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VirtualNuggets is an Online Training Company, Which Offers a Live instructor-Led Training in IBM API Connect to global Students and job Change Employee's. VirtualNuggets is Provide Job Support for IBM API Connect Technology. The Training Can is done in Week days, Week end and Fast Track by Professional Working Expert’s. IBM API Connect is a complete API lifecycle management solution that will make things easier for developers, Central IT, and LoB Management. The thought behind API Connect is that APIs are small data applications, often called micro services, but they are applications nonetheless. The steps of the API lifecycle include creating, running, managing, and securing APIs. With API Connect, you can perform all of the life cycle steps in a single integrated offering, removing the requirement to use multiple API management offerings to obtain the same capability. Training Highlights: • Practical Oriented Approach • Access to the Recorded Sessions • Learn from Certified and Expert Trainers • Customized Course content as per your requirement For More information on IBM API Connect Email : info(at)VirtualNuggets(dot)com Contact : +1 707 666 8949(USA) +91 888 556 0202(India – Whatsapp) Web URL : http://www.virtualnuggets.com/ibm-api-connect.html

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Big Data Revolution' studies the effect of number-crunching on business http://bit.ly/1JTv5im Big data paves the way for big building and engineering projects BigData Training.in has today grown to be amongst world�s leading talent development companies offering learning solutions to Individuals, Institutions & Corporate Clients. India�s Leading BigData Consulting & Training Experts Visit Us: #67, 2nd Floor, Gandhi Nagar 1st Main Road, Adyar, Chennai-20 To register for upcoming classes weekends(Classroom) April - Fast Track (Classroom)- April

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Hadoop for Developers and Administrators Hadoop for Developers and Administrators Syllabus COURSE CONTENT Traning at hadoop school of training Magarpatta city Pune. (+91-93257-93756) www.hadoopschooloftraining.co.in Next level of development and administration Schedule: Day 1:BigData • Why is Big Data important • What is Big Data • Characteristics of Big Data • How did data become so big • Why should you care about Big Data • Use Cases of Big Data Analysis • What are possible options for analyzing big data • Traditional Distributed Systems • Problems with traditional distributed systems • What is Hadoop • History of Hadoop • How does Hadoop solve Big Data problem • Components of Hadoop • What is HDFS • How HDFS works • What is Mapreduce • How Mapreduce works • How Hadoop works as a system Day2: Hadoop ecosystem • Pig • What is Pig • How it works • An example • Hive • What is Hive • How it works • An example • Flume • What is Flume • How it works • An example • Sqoop • What is Sqoop • How it works • An example • Oozie • What is Oozie • How it works • An example • HDFS in detail • Map Reduce in details Day3: Hands On-¬‐ • VMsetup • Setting up Virtual Machine • Installing Hadoop in Pseudo Distributed mode Day 4: Hands On-¬‐ • Programs • Running your first MapReduce Program • Sqoop Hands on • Flume Hands Day 5: • Multinode cluster setup • Setting up a multimode cluster Day 6: • Planning your Hadoop cluster • Considerations for setting up Hadoop Cluster • Hardware considerations • Software considerations • Other considerations Day 7: Disecting the Wordcount Program • Understanding the Driver • Understanding the Mapper • Understanding the Reducer Day 8: • Diving deeper into MapReduce • API • Understanding combiners • Understanding partitioners • Understanding input formats • Understanding output formats • Distributed Cache • Understanding Counters Day 9: • Common Mapreduce patterns • Sorting Serching • Inverted Indexes Day 10: • Common Mapreduce patterns • TF-IDF • Word-Cooccurance Day 11: • Hands on Mapreduce Day 12: • Hands on Mapreduce Day 13: • Introduction to Pig and Hive • Pig program structure and execution process • Joins • Filtering • Group and Co-Group • Schema merging and redefining schema • Pig functions • Motivation and Understanding Hive • Using Hive Command line Interface • Data types and File Formats • Basic DDL operations • Schema Design Day 14: • Hands on Hive and Pig Day 15: • Advanced Hadoop Concepts • Yarn • Hadoop Federation • Authntication in Hadoop • High Availbability Day 16: • Administration Refresher • Setting up hadoop cluster - Considerations • Most important configurations • Installation options Day 17: • Scheduling in Hadoop • FIFO Scheduler • Fair Scheduler Day 18: • Monitoring your Hadoop Cluster • Monitoring tools available • Ganglia • Monitoring best practices Day 19: • Administration Best practices • Hadoop Administration best practices • Tools of the trade Day 20: • Test • Test – 50 questions test (20- Development releated, 20- • Administration related and 10 Hadoop in General Please Contact- Hadoop School of Training Destination Center, Second Floor Magarpatta City Pune: 411013 Phone: India: +91-93257-93756 USA: 001-347-983-8512 www.hadoopschooloftraining.co.in Email: learninghub01@gmail.com Skype: learning.hub01

