Tutorial and A Course which will help you to clarify the existence of Hadoop for Big Data problem

By ridhigrg |Email | May 24, 2019 | 3309 Views

If you want to know that what is Big data, what is Hadoop and how people came to know about Hadoop,  this Hadoop tutorial will teach you the exact meaning of it. You will also get to know various components of Hadoop and an explanation on Hadoop use case.

We can see that a lot of data is being generated nowadays and it is difficult to store this huge amount of data and we can even process and analyze the data through these traditional methods. So to overcome this situation Hadoop came into existence for Big Data problem. So Hadoop is a framework which is used to manage the storage of big data in a proper way and see that it can be parallelly processed. 

Some major topics which will be discussed in this Tutorial are: 
  • You will see the rise of Big data. From where it has come.
  • You will get to know the exact meaning of big data.
  • You will see what are the challenges faced by big data.
  • How Hadoop came into existence as a solution to big data. 
  • What is Hadoop?
  • Some major components of Hadoop
  • Where Hadoop is used. 

To get to know more about Hadoop you have a course which is provided by Simplilearn's, that is Big Data Hadoop training course which helps you to master the concepts of Hadoop Framework and through which you are also trained for the certification of Cloudera's Big Data. With the online Hadoop training, you'll learn how the components of the Hadoop ecosystem, such as Hadoop 3.4, Yarn, MapReduce, HDFS, Pig, Impala, HBase, Flume, Apache Spark, etc. fit in with the Big Data processing lifecycle. Implement real-life projects in banking, telecommunication, social media, insurance, and e-commerce on CloudLab.

Why Learn Big Data Hadoop with Certification?
The world is getting increasingly digital, and this means big data is here to stay. In fact, the importance of big data and data analytics is going to continue growing in the coming years. Choosing a career in the field of big data and analytics might just be the type of role that you have been trying to find to meet your career expectations. Professionals who are working in this field can expect an impressive salary, with the median salary for data scientists being $116,000. Even those who are at the entry level will find high salaries, with average earnings of $92,000. As more and more companies realize the need for specialists in big data and analytics, the number of these jobs will continue to grow. Close to 80% of data scientists say there is currently a shortage of professionals working in the field.

What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.

What are the course objectives?
This course will enable you to:
1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames

Who should take up this Big Data and Hadoop Certification Training Course?
Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals:
1. Software Developers and Architects
2. Analytics Professionals
3. Senior IT professionals
4. Testing and Mainframe professionals
5. Data Management Professionals
6. Business Intelligence Professionals
7. Project Managers
8. Aspiring Data Scientists

Source: HOB