Introduction-to-big-data-hadoop-developer

 

Introduction to Big data

To most people, Big Data is a baffling tech term. If you mention Big Data, you could well be subjected to questions such as Is it a tool, or a product? Or Is Big Data only for big businesses? and many more such questions,More info go through Big Data and Hadoop Course

So, what is Big Data?

Today, the size or volume, complexity or variety, and the rate of growth or velocity of the data which organizations handle have reached such unbelievable levels that traditional processing and analytical tools fail to process.

Big Data is ever growing and cannot be determined concerning its size. What was considered as Big eight years ago, is no longer considered so.

For example Nokia, the telecom giant migrated to Hadoop to analyze 100 Terabytes of structured data and more than 500 Terabytes of semi-structured data.

The Hadoop Distributed File System data warehouse stored all the multi-structured data and processed data at a petabyte scale.

According to The Big Data Market report the Big Data market is expected to grow from USD 28.65 Billion in 2016 to USD 66.79 Billion by 2021.

The Big Data Hadoop Certification and Training from Simplilearn will prepare you for the Cloudera CCA175 exam. Of all the Hadoop distributions, Cloudera has the largest partner ecosystems.

This Big Data tutorial will give an overview of the course; its objectives, prerequisites, target audience and the value it will offer to you.

In the next section, we will focus on the benefits of this Hadoop Tutorial.To learn visit:big data hadoop course

Benefits of Hadoop for Organizations

Hadoop is used to overcome challenges of Distributed Systems such as -

• High chances of system failure

• Limited bandwidth

• High programming complexity

In the next section, we will discuss the prerequisites for taking the Big Data tutorial.

Apache Hadoop Prerequisites

There are no prerequisites for learning Apache Hadoop from this Big Data Hadoop tutorial. However, knowledge of Core Java and SQL is beneficial.

Let’s discuss who will benefit from this Big Data tutorial.

Target Audience of the Apache Hadoop Tutorial

The Apache Hadoop Tutorial offered by Simplilearn is ideal for:

• Software Developers and Architects

• Analytics Professionals

• Senior IT professionals

• Testing and Mainframe Professionals

• Data Management Professionals

• Business Intelligence Professionals

• Project Managers

• Aspiring Data Scientists

• Graduates looking to build a career in Big Data Analytics       

  Let us take a look at the lessons covered in this Hadoop Tutorial.

  Leszsons Covered in this Apache Hadoop Tutorial

  There are total sixteen lessons covered in this Apache Hadoop Tutorial. The lessons are listed in the table below.

  Lesson No	Chapter Name	What You’ll Learn
  Lesson 1	Big Data and Hadoop Ecosystem	In this chapter, you will be able to: Understand the concept of Big Data and its challenges Explain what Hadoop is and how it addresses Big Data challenges Describe the Hadoop ecosystem
  Lesson 2	HDFS and YARN	In this chapter, you will be able to: Explain Hadoop Distributed File System (HDFS) Explain HDFS architecture and components Describe YARN and its features Explain YARN architecture
  Lesson 3	MapReduce and Sqoop	In this chapter, you will be able to: Explain MapReduce with examples Explain Sqoop with examples
  Lesson 4	Basics of Hive and Impala	In this chapter, you will be able to: Identify the features of Hive and Impala Understand the methods to interact with Hive and Impala
  Lesson 5	Working with Hive and Impala	In this chapter, you will be able to: Explain metastore Define databases and tables Describe data types in Hive Explain data validation Explain HCatalog and its uses
  Lesson 6	Types of Data Formats	In this chapter, you will be able to: Characterize different types of file formats Explain data serialization
  Lesson 7	Advanced Hive Concept and Data File Partitioning	In this chapter, you will be able to: Improve query performance with concepts of data file partitioning Define Hive Query Language (HiveQL) Define ways in which HiveQL can be extended
  Lesson 8	Apache Flume and HBase	In this chapter, you will be able to: Explain  the meaning, extensibility, and components of Apache Flume Explain the meaning, architecture, and components of HBase
  Lesson 9	Apache Pig	In this chapter, you will be able to: Explain the basics of Apache Pig Explain Apache Pig Architecture and Operations
  Lesson 10	Basics of Apache Spark	In this chapter, you will be able to: Describe the limitations of MapReduce in Hadoop Compare the batch and real-time analytics Explain Spark, it’s architecture, and its advantages Understand Resilient Distributed Dataset Operations Compare Spark with MapReduce Understand functional programming in Spark
  Lesson 11	RDDs in Spark	In this chapter, you will be able to: Create RDDs from files and collections Create RDDs based on whole records List the data types supported by RDD Apply single-RDD and multi-RDD transformations
  Lesson 12	Implementation of Spark Applications	In this chapter, you will be able to: Describe SparkContext and Spark Application Cluster options List the steps to run Spark on Yarn List the steps to execute Spark application Explain dynamic resource allocation Understand the process of configuring a Spark application
  Lesson 13	Spark Parallel Processing	In this chapter, you will be able to: Explain Spark Cluster Explain Spark Partitions
  Lesson 14	Spark RDD Optimization Techniques	In this chapter, you will be able to: Explain the concept of RDD Lineage Describe the features and storage levels of RDD Persistence
  Lesson 15	Spark Algorithm	In this chapter, you will be able to: Explain Spark Algorithm Explain Graph-Parallel System Describe Machine Learning Explain the three C’s of Machine Learning
  Lesson 16	Spark SQL	In this chapter, you will be able to: Identify the features of Spark SQL Explain Spark Streaming and the working of stateful operations Understand transformation and checkpointing in DStreams Describe the architecture and configuration of Zeppelin Identify the importance of Kafka in Spark SQL

                                                                                                                                    
• To learn big data and hadoop complete course visit:   big data hadoop certification