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Data Stage Course Content at Traning at learning hub Magarpatta city /FC Road Pune (+91-93257-93756) www.learninghub.co.in Data Stage Data Stage Course Content at Learning Hub Contents • Introduction about Data Stage • Difference between Server Jobs and Parallel Jobs • Difference between Pipeline Parallelisms • Partition techniques (Round Robin, Random, Hash, Entire, Same, Modules,Range,DB2,Auto) • Configuration File • Difference between SMP/MPD architecture • Data Stage Components (Server components/Client Components) • Package Installer Data Stage Administrator • Creating project, Editing project and Deleting project • Permissions to user • .Apt Config file • Environment variable creation, permission Data stage director • Introduction to Data stage Director • Job status View • View logs • Scheduling • Batches Creation Designer • Introduction about Designer • Repository • Palatte • Types of Links • File Stages • Sequential File • Data set File • Lookup file set • Difference between Sequential file/Dataset/File set • Database stages • Dynamic RDBMS • Oracle Enterprise • ODBC Enterprise • Stored Procedure Processing stages • Change Capture (Caption) • Compare stage • Difference Stage • Aggregate Stage • Transformer Stage • Surrogate Generator Stage • Join Generator Stage • Merge Generator Stage • Lookup Generator Stage • Difference between join/Lookup/Merge • Difference between join/Lookup • Remove Duplicates • Switch • Pivot • Modify • Funnel Debugging stage • Head • Tail • Pea • Row Generator • Column Generator • Sample • Job Parameters Manager • Introduction About Data stage Manager • Importing the Job • Exporting the Job • Importing Table Definition • Importing Flat File Definition • Routines Containers • Difference between Local Container and Shared Container • Local Container • Shared Container Please Contact- Learning Hub, S-12,Destination Centre, 2nd Floor, Above HDFC Bank, Next to Noble Polyclinic, MAGARPATTA CITY, PUNE – 411013, PH: +91- 93257-93756. Skype id : learning.hub01 Email: learninghub01@gmail.com www.learninghub.co.in Data Stage Online Training, Data Stage Class Room Training, Data Stage Training in Magarpatta City, Data Stage Jobs and Placement, Data Stage Remote Support, Data Stage Online Help,Data Stage Videos training, Data Stage training by Learning Hub, Fast track classes in Data Stage, Best Data Stage training institutes in Pune, Best Faculty in Data Stage, Best online Faculty in Data Stage, Professional classroom training in Data Stage, Professional online training in Data Stage,Data Stage Certification, Data Stage training in Dubai, Data StageTraining in Melbourne, Data Stage Training in Dubai, Data Stage Training, Data Stage Training,Data Stage Training, Data StageOnline Training, Data Stage certfication and suppor

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An introduction to the fundamentals of data structures, this book explores abstract concepts and considers how those concepts are useful

