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About Hadoop: It is a Framework based on java and available for free. It supports the process of processing a large amount to datas over a wide range of distributed computers. It is sponsored by Apache Software Framework. Modules with Hadoop: Admin Developer Architect These are the modules available with Hadoop technology and currently hadoop is considered as the most booming technology with this requirement we are providing the best Hadoop Training in Chennai with the guidance of expert trainer from top companies. Our training will be more of practical classes which will readily offers you the full technical stuffs. We are having an excellent lab setup with us also providing you free software support which increases the time to practise. At the end of the course you will be having knowledge equal to the professionals having 2+ years of experience. Our customized syllabus will starts with basic training to advanced level training which can provide you guaranteed full technical knowledge. We are providing free demo session over every weekend. So contact us and enroll for free demo class. We are available at 9566183028 or

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Course content: "Teradata Admin Track" Teradata Architecture and other essentials Introduction What is Teradata and role of Teradata in Data Ware housing industry, Evolution of Teradata DW, Significant characteristics of Teradata, Advantages of Teradata over other RDBMS Teradata Architecture Understanding H/W and S/W components, involved in Architecture of Terdata(vdisks, AMP, PE Vprocs, BYNET etc...). Data distribution Understanding significance of Index in teradata(UPI, NUPI, SI, NUSI, Partitioned index) Data Protection Different levels of failures that could happen and fault tolarance of Teradata in that situations. (CLIQUE, CLUSTER, RAID, LOCKS and JORNALS) Advanced Teradata SQL HELP, SHOW, EXPLAIN, Define and execution of Macros, Date calculations, data type conversion, Case, COALESCE, sample, Ranking, Qualify, CSUM, MSUM, MDIFF, MAVG, WITH, WITH BY. Others (Optional) Unix Role of Unix in executing Teradata utility scripts and Basic commands used General Lifecycle of the projects General phases of a Development project. Documents required in each phase DBA Teradata DBA basics and responsibilities Initial Teradata Databases Administrative User Owners, Parents and Children Creating New Users and Databases Transfer of Ownership DELETE/DROP Statements User and Security Management Understand the Heirarchy,Teradata Administrator tool usage to perform creation of users, databases, Identify spaces, skew of databases, Moving spaces and accesses, And all the practicals to perform of all coming up topics. The Data Dictionary Updating Data Dictionary Tables Supplied Data Dictionary Views Restricted Views Suffix Options with Views Selecting Information about Created Object Children View, Databases View, Users View, Tables View Columns View, Indices View Capacity management and planning Spaces and types of tables - PERM, SPOOL, TEMP space terminology, Derived,Volatile, Global temporary tables. Identify current space usage and estimate the space requirments for the applications. Users, Accounts, and Accounting Creating and Using Account IDs Using Account IDs with Logon Dynamically Changing an Account ID Account Priorities Account String Expansion Access Rights Privileges/Access Rights Implicit, Automatic, and Explicit Rights GRAND and REVOKE accesses, GIVE command System Views for Access Rights Inheriting Access Rights, Transfer access rights, Delete or Drop / user or database Roles and Profiles What is a role, Advantages of Roles, Access Rights Using a Role, Implementing Roles, Nesting of roles, views for roles, Profiles, implementing Profiles, Teradata password control Work load management and Priority scheduler Levels of Workload Management, Priority Scheduler Architecture, and concepts Access logging and Query logging Setting up Access Logging, AccLogRules View, Query Logging (DBQL) Concepts, Objects used in Defining Rules for DBQL, DBQLRules View Setting up Access Logging, AccLogRules View, Query Logging (DBQL) Concepts, Objects used in Defining Rules for DBQL, DBQLRules View Performance monitoring (PMON) Resource usage, Session Management User session Info, SQL & Explain Steps Archive and Restore and copy Archive and restore data using ARCMAIN utility, Different levels of archiving and restoration, HUT locks, Revalidate references after restoration View point The Demo of view point portlets (which is new tool for DBAs having the features of PMON, TDMANAGER and TASM Performance tuning Explain plan, Statistics and Join strategies Explain plan and recommandations. Significance of collecting statistics Other indexes, and techniques Determine the proper join columns, Join index, Spars index, Aggregate index, SET / MULTSET with UPI and NUPI combinations, compress. Course Content: Teradata Dev Track History and Architecture Introduction OLTP, OLAP systems, Dataware house and Data Marts, Dimenssion modeling, Schemas, What is Teradata and role of Teradata in DW, Evolution of Teradata DW, Advantages of Teradata over other RDBMS Teradata Architecture Understanding H/W and S/W components, involved in Architecture of Terdata(vdisks, AMP, PE Vprocs, BYNET etc…). Database structure Data distribution Understanding significance of Index in teradata(UPI, NUPI, SI, NUSI, Partitioned index) Data Protection Different levels of failures that could happen and fault tolarance of Teradata in that situations.(CLIQUE, CLUSTER, RAID, LOCKS and JORNALS) Spaces and types of tables Different levels of accessing the objects granting the Privileges and locking mechanism SQL ASNI SQL Brief introduction of Relational concepts, understanding users, databases, tables, vies, index, macro etc. Sub query, corelated query, Data types, Joins, Arthimatic functions Teradata SQL Explore teradata specifc SQL statements such as show, help,explain..SET operations, Aggregate functions, Sring functions, Aliasing,FORMAT, conversion of the datatypes. Advanced Teradata SQL Define and execution of Macros, Date calculations, Case, COALESCE, sample, Ranking, Qualify, CSUM, MSUM, WITH, WITH BY. Client utilities SQL Assistant Settup ODBC for connecting through SQL assistant, options menu and EXPORT/IMPORT BTEQ Functinality,operations, exectuion and limitations FAST LOAD Functinality, Different phases, exectuion, restartability and limitations FAST EXPORT Functinality, Different phases, exectuion, restartability and limitations MULTI LOAD Functinality, Different phases, exectuion, restartability and limitations Performance tuning Explain plan & Statistics & Understanding Explain plan and recommandations. Significance of collecting statistics Other techniques Determine the proper join columns, Join index, Spars index, Aggregate index, SET / MULTSET with UPI and NUPI combinations, compress Others (Optional) Unix Role of Unix in executing Teradata utility scripts and Basic commands used General Lifecycle of the projects General phases of a Development project. Documents required in each phase

