Big Data Processing

Big Data Processing

The literal meaning of ‘Big Data Processing’ 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’.

This course gives participants the skills and knowledge to better manage analytical efforts. It describes how to get started and what is required to effectively run projects which leverage Big Data analytics

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, we suggest delegates capture a complete understanding of this topic i.e. the full syllabus of big data. So, that next time when delegates take up any course, they are confident that they’ve read every essential topic in big data. This becomes important when Remoik Nigeria as a top training provider in the market and you don’t know, which will cover the maximum of Big Data Analytics syllabus.

Big data Analytics Course Outline

1. Overview of Big Data

• History of big data
• Elements of Big Data
• Related knowledge in the workplace
• Advantages and disadvantages

2. Using Big Data in Businesses

• The application perspective of Big Data
• Using big data in marketing
• Using big data in analytics

3. Technologies for Handling Big Data

• Introduction to Hadoop,
• Functioning of Hadoop,
• Cloud computing (features, advantages, applications) etc

4. Understanding Hadoop Ecosystem

• Hadoop and its ecosystem
• HDFS
• MapReduce
• YARN
• HBase
• Hive
• Pig
• Sqoop
• Zookeeper, Flume, Oozie application.

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

• Detailed framework of MapReduce
• Uses of mapreduce.

6. Understanding Big Data Technology Foundations

• Big data stack
• Data source layer approach
• Ingestion layer approach
• Source layer approach
• Security layer approach
• Visualization layer approach
• Visualization approaches

7. Databases and Data Warehouses
8. Using Hadoop to store data

• HDFS module,
• HBase module
• Strategic ways to store and manage data along with their commands.

9. Learn to Process Data using Map Reduce

• Testing and Debugging Map Reduce Applications
• Learn Hadoop YARN Architechture
• The background of YARN
• Advantages of YARN
• Working with YARN
• Backward compatibility with YARN, YARN Commands, log management etc.

10. Exploring Hive
11. Exploring Pig
12. Exploring Oozie
13. Learn NoSQL Data Management
14. Integrating R and Hadoop and Understanding Hive in Detail

This course covers the complete syllabus of Big Data Technologies. This syllabus should give delegates a comprehensive knowledge of the topics that delegates should cover in this upcoming big data training.