BASE SAS MODULES Day 1: Introduction to the SAS System Components of Base SAS Software Output Produced by the SAS System Ways to Run SAS Programs Running Programs in the SAS Windowing Environment Introduction to DATA Step Processing The SAS Data Set introduction How the DATA Step Works: A Basic Introduction Supplying Information to Create a SAS Data Set Introduction to Raw Data Examine the Structure of the Raw Data: Factors to Consider Reading Unaligned Data Reading Data That Is Aligned in Columns Reading Data That Requires Special Instructions Reading Unaligned Data with More Flexibility Mixing Styles of Input Day 2: Introduction to Beyond the Basics with Raw Data Using INFILE statement and various options. Testing a Condition before Creating an Observation Creating Multiple Observations from a Single Record Reading Multiple Records to Create a Single Observation Problem Solving: When an Input Record Unexpectedly Does Not have enough values Day 3: Introduction to Starting with SAS Data Sets Understanding the Basics Input SAS Data Set for Examples Reading Selected Observations Reading Selected Variables Creating More Than One Data Set in a Single DATA Step Using the DROP=, KEEP= and WHERE= Data Set Options for Efficiency Introduction to DATA Step Processing Input SAS Data Set for Examples Adding Information to a SAS Data Set Defining Enough Storage Space for Variables Conditionally Deleting an Observation Day 4: Introduction to Working with Numeric Variables About Numeric Variables in SAS Input SAS Data Set for Examples Calculating with Numeric Variables Comparing Numeric Variables Storing Numeric Variables Efficiently Numeric Functions. Day 5: Introduction to Working with Character Variables Input SAS Data Set for Examples Identifying Character Variables and Expressing Character Values Handling Missing Values Creating New Character Values Saving Storage Space by Treating Numbers as Characters Character Functions Day 6: Introduction to Acting on Selected Observations Input SAS Data Set for Examples Selecting Observations Constructing Conditions Comparing Characters Introduction to Creating Subsets of Observations Input SAS Data Set for Examples Selecting Observations for a New SAS Data Set Conditionally Writing Observations to One or More SAS Data Sets Day 7: Introduction to Working with Grouped or Sorted Observations Input SAS Data Set for Examples Working with Grouped Data Working with Sorted Data Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Day 8: Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Introduction to Working with Dates Understanding How SAS Handles Dates Input File and SAS Data Set for Examples Entering Dates Displaying Dates Using Dates in Calculations Using SAS Date Functions Comparing Durations and SAS Date Values Day 9: Introduction to Combining SAS Data Sets Definition of Concatenating Definition of Interleaving Definition of Merging Definition of Updating Definition of Modifying 237 Comparing Modifying, Merging, and Updating Data Sets Day 10: Introduction to Concatenating SAS Data Sets Concatenating Data Sets with the SET Statement Concatenating Data Sets Using the APPEND Procedure Choosing between the SET Statement and the APPEND Procedure. Introduction to Interleaving SAS Data Sets Understanding BY-Group Processing Concepts Interleaving Data Sets Day 11: Introduction to Merging SAS Data Sets Understanding the MERGE Statement One-to-One Merging Match-Merging Choosing between One-to-One Merging and Match-Merging Introduction to Updating SAS Data Sets Understanding the UPDATE Statement Understanding How to Sel

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Big Data & Hadoop Classroon Developer Training In Bangalore. Introduction 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 • HBASE Concepts • Mongo DB Concepts • Sqoop 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 System • 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 problems • Algorithms for 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 c • 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 • 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 • 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 • Hbase Architecture and concepts • Programming and Hands on Exercises Case Studies Discussions Thanks&Regards Softech Solution.

Big Data & Hadoop Training in one month in Aptech Hazra Learn basics of Big-Data& Hadoop Smart Professional - Big Data Aptech's Smart Professional: Big Data course trains you in advance database technologies like Hadoop, used by more than half of Fortune 50 companies. The curriculum trains you from the basic to the advanced level, right from installing & configuring Hadoop, and maintaining the system, to using additional products that integrate with other systems. Course Details •Onlinevarsity - A learning app, exclusively for our students that provides access to study material, e-books, reference material, video tutorials, chats with experts & more •Move applications stored on a computer to a remote location & make them accessible online through standard browsers •Understand concepts & technologies of big data & its management •Develop dynamic web applications in PHP & use MySQL efficiently for those applications •Implement data security during data manipulation & access •Use NoSQL for storage & retrieval of data •DUse MongoDB and Apache Cassandra to handle large amounts of data across servers •Use Hadoop for distributed storage & processing of big data •Use PigLatin, Hive, Hbase for querying & managing databases •Perform analysis & reporting with big data tools Course Covers •Introduction to cloud computing •Introduction to big data •Data security •Working with NoSQL •Data management using MongoDB & Apache Cassandra •Fundamentals of Hadoop •Reporting & analytics with bigdata •Project COURSE DURATION Smart Professional - Big Data is an 8-month course. Classes are typically held 2 hours - a - day / 3 - days - a - week. ELIGIBILITY IT graduates / professionals / engineers

Certification course in Big data and Hadoop. Certification provided by Government of India. Batch Starting Dates: June Batch Size - 25 Students Eligibity: BE/BTECH CS, IT, ES Semester: Course Duration - 40 Hours Timings - 10 AM - 6 PM Fees: Rs /- Benefits: 1. Certification by Skill Development Ministry, Government of India. 2. Free placement assistance for one year. 3. Training by industry experts and live project. Course Outline: > What is Big Data & Why Hadoop? > HDFS (Hadoop Distributed File System) and installing Hadoop on single node. > Advanced HDFS concepts > Cloud computing overview and installing Hadoop on multiple nodes. > Introduction to Map Reduce. > Map Reduce workshop. > Advanced Map Reduce concepts. > Using Pig and Hive for data analysis. > Introduction to HBase, Zookeeper & Sqoop. > Introduction to Oozie, Flume and advanced Hadoop concepts. > Building a web-log analysis POC using MapReduce & project discussion