With 2.6 quintillion bytes of data being produced on a daily basis, there is a fast growing need of big data & Hadoop training to nurture professionals who can manage and analyse massive (tera/petabytes) data-sets to bring out business insights. To do this requires specialized knowledge on various tools like the Hadoop ecosystem. Through this big data & Hadoop training course, the participants will gain all the skills requisite to be a Hadoop Developer. The participant will learn the installation of Hadoop cluster, understand the basic and advanced concepts of Map Reduce tools used by Big Data analysts like Pig, Hive, Flume, Sqoop and Oozie. The course will train you towards global certifications offered by Cloudera, Hortonworks etc. The course will be very useful for engineers and software professionals with a programming background. HADOOP Online Training by Peopleclick with an excellent and real time faculty. Our Hadoop Big Data course content designed as per the current IT industry requirement. Apache Hadoop is having very good demand in the market, huge number of job openings are there in the IT world. We provide regular and weekend classes as well as Normal track/Fast track based on the learners requirement and availability. As all our faculty is real time professionals our trainer will cover all the real time scenarios. We have trained many students on Apache Hadoop Big Data, We provide Corporate Trainings and Online trainings throughout the world. We will give you 100% satisfaction guarantee, After completion of Hadoop Training we provide days technical support for required candidates. We will provide 100% certification support, resume preparation and Placements. HADOOP ONLINE TRAINING COURSE CONTENT: We provide both Hadoop Development and Admin Training. 1. INTRODUCTION What is Hadoop? History of Hadoop Building Blocks – Hadoop Eco-System Who is behind Hadoop? What Hadoop is good for and why it is Good 2. HDFS Configuring HDFS Interacting With HDFS HDFS Permissions and Security Additional HDFS Tasks HDFS Overview and Architecture HDFS Installation Hadoop File System Shell File System Java API 3. MAPREDUCE Map/Reduce Overview and Architecture Installation Developing Map/Red Jobs Input and Output Formats Job Configuration Job Submission Practicing Map Reduce Programs (atleast 10 Map Reduce Algorithms) 4. Getting Started With Eclipse IDE Configuring Hadoop API on Eclipse IDE Connecting Eclipse IDE to HDFS 5. Hadoop Streaming 6. Advanced MapReduce Features Custom Data Types Input Formats Output Formats Partitioning Data Reporting Custom Metrics Distributing Auxiliary Job Data 7. Distributing Debug Scripts 8.Using Yahoo Web Services 9. Pig Pig Overview Installation Pig Latin Pig with HDFS 10. Hive Hive Overview Installation Hive QL Hive Unstructured Data Analyzation Hive Semistructured Data Analyzation 11.HBase HBase Overview and Architecture HBase Installation HBase Shell CRUD operations Scanning and Batching Filters HBase Key Design 12.ZooKeeper Zoo Keeper Overview Installation Server Mantainace 13.Sqoop Sqoop Overview Installation Imports and Exports 14.CONFIGURATION Basic Setup Important Directories Selecting Machines Cluster Configurations Small Clusters: 2-10 Nodes Medium Clusters: Nodes Large Clusters: Multiple Racks 15.Integrations 16.Putting it all together Distributed installations Best Practices Benefits of taking the Hadoop & Big Data course •Learn to store, manage, retrieve and analyze Big Data on clusters of servers in the cloud using the Hadoop eco-system •Become one of the most in-demand IT professional in the world today •Don't just learn Hadoop development but also learn how to analyze large amounts of data to bring out insights •Relevant examples and cases make the learning more effective and easier •Gain hands-on knowledge through the problem solving based approach of the course along with working on a project at the end of the course Who should take this course? This course is designed for anyone who: •wants to architect a big data project using Hadoop and its Eco System components •wants to develop Map Reduce programs to handle enormous amounts of data •you have a programming background and want to take your career to another level Pre-requisites •The participants need basic knowledge of core Java for this course. (If you do not have Java knowledge, then do not worry. We provide you with our 'Java Primer for Hadoop' course complimentary with this course so that you can learn the requisite Java skills) •Any experience of Linux environment will be helpful but is not necessary

