Big Data Analytics Notes PDF Free Download | Syllabus, Books, Questions & Lecture Notes for Big Data Analytics

Big Data Analytics Lecture Notes PDF Download: Choosing a career in the field of Big Data Analytics. Acquiring accurate notes is the most crucial phase of the Data Analyst preparation plan, which also includes a comprehensive study plan, all-important information, and timetable along with Big Data Analytics Study Notes. Students will get information about the latest Reference Books, Syllabus & Important Questions List for Analytics Big Data Notes.

The unstructured Data Analytics Big Notes & Introduction to big data analytics books are the essential study resources, and the reference materials nurture and develop better preparation and assist students in obtaining good grades. Students can refer to the Big Data Analytics Lecture Notes as per the latest updated syllabus from this article.

Graduates can find the Big Data Analytics Class Notes PDFs links and Reference Books from this article and exceed their preparation with the best study resources and obtain better scores in the exams. Share this article with the friends & known students to study well for the big data analytics exams.

Introduction to Big Data Analytics Notes

The science of analyzing raw data to make inferences about information is known as Data Analytics. Many of the techniques and methods of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption.

Big Data analytics technologies and techniques provide a means to take away new information and analyze data sets, which can aid organizations to make informed business resolutions. Big data analytics is a science of analytics, which involves complex applications with components such as statistical algorithms, predictive models, and what-if analysis powered by analytics operations.

Big Data Analytics Lecture Notes PDF and Study Material Free Download

Candidates pursuing Analytics Courses can download Big Data Analytics Lecture Notes PDF and Study Materials updated in this article. Students can increase their preparation with the ideal implementation that helps them secure good grades.

Students can download the notes and study materials and use them as a reference during the revision or preparation process. Application of the Lecture Notes for Big Data Analytics sources of reference will help graduates get a better idea of the concepts and topics and elevate their grade sheet.

The students can use the Big Data Analytics Lecture Notes PDF and Study Materials as a reference. Students pursuing Data Analytics can download PDF notes.

Big Data Analytics Reference Books

Reference books for Big Data Analytics are an essential source of information. It provides necessary information about the topics with essential explanations. Students can develop a solid base when they refer to books that subject experts recommend.

Candidates would understand the topics more precisely if they consult the latest version that includes the updated syllabus. Here is a list of the best-recommended books for Big Data Analytics.

  • Data Warehousing and Multidimensional Databases – Torben Bach Pedersen, Christian S. Jensen, Christian Thomsen, Morgan & Claypool Publishers, 2010
  • Kimball et al., Wiley 1998 – The Data Warehouse Lifecycle Toolkit
  • Hadoop Practice by Alex Holmes Manning publ.
  • Chuck Lam – Hadoop in Action, MANNING Publication.
  • Golfarelli and Rizzi – Modern Principles and Methodologies: Data Warehouse Design, McGraw-Hill, 2009
  • Wiley John Wiley & Sons, Cay Horstmann, INC – Big Java 4th Edition
  • Elżbieta Malinowski, Esteban Zimányi, Springer, 2008 – Advanced-Data Warehouse Design: From Spatial to Conventional and Temporal Applications,
  • 2nd Ed., Kimball and Ross, Wiley, 2002 – The Data Warehouse Toolkit
  • Tom Whites, 3rd Edition, O’Reilly – Hadoop: The Definitive Guide.
  • Roman B.Melnyk, Bruce Brown, Dirk deRoos, Paul C.Zikopoulos, Rafael Coss – The Hadoop for Dummies.
  • Hadoop MapReduce Cookbook, Srinath Perera, Thilina Gunarathne

Big Data Analytics Curriculum & Syllabus

The best way to commence your preparation for the Big Data Analytics Courses is to understand the syllabus and the topics of the subject. Keeping in mind every student’s requirements, we have presented a comprehensive view of the Big Data Analytics Syllabus.

The Syllabus of Big Data Analytics aims to present the students with a brief idea of what to study, the unit-wise breakup of the topics, and how to allot time to each subject.

Students must ensure to cover all the topics and concepts before attempting the exams to ensure that the paper is easy and stress-free at the time of the exam. Graduates must make sure that they are aware of the course Syllabus to prevent unnecessary waste of time on unnecessary topics.