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

Learn in just One month Big Data Hadoop,Hadoop,Hadoop by Industry experts in Elegant it Introduction to Big Data and Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • HBASE Concepts • Mongo DB Concepts • Sqoop 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 System • 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 problems • Algorithms for 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 c • 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 • 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 • 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 • Hbase Architecture and concepts • Programming and Hands on Exercises Case Studies Discussions Thanks&Regards Elegant IT Services, #nd Floor,Aswath Nagar Varthur main road,Near Railway Fly Over Maratha halli,Land mark: Chemmunar Jewellers, Bangalore -

SequelGate is one of the best training institutes for Hadoop Training, Big Data Training, Informatica Training and Dataware House Training. We have been providing Classroom and Classroom Trainings and Corporate training. All our training sessions are COMPLETELY PRACTICAL. Hadoop Training with PROJECT - ONLINE TRAINING COURSE DETAILS: Introduction to Hadoop Introduction to Big Data Introduction to Hadoop The Hadoop Distributed File System (HDFS) Map Reduce Map/Reduce Programming – Java Programming NOSQL HBase Hive Pig SQOOP HCATALOG. FLUME Flume Agents Log User information using Java program More Ecosystems Oozie SPARK Initializing Spark Resilient Distributed Datasets (RDDs) Parallelized Collections Duration: 7 weeks, every day for 1.5 hours and all sessions are completely practical. One Real-time Project included in the c Office: (+91) 040 65358866 Mobile: (+91) 0 9030040801  Sai Anu Avenue, Street Number 3, Patrika Nagar, HITEC City, Hyderabad - 81 (India).

SequelGate is one of the best training institutes for Hadoop Training, Big Data Training, Informatica Training and Dataware House Training. We have been providing Classroom and Classroom Trainings and Corporate training. All our training sessions are COMPLETELY PRACTICAL. Hadoop Training with PROJECT - ONLINE TRAINING COURSE DETAILS: Introduction to Hadoop Introduction to Big Data Introduction to Hadoop The Hadoop Distributed File System (HDFS) Map Reduce Map/Reduce Programming – Java Programming NOSQL HBase Hive Pig SQOOP HCATALOG. FLUME Flume Agents Log User information using Java program More Ecosystems Oozie SPARK Initializing Spark Resilient Distributed Datasets (RDDs) Parallelized Collections Duration: 7 weeks, every day for 1.5 hours and all sessions are completely practical. One Real-time Project included in the course. All Sessions are Completely Practical and Realtime. Contact us today for practical Hadoop Online training. Office: (+91) 040 65358866 Mobile: (+91) 0 9030040801  Sai Anu Avenue, Street Number 3, Patrika Nagar, HITEC City, Hyderabad - 81 (India).

SequelGate is one of the best training institutes for HADOOP Training, Big Data Training, Informatica Training and Dataware House Training. We have been providing Classroom and Online Trainings and Corporate training. All Our Training Classes are Example Based and Real Time. We provide Big Data and Hadoop Certification course is designed to prepare you for a job assignment in the Big Data world. The course provides you not only with Hadoop 2.7 essential skills, but also gives you practical work experience in Big Data Hadoop by completing long-term, real-world projects. Study & Practice Material provided during the course. HADOOP Training with PROJECT - CLASSROOM TRAINING COURSE DETAILS: Introduction to Big Data Introduction to Hadoop The Hadoop Distributed File System (HDFS) Map Reduce Map/Reduce Programming – Java Programming NOSQL HBase Hive Pig SQOOP HCATALOG. FLUME Flume Agents Log User information using Java program More Ecosystems Oozie SPARK Initializing Spark Resilient Distributed Datasets (RDDs) Parallelized Collections Duration: 7 weeks, every day for 1.5 hours and all sessions are completely practical. One Real-time Project included in the course.

