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Big Data Analytics using Hadoop
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Big Data Analytics using Hadoop Training in Chicago-IL, United States

Gain knowledge of Big Data Analytics concepts and tools along with Reinforce concepts by working on a Big Data Analytics Project

Online & Classroom | Latest & Accredited Courseware | 100+ hrs of assignments

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Modes of Delivery

Key Features

Instructor Led Live online training
30 Hours immersive Hands-on training sessions
High Quality training from an industry expert
Downloadable e-book
Project-based learning

Description

Understand the A to Z of Big Data and Hadoop Analytics with our comprehensive Hadoop online training program. Using hands-on work examples you will learn to extract real time information with Hadoop MapReduce and the various tools and techniques such as HDFS, Pig, Hive, HBase, Sqoop, Oozie, and Flume.

Here’s what you will learn!

  • Gain in depth knowledge of Big Data Analytics concepts and tools
  • Process large data sets using the various tools of Big Data and extract relevant information from seemingly disparate sources
  • Query databases using Hadoop MapReduce to create scalable, flexible and cost effective solutions
  • Perform data analytics using Pig, Hive and Sqoop
  • Implement Integration with HBase and MapReduce
  • Schedule jobs using Oozie
  • Execute Flume jobs
  • Understand the use of best practices for Hadoop development
  • Reinforce concepts by working on a Big Data Analytics Project

Is this course right for you?

Architects and developers who design Hadoop-based solutions, data analysts, BI analysts, BI Developers, SAS Developers, consultants, Java software engineers and software developers working on Hadoop environments will find this course beneficial.

Why should you learn Big Data Analytics?

Examining large amounts of data called Big Data reveals patterns of trends, associations, and customer preferences and helps organizations take business decisions that will align them with market and customer need and increase profitability. This ultimately leads to business success, which is why Big Data Analytics and Hadoop is among the fastest growing technologies to be adopted by organizations across the world.Hadoop is an architecture that is highly scalable and flexible and has uses in such varied industries as telecommunications, retail, security, manufacturing, banking, media and healthcare. Big Data and Hadoop specialists who can leverage the Hadoop platform to deal with terabyte scale of data, are much sought after.Zeolearn’s workshop not only teaches candidates the theoretical aspects of the subject but also gives hands-on practice on using this technology. 

Pre-requisites

  • Basic programming knowledge is desired though not a prerequisite for attending this course
  • Knowledge of Microsoft Windows platform

 

Curriculum

  • What is Big Data?
  • Characteristics of big data
  • Big Data challenges
  • Popular tools used with big data For storing, processing, analysing & visualization
  • Where Hadoop fits in?
  • Traditional data analytic's architecture versus Hadoop
  • What is Hadoop?
  • History of Hadoop
  • Hadoop’s key characteristics
  • Hadoop usage
  • Hadoop eco-system & core components
  • HDFS architecture & overview of MRv1
  • HDFS daemons
  • Files and blocks
  • Anatomy of a file write & read
  • Replication & rack awareness
  • What is YARN?
  • MR1 v MR2
  • YARN architecture
  • HDFS Federation
  • YARN Deamons
  • YARN Job execution workflow
  • Authentication and high availability in Hadoop
  • Hortonworks sandbox installation & configuration
  • Hadoop Configuration files
  • Working with Hadoop services using Ambari
  • Hadoop deamons
  • Browsing Hadoop UI consoles
  • Basic Hadoop Shell commands
  • Eclipse & winscp installation & configurations on VM

