The challenge is that most customers will judge you based on appearance alone, and if your website looks unprofessional or poorly made then they will think your company as a whole is unprofessional. Each and every part of the organization matters when winning over a new client:

• Hadoop Course Introduction
  Hadoop is an Apache open source framework written in java that allows distributed processing of large datasets across clusters of computers using simple programming models. A Hadoop frame-worked application works in an environment that provides distributed storage and computation across clusters of computers. Hadoop is designed to scale up from single server to thousands of machines, each offering local computation and storage.
• Hadoop framework includes following four modules:
  
• Hadoop Common: These are Java libraries and utilities required by other Hadoop modules.
• These libraries provides filesystem and OS level abstractions and contains the necessary Java files and scripts required to start Hadoop.
• Hadoop YARN: This is a framework for job scheduling and cluster resource management.
• Hadoop Distributed File System (HDFS™): A distributed file system that provides high-throughput access to application data.
• Hadoop MapReduce: This is YARN-based system for parallel processing of large data sets.

Hadoop: Basic Concepts

• An Overview of Hadoop
• The Hadoop Distributed File System
• Hands-On Exercise
• How MapReduce Works
• Hands-On Exercise
• Anatomy of a Hadoop Cluster
• Other Hadoop Ecosystem Components

Writing a MapReduce Program

• The MapReduce Flow
• Examining a Sample MapReduce Program
• Basic MapReduce API Concepts
• The Driver Code
• The Mapper
• The Reducer
• Hadoop’s Streaming API
• Using Eclipse for Rapid Development
• Hands-on exercise
• The New MapReduce API

Common MapReduce Algorithms

• Sorting and Searching
• Indexing
• Machine Learning With Mahout
• Term Frequency – Inverse Document Frequency
• Word Co-Occurrence
• Hands-On Exercise.

PIG

• Data loading in PIG.
• Data Extraction in PIG.
• Data Transformation in PIG.
• Hands on exercise on PIG.

Hive

• Hive Query Language.
• Alter and Delete in Hive.
• Partition in Hive.
• Indexing.
• Joins in Hive.Unions in hive.
• Industry specific configuration of hive parameters.
• Authentication & Authorization.
• Statistics with Hive.
• Archiving in Hive.
• Hands-on exercise

Working with Sqoop

• Introduction.
• Import Data.
• Export Data.
• Sqoop Syntaxs.
• Databases connection.
• Hands-on exercise

Working with Flume

• Introduction.
• Configuration and Setup.
• Flume Sink with example.
• Channel.
• Flume Source with example.
• Complex flume architecture.

OOZIE Concepts
IMPALA Concepts
HUE Concepts
HBASE Concepts
ZooKeeper concepts

Support services

We know how hard it can be to find and keep a job when there are so many other things to worry about. Our support team is here to help break down the barriers which are blocking your road to employment.

If you are a Working Chance candidate, please don’t hesitate to ask for advice or support on any issues which are affecting your chances of finding a job.
For further information, please email careers@www.btmgusa.com and our Support and Training Manager will get in touch with you.

Job Preparation

• Assistance with learning job seeking skills.
• Resume creation.
• Master application completion.
• Dressing for success.
• Job interview preparation.

Job Development

• Assistance with completing applications online or in person.
• Job development online, on foot, networking events, job fairs and established employer relationships to locate available positions in your job goal.
• Job leads and information on attending hiring events.
• Follow-ups on applications placed to request interviews.