Best Big Data Hadoop Training in Hyderabad

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Dataopt solutions have started Hadoop e-training. e-training offers full-length courses on a range of Big Data Hadoop technologies for developers, data analysts and data Science by DataOpt Solutions. Designed in a format that meets your convenience, availability and flexibility needs, these courses will lead you on the path to becoming a certified Hadoop professional. e-training includes details course contents, Quiz, Questions and Answers on specific topics like Big Data concepts, HDFS, Map-Reduce, Hive, Pig, HBase, NoSQL, Sqoop, Oozie, Flume etc. and question bank for Big Data-Hadoop developer jobs interview.

http://www.dataoptsol.com/elearning.html

Why data Science?

We are starting a new classroom weekend batch on Hadoop and Big data from 13-June-2015, this Saturday a weekday batch from 10-June-2015.
You can still enroll for this batch but please hurry up before all seats are booked.
Enroll and get ahead from your peers in this appraisal season.
Please note that there is no need to have Java knowledge to be able to attend this course.
We will teach you from the basics and our main focus is on Hadoop eco-system tools which are the most used tools in Big Data Industry.
To know more about this you can call us at +040 40037316 or visit: http://www.dataoptsol.com/
Learn about Big Data and why is it becoming so important now days.
Introduction to Big Data, Hadoop and Data Science
Challenges of Big Data
Business Intelligence & Data Analysis
Data Mining & Machine Learning
Hadoop Architecture & Other Architectures
Technologies supporting Big Data
Hadoop Eco-System
Use cases of Hadoop
Fundamental Design Principles of Hadoop
Understand Hadoop Cluster Architecture & Map Reduce
Hadoop Cluster & Architecture
Daemons
Rack Awareness & Cluster Balancing
Map Reduce Overivew
Log Processing and Map Reduce
Advanced Map Reduce Concepts
Hadoop 2.0 Yarn
Hadoop 1.0 Challenges
Hadoop 2.0 New Features
Hadoop 2.0 Cluster Architecture & Federation
Hadoop 2.0 HA
Yarn & Hadoop Ecosystem
Yarn MR Application Flow
PIG
Multi-Dataset Operations with Pig
Techniques for Combining Data Sets
Hive Fundamentals & Architecture
Hive Architecture and Installation
HiveQL: Data Types, Operators and Functions,
HBase Architecture and concepts
SQOOP
Flume & Oozie
Hadoop Project in Banking Domain
Hadoop Project in Telecom Domain
Hadoop Project in Sentimental Analysis
Hadoop Project in Sentimental Analysis & ETL Offloading
Hadoop Project in Healthcare

Data Opt Solutions Data Opt Solutions

Hadoop & Data Science contents.
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Batch started for Data Science for weekdays and weekend.

Module 1 Introduction tp Big Data, Hadoop and Data Science
What is Big Data and Hadoop?
Challenges of Big Data
Traditional approach Vs Hadoop
Analytics Value Chain
Business Intelligence & Data Analysis
Data Mining & Machine Learning
Hadoop Architecture & Other Architectures
OLTP vs OLAP
Distributed Model
Block structure File System
Technologies supporting Big Data
Replication
Fault Tolerance
Why Hadoop?
Hadoop Eco-System
Use cases of Hadoop
Fundamental Design Principles of Hadoop
Comparison of Hadoop Vs RDBMS

Module 2 Understand Hadoop Cluster Architecture & Map Reduce
Hadoop Cluster & Architecture
5 Daemons
Typical Workflow
Writing Files to HDFS
Reading Files from HDFS
Rack Awareness & Cluster Balancing
Before Map Reduce

Map Reduce Overivew
Word Count Problem
Word Count Flow & Solution
Map Reduce Flow
Log Processing and Map Reduce
What is Mapper?
What is Reducer?
What is Shuffling?

Module 3 Advanced Map Reduce Concepts
What is Combiner?
What is Partitioner?
What is Counter?
InputFormats/Output Formats
Map Join using MR
Reduce Join using MR
MR Distributed Cache
Using sequence files & images with MR
Module 4 Hadoop 2.0 Yarn
Hadoop 1.0 Challenges
NN Scalability
NN SPOF & HA
Job Tracker Challenges
Hadoop 2.0 New Features
Hadoop 2.0 Cluster Architecture & Federation
Hadoop 2.0 HA
Yarn & Hadoop Ecosystem
Yarn MR Application Flow

Module 5 PIG
Introduction to Pig
What Is Pig?
Pig’s Features & Pig Use Cases
Interacting with Pig
Basic Data Analysis with Pig
Pig Latin Syntax
Loading Data
Simple Data Types
Field Definitions
Data Output
Viewing the Schema
Filtering and Sorting Data
Commonly-Used Functions
Hands-On Exercise: Pig for ETL Processing
Processing Complex Data with Pig
Storage Formats
Complex/Nested Data Types
Grouping
Built-in Functions for Complex Data
Iterating Grouped Data
Hands-On Exercises
Multi-Dataset Operations with Pig
Techniques for Combining Data Sets
Joining Data Sets in Pig
Splitting Data Sets
Hands-On Exercise