  • Running a MapReduce application in MR2
  • MapReduce Framework on YARN
  • Fault tolerance in YARN
  • Map, Reduce & Shuffle phases
  • Understanding Mapper, Reducer & Driver classes
  • Writing Map Reduce WordCount program
  • Executing & monitoring a Map Reduce  job
  • Use case - Sales calculation using M/R
  • Background of Pig
  • Pig architecture
  • Pig Latin basics
  • Pig execution modes
  • Pig processing – loading and transforming data
  • Pig built-in functions
  • Filtering, grouping, sorting data
  • Relational join operators
  • Pig Scripting
  • Pig UDF's 
  • Background of Hive
  • Hive architecture
  • Hive Query Language
  • Derby to MySQL  database
  • Managed & external tables
  • Data processing – loading data into tables
  • Hive Query Language
  • Using Hive built-in functions
  • Partitioning data using Hive
  • Bucketing data
  • Hive Scripting
  • Using Hive UDF's 
  • HBase overview
  • Data model
  • HBase architecture
  • HBase shell
  • Zookeeper & its role in HBase environment
  • HBase Shell environment
  • Creating table
  • Creating column families
  • CLI commands – get, put, delete & scan
  • Scan Filter operations
  • Importing data from RDBMS to HDFS
  • Exporting data from HDFS to RDBMS
  • Importing & exporting  data between RDBMS & Hive tables
  • Overview of Oozie
  • Oozie Workflow Architecture
  • Creating workflows with Oozie
  • Introduction to Flume
  • Flume Architecture
  • Flume Demo

Frequently Asked Questions

After completing our course, you will be able to understand:
  • The need for Big Data and its applications in business
  • The various types of data used to extract Big data information
  • The basics of Hadoop including fundamentals of HDFs and MapReduce
  • How to navigate the Hadoop Ecosystem
  • How to use the various tools and techniques used to analyse Big Data
  • How to use Pig and Hive to extract data
  • How to increase sustainability and flexibility across the organization’s data sets
  • How to develop a Big Data strategy for promoting business intelligence
All participants will be required to work on a project to get hands on familiarity with the concepts learnt. You will use Hadoop techniques on a complex data set to extract relevant information. This project, which can also be a live industry project, will be reviewed by our instructors and industry experts. On successful completion, you will be awarded a certificate.
No prior experience in Hadoop is required. Basic programming knowledge is desired though not a prerequisite for attending this course, also basic knowledge of Microsoft Windows platform is desired.However, if you already have exposure to Hadoop, we can give you a more advanced project to work on based on your capabilities.
Classes are held on weekdays and weekends. You can check available schedules and choose the batch timings which are convenient for you.
You can attend our instructor-led live online classes from the convenience of your home or office, by logging into the virtual classroom on schedule. Classes are conducted via online live streaming, and the recordings will be made available for you a day later.
Please ensure you have:
  • Internet Speed: Minimum 1.0 Mbps connection, with uninterrupted availability 
  • OS: Windows any version above XP SP3, or Mac any version above OS X 10.6
  • 500 MHz processor, 256 MB Ram, 3 GB HDD (minimum)
  • Headset: A good headset with a microphone. You will be responding to the instructor’s questions as well as listening to the lectures.
You may be required to put in 10 to 12 hours of effort every week, including the live class, self study and assignments.
On successful completion of the training, you will get a Course completion certificate. You will be required to work on a project, and will receive detailed project specifications to create an android application. Your project will be reviewed by an expert and if deemed satisfactory, you will be awarded a certificate that grades your performance. In case your project is found unsatisfactory in your first attempt, you can take some extra help and rework on it at no extra cost.
No, you will not be required to refer to textbooks. The training is hands-on and all the course material and class recordings will be made available to you. You will learn by working on a project. You will be supported by your mentor and can clarify doubts at any point of time. 
Don’t worry, you can always access your class recording or opt to attend the missed session again in any other live batch.
We always make sure that all our students are extremely satisfied with the training. However, if you find that it’s not working for you, you can discontinue immediately after your first session and request for a full refund within 7 business days from the class start date.Please refer our Refunds policy for more details.
Please send in an email to hello@zeolearn.com, or contact us through any of the numbers at this link: http://www.zeolearn.com/contact-us We will respond to your queries within 24 hours.

Big Data Analytics using Hadoop Course in Chicago-IL

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