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Big Data Analytics Course Training in Taipei, Taiwan, ROC

Master Hadoop and unleash the power of Big Data!

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Modes of Delivery

Classroom

Our classroom training provides you the opportunity to interact with instructors face-to-face.

Online Classroom

Collaborative, enriching virtual sessions, led by world class instructors at time slots to suit your convenience.

From USD 999 USD 799 (6 Days)

Description

The explosion of data has greatly enhanced the significance of Hadoop, as organizations worldwide have found Hadoop to be the best platform for managing and processing big data and make the best decisions to transform their business.

Trained Hadoop Data Analysts are much in demand for their expertise on using the Hadoop platform and leverage its best practices to work with big data faster and more effectively.

Our Hadoop Data Analyst course is for those who wish to access, manipulate, and analyze massive data sets using SQL and familiar scripting languages on Hadoop. Learn how to transform data using Apache Pig, Apache Hive, and Cloudera Impala and analyze it using filters, joins, and user-defined functions familiar from other technologies.

On successful completion of the course, you will receive a Course Completion Certificate from KnowledgeHut with Credits (1 credit per hour of training).

What you will learn :
  • Basics of Apache Hadoop and data ETL (extract, transform, load), ingestion, and processing with Hadoop tools
  • How to join multiple data sets and analyze disparate data with Pig
  • How to organize data into tables, perform transformations, and simplify complex queries with Hive
  • How to perform real-time interactive analyses on massive data sets stored in HDFS or HBase using SQL with Impala
  • How to pick the best tool for a given task in Hadoop, achieve interoperability, and manage workflows that are repetitive
You will also learn :
  • High quality training from an industry expert
  • Hands-on experience and practical exercises
  • Downloadable e-book
  • Topic-wise Questionnaire to help you revise course content

Key Features

24 hours intensive training on Big Data and Hadoop
Get comprehensive curriculum with extensive focus on frameworks like PIG, HIVE etc.
Learn practical applications with case studies and hands on exercises
Get course completion certificate
Learn from certified, experienced instructors
Thoroughly grasp the concepts with in-depth questionnaires on each topic

1.1 Big Data Introduction

  • What is Big Data
  • Data Analytics
  • Big Data Challenges
  • Technologies supported by big data

1.2 Hadoop Introduction

  • What is Hadoop?
  • History of Hadoop
  • Basic Concepts
  • Future of Hadoop
  • The Hadoop Distributed File System
  • Anatomy of a Hadoop Cluster
  • Breakthroughs of Hadoop
  • Hadoop Distributions:
  • Apache Hadoop
  • Cloudera Hadoop
  • Horton Networks Hadoop
  • MapR Hadoop
  • Name Node
  • Data Node
  • Secondary Name Node
  • Job Tracker
  • Task Tracker
  • Blocks and Input Splits
  • Data Replication
  • Hadoop Rack Awareness
  • Cluster Architecture and Block Placement
  • Accessing HDFS
  • JAVA Approach
  • CLI Approach
  • Local Mode
  • Pseudo-distributed Mode
  • Fully distributed mode
  • Pseudo Mode installation and configurations
  • HDFS basic file operations

5.1 Writing a MapReduce Program

  • Basic API Concepts
  • The Driver Class
  • The Mapper Class
  • The Reducer Class
  • The Combiner Class
  • The Partitioner Class
  • Examining a Sample MapReduce Program with several examples
  • Hadoop's Streaming API

6.1 PIG

  • PIG concepts
  • Install and configure PIG on a cluster
  • PIG Vs MapReduce and SQL
  • Write sample PIG Latin scripts
  • Modes of running PIG
  • PIG UDFs

6.2 HIVE

  • Hive concepts
  • Hive architecture
  • Installing and configuring HIVE
  • Managed tables and external tables
  • Joins in HIVE
  • Multiple ways of inserting data in HIVE tables
  • CTAS, views, alter tables
  • User defined functions in HIVE
  • Hive UDF

