Big data Analytics Course Syllabus (Content/ Outline) : The literal meaning of ‘Big Data’ seems to have developed a myopic understanding in the minds of aspiring big data enthusiasts. When asked people about Big Data, all they know is, ‘It is referred to as massive collection of data which cannot be used for computations unless supplied operated with some unconventional ways’.

Big Data, is not just about, storing and extracting data, but much more than that. Big Data, itself comprises of so many technologies that it is difficult to recall which one to start learning with. No really! Some of the technologies big data consists of is Hadoop, MapReduce, Apache, Pig, Hive, Flume, Sqoop, Zookeeper, Oozie, Spark, Cassandra, Mongo DB and what not!

Companies are desperately in search of skilled big data analysts. Considering the fact, that data is being collected and stored at a velocity faster than ever, the urgency of such skilled professionals increases further. Before delving into big data, I’d suggest you capture a complete understanding of this topic i.e. the full syllabus of big data. So, that next time when you take up any course, you are confident that you’ve read every essential topic in big data. This becomes important when there are large numbers of training providers in the market and you don’t know, which one has covered the maximum of syllabus.

Talking about training courses, the syllabus may vary depending on the course level (beginners or advanced). In here, I intend to provide a complete syllabus of mastering big data.

While searching for big data resources, I realized there isn’t a standard syllabus available which is globally recognized. The sequence may differ, depending on the course structure of training provider.

With the syllabus mentioned in this article, you should get a brief idea of all big data related technologies and what you should expect from you training provider. Recently, I read of ‘Black Book’ of Big Data and gathered some useful information parallel with internet search. Here’s the syllabus, covering beginners to advanced level concepts of Big Data:

1. Overview of Big Data

This includes topics such as history of big data, its elements, career related knowledge, advantages, disadvantages and similar topics.

2. Using Big Data in Businesses

This module should focus on the application perspective of Big Data covering topics such as using big data in marketing, analytics, retail, hospitality, consumer good, defense etc.

3. Technologies for Handling Big Data

Big Data is primarily characterized by Hadoop. This module cover topics such as Introduction to Hadoop, functioning of Hadoop, Cloud computing (features, advantages, applications) etc

4. Understanding Hadoop Ecosystem

This includes learning about Hadoop and its ecosystem which includes HDFS, MapReduce, YARN, HBase, Hive, Pig, Sqoop, Zookeeper, Flume, Oozie etc.

5. Dig Deep to understand the fundamental of MapReduce and HBase

This module should cover the entire framework of MapReduce and uses of mapreduce.

6. Understanding Big Data Technology Foundations

This module covers the big data stack i.e. data source layer, ingestion layer, source layer, security layer, visualization layer, visualization approaches etc.

7. Databases and Data Warehouses

This module should cover all about databases, polygot persistence and their related introductory knowledge

8. Using Hadoop to store data

This includes an entire module of HDFS, HBase and their respective ways to store and manage data along with their commands.

9. Learn to Process Data using Map Reduce

This emphasizes on developing simple mapreduce framework and the concepts applied to it.

10. Testing and Debugging Map Reduce Applications

After the applications are developed, the next step is to test and debug it. This modules imparts this knowledge.

11. Learn Hadoop YARN Architechture

This module covers the background of YARN, advantages of YARN, working with YARN, backward compatibility with YARN, YARN Commands, log management etc.

12. Exploring Hive

This modules introduces you with all the necessary knowledge of Hive.

13. Exploring Pig

This modules introduces you with all the necessary knowledge of PIG.

14. Exploring Oozie

This modules introduces you with all the necessary knowledge of Oozie.

15. Learn NoSQL Data Management

This modules covers all about NoSQL including document databases, relationships, graph databases, schema less databases, CAP Theorem etc.

16. Integrating R and Hadoop and Understanding Hive in Detail

This module introduces you to RHadoop, ways to do text mining and related knowledge.

In this article, I’ve covered the complete syllabus of Big Data Technologies. This syllabus should give you a comprehensive overview of the topics that you should cover in your upcoming big data training. If you realize, that your training doesn’t have any of the mentioned module in the syllabus, I’d recommend you to get in touch with the course administrator and get this thing sorted.