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SAP Warehouse Management Course Content Introduction to Warehouse Management • Organization Data • Master Data • Transactions • Reports Organization Data Define Warehouse Structure • Warehouse Number • Storage Type • Storage Section • Storage Unit Master Data • Material Master • Storage Bin Transfer Requirement • Create Transfer Requirement Automatically • Create Transfer Requirement Manually • Create Transfer Requirement for Storage Type • Create Transfer Requirement for Material Posting change notice • Create Posting change notice Transfer Order • Number Range for TO • Create TO w.r.t Transfer Requirement • Create TO w.r.t Posting Change Notice No • Create TO w.r.t Storage Unit Number • Create TO w.r.t Material Document • Create TO w.r.t Inbound/Out Bound Delivery • Confirm the Transfer Order • Cancel the Transfer Order Put away Strategies • Next to Empty Bin • Addition to Existing Bin • Bulk Storage • Fixed Bin Strategy • Storage Unit Type Picking Strategies • Shelf Life Expired • FIFO • LIFO • Stringent Picking Business Scenario’s • Goods Receipt Processing with Inbound Delivery • Goods Receipt Processing with out Inbound Delivery • Goods Issue with out Bound Delivery • Goods Issue for Internal Consumption • Stock Transfer from Warehouse Store to Non-Warehouse Store • Stock Transfer from Warehouse to Warehouse Store • Stock Transfer from Non Warehouse-to-Warehouse Store • Stock Transfer from Bin to Bin • Stock Transfer from Stock Type to Stock Type • Multiple Picking Process for TR's/Outbound Deliveries • Two Step Picking and Wave Picks Storage unit management • Define Storage Types with Storage Unit Management • Put away and Picking Strategies with Storage Unit Management • Create Transfer Order with Storage Unit Number Physical Inventory • Create Physical Inventory Record • Enter Count Results • Clear the Difference in WM • Clear the Difference in IM Warehouse movement types • Define Reference Movement Types for WM • Assign Reference Movement Types to WM Movement Types • Define WM Movement Types Search Strategies • Storage Type Search Strategies • Storage Section Search Strategies • Storage Bin Type Search Strategies RFID Overview All Training reference Materials would be provided as a part of the course. SAP ECC 6.0 EHP 5 Server will also be configured as part of this training.(Hands on)

Pentaho data integration training in Hyderabad Course Introduction Pentaho Data Integration Overview Inputs and Outputs Introduction to the Training Data