Here is an updated list of topics of the Big Data Analytics Course Syllabus-

Unit I

Data Structures in Java

  • Linked List
  • Stacks
  • Queues
  • Sets
  • Maps


  • Generic classes and Type parameters
  •  Implementing Generic Types
  • Generic Methods
  • Wrapper Classes
  • Concept of Serialization
Unit II

Working with Big Data

  • Google File System
  • Hadoop Distributed File System (HDFS) – Building blocks of Hadoop (Namenode Datanode, Secondary Namenode, Job Tracker, Task Tracker)
  • Configuring and Introducing Hadoop cluster (Local,Fully Distributed mode,  Pseudo-distributed mode)
  • Configuring XML files
Unit III

Writing Map Reduce Programs

  • A Weather Dataset
  • (Old and New) Hadoop API understanding for MapReduce Framework

Basic programs of Hadoop MapReduce:

  • Driver code
  • Mapper code
  • Reducer code
  • Record Reader
  • Combiner
  • Partitioner
Unit IV

Hadoop I/O

  • The Writable Interface
  • Writable Comparable
  • Comparators

Writable Classes

  • Writable wrappers for Java primitives
  • Text
  • Bytes Writable
  • Null Writable
  • Object Writable and Generic Writable
  • Writable collections

Implementing a Custom Writable:

  • Implementing a Raw Comparator for speed
  • Custom comparators
Unit V


  • Hadoop Programming Made Easier Admiring the Pig Architecture
  • Going with the Pig Latin Application Flow,
  • Working through the ABCs of Pig Latin,
  • Evaluating Distributed and  Local Modes of Running Pig Scripts
  • Checking out the Pig Script Interfaces
  •  Scripting with Pig Latin
Unit VI

Applying Structure to Hadoop Data with Hive

  • Saying Hello to Hive
  •  Seeing How the Hive is Put Together
  • Getting Started with Apache Hive
  • Examining the Hive Clients
  • Working with Hive Data Types
  • Creating and Managing Databases and Tables
  • Seeing How the Hive Data Manipulation Language Works
  • Querying and Analyzing Data.

Big Data Analytics Important Questions List

Candidates pursuing Big Data Analytics can refer to the list of all the essential questions stated below for the Big Data Analytics Notes. All the assigned questions are aimed to help the aspirants to excel in the examination. Here is a list of some essential questions that will help the students to have a better understanding of the subject.

  1. Explain in brief about Commands of PIG?
  2. Define Wrapper Class? Describe in brief about writable wrappers for java primitives.
  3. How Hadoop uses the Scale-out feature to develop the performance? Give an explanation with examples.
  4. Differentiate between class linked list functionalities and Array List.
  5. Explain with example about the implementation of the map-reduce concept.
  6. In what mode does a Hadoop can run?
  7. Explain in brief about API for the Map-reduce framework.
  8. What is Generic writable and Object writable?
  9. Explain and describe in brief about the construction blocks of Hadoop?
  10. Explain in brief about running a pig script in distributed mode and local.

Frequently Asked Questions on Big Data Analytics Notes PDF Download

Question 1.

Why is Big Data Analytics imperative for business enterprises and industries?

Answer :

Big Data analytics is essential for business enterprises and industries to understand obstacles sustaining an organization and to explore data in meaningful ways. Big Data analytics interprets, organizes, structures, and presents the data into beneficial information that offers context to the data.

Question 2.

What are the types of Big Data Analytics?

Answer :

There are four types of big Data Analytics: Prescriptive, Predictive, Diagnostic and Descriptive

Question 3.

Name a few of the big data software and tools?

Answer :

Some of the Big Data Tools and Software are Apache Storm, Hadoop, MongoDB, Quoble, Cassandra, CouchDB, HPCC, and Statwing.

Question 4.

How does Big Data Analytics operate?

Answer :

Big data analytics is the science of analyzing big sets of data through different processes and tools to find out unique hidden correlations, patterns, meaningful trends, and other insights for building data-driven judgments in the pursuit of better outcomes.


The Big Data Analytics Lecture Notes and Study Materials written above are aimed to assist the students at the time of exam preparations. The notes for big data analytics are reliable and have authoritative references focused to help students and improve their knowledge and understanding of the subject during the time of preparation for the exam. Students can refer and practice from the provided notes for big data analytics, analytics big data curriculum, and important questions from this article.