Module 6 HIVE
Hive Fundamentals & Architecture
Loading and Querying Data in Hive
Hive Architecture and Installation
Comparison with Traditional Database
HiveQL: Data Types, Operators and Functions,
Hive Tables ,Managed Tables and External Tables
Partitions and Buckets
Storage Formats, Importing Data, Altering Tables, Dropping Tables
Querying Data, Sorting and Aggregating, Map Reduce Scripts,
Joins & Sub queries, Views
When to Use HIVE, Impala and Pig
Hands on Exercises
Integration, Data manipulation with Hive
User Defined Functions,
Appending Data into existing Hive Table
Static partitioning vs dynamic partitioning

Module 7 HBASE
CAP Theorem
HBase Architecture and concepts
Introduction to HBase
Client API's and their features
HBase tables The ZooKeeper Service
Data Model, Operations
Programming and Hands on Exercises

Module 8 SQOOP
Introduction to Sqoop
MySQL Client & server
Connecting to relational data base using Sqoop
Importing data using Sqoop from Mysql
Exporting data using Sqoop to MySql
Incremental append
Importing data using Sqoop from Mysql to hive
Exporting data using Sqoop to MySql from hive
Importing data using Sqoop from Mysql to hbase
Using queries and sqoop

Module 9 Flume & Oozie
What is Flume?
Why use Flume, Architecture, configurations
Master, collector, Agent
Twitter Data Analysis project

Module 10 Oozie
What is Oozie, Architecture, configurations?
Oozie Job Submission
Oozie properties
Hands on exercises

Module 11 Project in Banking Domain
Hadoop Project in Banking Domain
Objective
Problem Definition
Solution
Discuss data sets and specifications of the project.

Module 12 Project in Telecom Domain
Hadoop Project in Telecom Domain
Objective
Problem Definition
Solution
Discuss data sets and specifications of the project.

Module 13 Project in Sentimental Analysis
Hadoop Project in Sentimental Analysis
Objective
Problem Definition
Solution
Discuss data sets and specifications of the project.

Module 14 Project in Sentimental Analysis & ETL Offloading
Hadoop Project in Sentimental Analysis & ETL Offloading
Objective
Problem Definition
Solution
Discuss data sets and specifications of the project.

Module 15 Project in Healthcare
Hadoop Project in Healthcare
Objective
Problem Definition
Solution
Discuss data sets and specifications of the project.

We have started the Hadoop Advanced Administrator Training. This training is design for corporate peoples who are working as System Admin. This training is started on 9th Feb 2015. Trainer is Hadoop Administrator working with Big MNC.

We have started the Hadoop Advanced Administrator Training. This training is design for corporate peoples who are working as System Admin. This training is started on 9th Feb 2015. Trainer is Hadoop Administrator working with Big MNC.

Big Data and Hadoop Training batch in DataOpt Solutions, Madhapur Hyderabad is scheduled to commence on January 20th, 2015. The training is conducted in a workshop like environment with an effective blend of hands-on practical’s and assignments to augment the fundamental theory covered and Live Project (Actually implemented)
About the Faculty:
He is a Data scientist and an industry veteran on Big Data Analystics with more than fifteen years’ experience in launching new technologies, products and businesses. He has been involved in acquiring four patents for the company that he has worked for.

Big Data Analytics – Why?
Data is now generated by more sources and at ever increasing rates. Examples include Social Media sites, GPS based tracking systems, Telecom domain analytics, point of sale equipment, etc. The ability to process such data can provide that essential edge required for business success. Demand for Big Data professionals is rapidly increasing. Knowledge of Big Data can provide an advantage leading to faster professional advancement

About this course
This course on Big Data Analytics for Business is a combination of essential fundamentals, practical techniques, hands-on sessions on Hadoop, and case studies, Live project to cement all this together.
By completing this course you will be able to …
Understand fundamentals of analytics: Descriptive, Predictive and Prescriptive Analytics
Know what ‘Big Data’, Map Reduce and Hadoop are all about
Get a grip on the structure of Big Data applications
Effectively use Big Data techniques like Map Reduce and tools like Hadoop, Hive, Hbase, Pig, R
Choose the most appropriate tools to solve Big Data problems
Identify, propose and lead Big Data projects in your organizations



Course Content -
What is Big Data?
Overview of Big Data tools and techniques
In-depth coverage of Map-reduce techniques to manage Big Data
Hadoop - In Depth
HDFS – In Depth
Installing and managing Hadoop – Hands-on
Introduction to Hadoop Clusters
Hands-on session using native installation and cloud implementation of Hadoop
The Hadoop ecosystem: Pig, HIVE, HBase, Pig, SQOOP and Flume
Big Data Analytics using R
Analytics: Descriptive, Predictive and Prescriptive
What is Big Data Analytics
Introducing Analytics in the enterprise: Case Studies
Trends in Big Data Analytics
Live Projects which are already implemented for big company
The course takes a "hands-on" approach to ensure that the basics are understood very well and assimilated concepts are applied in practice.

Hurry up!!! the next batch will be started by 12th Oct 2014. Already 3 batches are running with great learning and students provided very good feedback about our training solutions.

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DataOpt Solutions Hyderabad India The ever competitive software product industry continues to witness new technologies like Big Data Analytics, Real Time Data Warehousing, Virtualization and ...

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