WARM WELCOME FROM VELGRO TECHNOLOGIES!!! We are providing training for DATA WAREHOUSE Training is provided by well experienced (REAL TIME) Faculty!!! Fee structure Course fees: RS./- Data Warehouse The Compelling Need for Data Warehousing • Escalating Need for Strategic Information • Failures of Past Decision-Support Systems • Operational Versus Decision-Support Systems • Datawarehousing—The Only Viable Solution • Datawarehouse Defined • The Datawarehousing Movement • Evolution of Business Intelligence Data Warehouse: The Building Blocks • Review formal definitions of a data warehouse • Discuss the defining features • Distinguish between data warehouses and data marts • Study each component or building block that makes up a data warehouse • Introduce metadata and highlight its significance Trends in Data Warehousing • Data Warehouse Do-Overs • Proliferation of Data Sources • Outsourcing • Hub Versus Relational Databases • Active Data Warehouses • Fusion with CRM • Growing Number of End Users • More Complex Queries • Integrated Customer View • Exploding Data Volumes Planning and Project Management • Phases in project management • Inception • Elaboration • Construction • Transition Defining the Business Requirements • To gain agreement with stakeholders • To provide a foundation to communicate to a technology service provider what the solution needs to do to satisfy the customer’s and business’ needs • To provide input into the next phase for this project • To describe what not how the customer/business needs will be met by the solution Requirements as the driving force for data warehousing • Understand why business requirements are the driving force • Discuss how requirements drive every development phase • Specifically learn how requirements influence data design • Review the impact of requirements on architecture • Note the special considerations for ETL and metadata • Examine how requirements shape information delivery The Architectural Components • Overall Architecture • Data Warehouse Database • Sourcing, Acquisition, Cleanup and Transformation Tools • Meta data • Data Marts • Data Warehouse Administration and Management Infrastructure as the Foundation for Data Warehousing • Understand the distinction between architecture and infrastructure • Find out how the data warehouse infrastructure supports its architecture • Gain an insight into the components of the physical infrastructure • Review hardware and operating systems for the data warehouse • Study parallel processing options as applicable to the data warehouse • Discuss the server options in detail • Learn how to select the DBMS • Review the types of tools needed for the data warehouse • Study the concept and use of data warehouse appliances The Significant Role of Metadata • Find out why metadata is so important • Understand who needs metadata and what types they need • Review metadata types by the three functional areas • Discuss business metadata and technical metadata in detail • Examine all the requirements metadata must satisfy • Understand the challenges for metadata management • Study options for providing metadata Principles of Dimensional Modelling • Clearly understand how the requirements definition determines data design • Introduce dimensional modelling and contrast it with entity-relationship modelling • Review the basics of the STAR schema • Find out what is inside the fact table and inside the dimension tables • Determine the advantages of the STAR schema for data warehouses Dimensional Modelling: Advanced Topics • Discuss and get a good grasp of slowly changing dimensions • Understand large dimensions and how to deal with them • Examine the snowflake schema in detail • Learn about aggregate tables and determine when to use them • Completely survey families of STARS and their application Data Extraction, Transformation, and Loading • Part I: When to build your data warehouse • Part II: Building a new schema • Part III: Location of your data warehouse The Physical Design Process in DWH • Distinguish between physical design and logical design as applicable to the data warehouse • Study the steps in the physical design process in detail • Understand physical design considerations and know the implications • Grasp the role of storage considerations in physical design • Examine indexing techniques for the data warehouse environment • Review and summarize all performance enhancement options • Matching Information to the Classes of Users OLAP in the Data Warehouse • OLAP (Online Analytical Processing) • Overview & Introduction • OLAP Cube • HISTORY of OLAP • OLAP Operations • DATAWAREHOUSE • ARCHITECHTURE Difference between OLAP & • OLTP & TYPES OF OLAP APPLICATIONS OF OLAP • Data Warehousing and the Web • Data Warehouse Deployment • Data Quality: A Key to Success • Data Mining Basics • Growth and Maintenance contact person: SUJITHA Venue Address: #st floor,Gandhi Road, Velachery Email Id:velgrotechnologies at gmail dot com info at velgrotechnologies dot com Website:www dot velgrotechnologies dot com

SequelGate is one of the best training institutes for Data Science & Big Data /Data Analytics Training. We have been providing Classroom and Online Trainings and Corporate training. All our training sessions are COMPLETELY PRACTICAL. DATA SCIENCE & BIG DATA/ DATA ANALYTICS TRAINING WITH PROJECT - ONLINE TRAINING COURSE DETAILS: Real time training on latest concepts related to Big Data Technologies: Hadoop – Modules, HDFS - Hadoop Distributed File System, PIG, HIVE, HBASE, SQOOP, OOZIEE, FLUME, Kafka, Spark/Scala, R –Language, and Python.This training course is exclusively designed addressing all practical aspects of Big Data concepts and implementing the real-time aspects. Material provided during the course. Data Science & Bigdata Analytics Overview HADOOP - Frame work for Big data HDFS Understanding the Cluster Map Reduce: PIG HIVE Hbase Cassandra Scala - Language for Data Science & Bigdata Scala Introduction &Environment Setup: Scala Basic Syntax Scala Data TYPES: Scala Variables: Scala Operators: Scala Conditions Scala Loops Scala Strings: Scala Regular Expressions: Scala Functions: Scala Arrays Scala Collections Scala Classes & Objects: SPark - Frame work for Data Science & Bigdata Analytics Spark Core Spark SQL Spark Streaming Spark GraphX SPARK Mlib STATISTICS STATISTICS: Descriptive & Inferential Statistics DESCRIPTIVE STATISTICS INFERENTIAL STATICS Data quality and outlier treatment Data Visualization. Cumulative Frequency plots Data Quality checking R–Lan/Python for Data Analytics Getting Started R Python Probability Graphics Machine Learning All Sessions are Completely Practical and Realtime. Duration: 4 Months, every day for 1.5 hours and all sessions are completely practical. One Real-time Project included in the course. For free Data Science Online Demo, please visit Contact us today for practical Data Science & Big Data /Data Analytics Online Training: Office: (+91) 040 65358866 Mobile: (+91) 0 9030040801  Sai Anu Avenue, Street No #3, Patrika Nagar, HITEC City, Hyderabad - 81 (India).