6.3 SQOOP

  • SQOOP concepts
  • SQOOP architecture
  • Install and configure SQOOP
  • Connecting to RDBMS
  • Internal mechanism of import/export
  • Import data from Oracle/MySQL to HIVE
  • Export data to Oracle/MySQL
  • Other SQOOP commands

6.4 HBASE

  • HBASE concepts
  • ZOOKEEPER concepts
  • HBASE and Region server architecture
  • File storage architecture
  • NoSQL vs SQL
  • Defining Schema and basic operations
  • DDLs
  • DMLs
  • HBASE use cases

6.5 OOZIE

  • OOZIE concepts
  • OOZIE architecture
  • Workflow engine
  • Job coordinator
  • Installing and configuring OOZIE
  • HPDL and XML for creating Workflows
  • Nodes in OOZIE
  • Action nodes and Control nodes
  • Accessing OOZIE jobs through CLI, and web console
  • Develop and run sample workflows in OOZIE
  • Run MapReduce programs
  • Run HIVE scripts/jobs

6.6 FLUME

  • FLUME Concepts
  • FLUME Architecture
  • Installation and configurations
  • Executing FLUME jobs

7. Data Analytics using Pentaho as an ETL tool

  • MapReduce and HIVE integration
  • MapReduce and HBASE integration
  • Java and HIVE integration
  • HIVE - HBASE Integration

Our Students

"The course content covered most of the basics and went deeper into details when required. Good hands-on exercises with practical examples."

"Excellent trainer and with confidence I can handle all sorts of PM scenarios and can challenge your mindset. Very good customer service from KnowledgeHut."

"I learned much from this training session, the faculty had good knowledge of the subject matter and provided good learning examples."

"2days PMP training was very good, I got lot of inspiration from this training."

Shreerang Bhawalkar

Shreerang Bhawalkar

ADP Dealer Services
Milind Gawaskar

Milind Gawaskar

Design Managr at NEC
Jan Miko

Jan Miko

Senior Digital Manager
Ada Lee

Ada Lee

Marketing Director

Frequently Asked Questions

There are no prerequisites for attending this course.

Yes, KnowledgeHut does offer virtual training for Big Data Analytics. Call us for more information on the same.

On successful completion of the course you will receive a course completion certificate issued by KnowledgeHut.

You will receive 1 credit per hour of learning which totals to 24 PDUs for the entire workshop.

To make the most effective use of the Hadoop platform, and fully analyze and utilize every aspect of data for maximized productivity, training is of paramount importance. Trained Hadoop Data Analysts will be able to leverage best practices to work with big data faster and more effectively. Our Hadoop Data Analyst course is for those who wish to access, manipulate, and analyze massive data sets using SQL and familiar scripting languages on Hadoop. Learn how to transform data using Apache Pig, Apache Hive, and analyze it using filters, and other user-defined functions familiar from other technologies.

Big Data has found uses everywhere from retail to politics to environmental issues. Most significantly it has been used to understand and target customers. Retailers are also using it with success to optimize their business processes. Big Data has also revolutionized the way healthcare operates and has helped huge advances to be made in the field of science and technology. The technology is now being used to decode complex biological patterns such as DNA strings and predict outbreak of diseases. Its use in military and defence operations have been well documented with NSA using it to foil terrorist plots. Big Data analytics have helped make better machines and optimize their performance to make our lives better and easier.

Any registration cancelled within 48 hours of the initial registration will be refunded in FULL (please note that all cancellations will incur a 5% deduction in the refunded amount due to transactional costs applicable while refunding). Refunds will be processed within 30 days of receipt of written request for refund. Kindly go through our Refund Policy for more details: http://www.knowledgehut.com/refund.

Please send in an email to support@knowledgehut.com, and we will answer any queries you may have!

This course is best suited to data analysts, business analysts, developers, and administrators who have experience with SQL and basic UNIX or Linux commands.

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