Syllabus- Course Objective Summary During this course, you will learn: Introduction to Big Data and Hadoop Hadoop ecosystem - Concepts Hadoop Map - reduce concepts and features Developing the map - reduce Applications Pig concepts Hive concepts Oozie workflow concepts HBASE Concepts Real Life Use Cases Introduction to Big Data and Hadoop What is Big Data? What are the challenges for processing big data? What technologies support big data? What is Hadoop? Why Hadoop? History of Hadoop Use Cases of Hadoop Hadoop eco Syst em HDFS Map Reduce Statistics Understanding the Cluster Typical workflow Writing files to HDFS Reading files from HDFS Rack Awareness 5 daemons Let's talk Map Reduce Before Map reduce Map Reduce Overview Word Count Problem Word Count Flow and Solution Map Reduce Flow Algorithms for simple & Complex problems Developing the Map Reduce Application Data Types File Formats Explain the Driver, Mapper and Reducer code Configuring development environment - Eclipse Writing Unit Test Running locally Running on Cluster Hands on exercises How Map - Reduce Works Anatomy of Map Reduce Job run Job Submission Job Initialization Task Assignment Job Completion Job Scheduling Job Failures Shuffle and sort Oozie Workflows Hands on Exercises Map Reduce Types and Formats Map Reduce Types Input Formats - Input splits & records, text input, binary input, multiple inputs & database input Output Formats - text Output, binary output, multiple outputs, lazy output and database output Hands on Exercises Map Reduce Features Counters Sorting Joins - Map Side and Reduce Side Side Data Distribution MapReduce Combiner MapReduce Partitioner MapReduce Distributed Cache Hands Exercises Hive and PIG Fundamentals When to Use PIG and HIVE Concepts Hands on Exercises HBASE CAP Theorem  Introducti on to NOSQL Hbase Architecture and concepts Programming and Hands on Exercises Case Studies Discussions Certification Guidance Fee- INR+100 INR Registration Duration-45 hours(weekdays & weekends) Online training available on request Get trained on latest technology by ZEN industry expert. Technology: Java-SCJP/OCJP/Hibernate/Struts/Sprint etc.NET- VB.Net/C#/ASP.net/ MVC frarmrework etc Big data/Hadoop etc ETL/ data Stage/SQL Oracle// DBA/App / forms & reports etc C,C++ PHP/HTML5/javascript/JQuery/AJAX/AngularJS etc For other course like software testing, java, PHP, web technologies, Mobile application using Android/iOS and phone GAP please visit our office or contact us on given number Zeuristech Enterprise Networks Pvt. Ltd.,-ZEN 2nd Floor, Saikar Complex,Beside Ginger Hotel Bhumkar Chowk -pune- Land Mark- ICICI/AXIS Bank ATM Building

Introduction to Big Data and Hadoop What is Big Data? What are the challenges for processing big data? What technologies support big data? Distribution systems. What is Hadoop? Why Hadoop? History of Hadoop Use Cases of Hadoop Hadoop eco System HDFS Map Reduce Statistics Understanding the Cluster Typical workflow Writing files to HDFS Reading files from HDFS Rack Awareness 5 daemons Developing the Map Reduce Application Configuring development environment - Eclipse Writing Unit Test Running locally Running on Cluster MapReduce workflows How MapReduce Works Anatomy of a MapReduce job run Failures Job Scheduling Shuffle and Sort Task Execution MapReduce Types and Formats MapReduce Types Input Formats - Input splits & records, text input, binary input, multiple inputs & database input Output Formats - text Output, binary output, multiple outputs, lazy output and database output MapReduce Features Counters Sorting Joins - Map Side and Reduce Side Side Data Distribution MapReduce Combiner MapReduce Partitioner MapReduce Distributed Cache Hive and PIG Fundamentals When to Use PIG and HIVE Concepts HBASE CAP Theorem Hbase Architecture and concepts Programming

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