definition of Data Architecture, Principles of Good Data Architecture, Major Architecture Concepts, Types and Examples of Data Architecture. Data Warehouse, Data Lake, Data Lakehouse, Data Mesh Stakeholders in Designing Data Architecture 4. Choosing Technologies in Data Engineering: Factors for Technology Selection, Team Size and Capabilities. Speed to Market, Interoperability, Cost Optimization and Business Value, Build vs Buy, Monolithic vs Modular Architecture. Serverless vs Server-based Systems. Optimization and Performance Considerations 5. Data Generation in Source Systems: Sources of Data. Data Creation Methods, Source System Concepts, Practical Details of Source Systems, Collaboration with Data Producers

Module II: Data Processing, Analytics Serving, and Advanced Concepts

  • 1. Data Ingestion Definition and Importance of Data Ingestion, Key Engineering Considerations, Batch Data Ingestion, Streaming and Message-based Ingestion, Methods and Tools for Data Ingestion, Collaboration with Data Platform Teams 2. Queries, Data Modelling, and Transformation Querying Data, Data Modelling Techniques, Relational Modelling, Dimensional Modelling, Data Transformation Processes, ETL and ELT Pipelines 3. Serving Data for Analytics and Machine Learning Serving Data for Business Analytics, Data for Machine Learning Workflows, Role of Data Engineers in ML Pipelines, Reverse ETL Concepts, Data Delivery Methods, 4. Security and Privacy Data Security Concepts, Privacy and Compliance. People, Processes, and Technology in Data Protection 5. Advanced Data Engineering Concepts Serialization Formats, Columnar and Hybrid Serialization, Database Storage Engines. Data Compression Techniques:gzip,bzip2,Snappy 10 Text Books 1. Fundamentals of Data Engineering, Joe Reis, Matt Housley, O'Reilly Media, 1st, 2022 2. Learning Spark: Lightning-Fast Data Analytics, Jules S. Damji, Brooke Wenig, O'Reilly Media, 2nd, 2020 11 Reference Books 1. Kafka: The Definitive Guide, Neha Narkhede, Gwen Shapira, Todd Palino, O'Reilly Media, 1st, 2017 2. Data Pipelines Pocket Reference, James Densmore, O'Reilly Media, 1st,2021 12 Internal Continuous Assessment: 40% Semester End Examination: 60% 13 Continuous Evaluation through: External examination (30 Marks)- Class Test 1 of 15 marks (Duration- 1Hr) Class Test 2 of 15 marks Average of the two: 15 marks Quizzes/Presentation/Assignments: 5 marks Total : 20 marks 14 Format of Question Paper: (Semester End Examination: 30 Marks. Duration: 1 Hr ) Q1: Attempt any three (out of five/six) from Module 1 (15 Marks) Q2: Attempt any three (out of five/six) from Module 1 (15 Marks)

Text Books

  • 1 Fundamentals of Data Engineering, Joe Reis, Matt Housley, O'Reilly Media, 1st, 2022
  • 2 Learning Spark: Lightning-Fast Data Analytics, Jules S. Damji, Brooke Wenig, O'Reilly Media, 2nd, 2020
  • 1 Kafka: The Definitive Guide, Neha Narkhede, Gwen Shapira, Todd Palino, O'Reilly Media, 1st, 2017
  • 2 Data Pipelines Pocket Reference, James Densmore, O'Reilly Media, 1st,2021

Reproduced from the University of Mumbai syllabus for B.Sc. (Data Science) under NEP 2020, in force from the academic year 2026-27. Wording is as printed in that syllabus. Module numbering is as printed there too.

The complete syllabus

This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.

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