With 2.6 quintillion bytes of data being produced on a daily basis, there is a fast growing need of big data & Hadoop training to nurture professionals who can manage and analyse massive (tera/petabytes) data-sets to bring out business insights. To do this requires specialized knowledge on various tools like the Hadoop ecosystem. Through this big data & Hadoop training course, the participants will gain all the skills requisite to be a Hadoop Developer. The participant will learn the installation of Hadoop cluster, understand the basic and advanced concepts of Map Reduce tools used by Big Data analysts like Pig, Hive, Flume, Sqoop and Oozie. The course will train you towards global certifications offered by Cloudera, Hortonworks etc. The course will be very useful for engineers and software professionals with a programming background. HADOOP Online Training by Peopleclick with an excellent and real time faculty. Our Hadoop Big Data course content designed as per the current IT industry requirement. Apache Hadoop is having very good demand in the market, huge number of job openings are there in the IT world. We provide regular and weekend classes as well as Normal track/Fast track based on the learners requirement and availability. As all our faculty is real time professionals our trainer will cover all the real time scenarios. We have trained many students on Apache Hadoop Big Data, We provide Corporate Trainings and Online trainings throughout the world. We will give you 100% satisfaction guarantee, After completion of Hadoop Training we provide days technical support for required candidates. We will provide 100% certification support, resume preparation and Placements. HADOOP ONLINE TRAINING COURSE CONTENT: We provide both Hadoop Development and Admin Training. 1. INTRODUCTION What is Hadoop? History of Hadoop Building Blocks – Hadoop Eco-System Who is behind Hadoop? What Hadoop is good for and why it is Good 2. HDFS Configuring HDFS Interacting With HDFS HDFS Permissions and Security Additional HDFS Tasks HDFS Overview and Architecture HDFS Installation Hadoop File System Shell File System Java API 3. MAPREDUCE Map/Reduce Overview and Architecture Installation Developing Map/Red Jobs Input and Output Formats Job Configuration Job Submission Practicing Map Reduce Programs (atleast 10 Map Reduce Algorithms) 4. Getting Started With Eclipse IDE Configuring Hadoop API on Eclipse IDE Connecting Eclipse IDE to HDFS 5. Hadoop Streaming 6. Advanced MapReduce Features Custom Data Types Input Formats Output Formats Partitioning Data Reporting Custom Metrics Distributing Auxiliary Job Data 7. Distributing Debug Scripts 8.Using Yahoo Web Services 9. Pig Pig Overview Installation Pig Latin Pig with HDFS 10. Hive Hive Overview Installation Hive QL Hive Unstructured Data Analyzation Hive Semistructured Data Analyzation 11.HBase HBase Overview and Architecture HBase Installation HBase Shell CRUD operations Scanning and Batching Filters HBase Key Design 12.ZooKeeper Zoo Keeper Overview Installation Server Mantainace 13.Sqoop Sqoop Overview Installation Imports and Exports 14.CONFIGURATION Basic Setup Important Directories Selecting Machines Cluster Configurations Small Clusters: 2-10 Nodes Medium Clusters: Nodes Large Clusters: Multiple Racks 15.Integrations 16.Putting it all together Distributed installations Best Practices Benefits of taking the Hadoop & Big Data course •Learn to store, manage, retrieve and analyze Big Data on clusters of servers in the cloud using the Hadoop eco-system •Become one of the most in-demand IT professional in the world today •Don't just learn Hadoop development but also learn how to analyze large amounts of data to bring out insights •Relevant examples and cases make the learning more effective and easier •Gain hands-on knowledge through the problem solving based approach of the course along with working on a project at the end of the course Who should take this course? This course is designed for anyone who: •wants to architect a big data project using Hadoop and its Eco System components •wants to develop Map Reduce programs to handle enormous amounts of data •you have a programming background and want to take your career to another level Pre-requisites •The participants need basic knowledge of core Java for this course. (If you do not have Java knowledge, then do not worry. We provide you with our 'Java Primer for Hadoop' course complimentary with this course so that you can learn the requisite Java skills) •Any experience of Linux environment will be helpful but is not necessary For Further query call us @ or

Through this big data & Hadoop training course, the participants will gain all the skills requisite to be a Hadoop Developer. The participant will learn the installation of Hadoop cluster, understand the basic and advanced concepts of Map Reduce tools used by Big Data analysts like Pig, Hive, Flume, Sqoop and Oozie. The course will train you towards global certifications offered by Cloudera, Hortonworks etc. The course will be very useful for engineers and software professionals with a programming background. HADOOP Online Training by Peopleclick with an excellent and real time faculty. Our Hadoop Big Data course content designed as per the current IT industry requirement. Apache Hadoop is having very good demand in the market, huge number of job openings are there in the IT world. We provide regular and weekend classes as well as Normal track/Fast track based on the learners requirement and availability. As all our faculty is real time professionals our trainer will cover all the real time scenarios. We have trained many students on Apache Hadoop Big Data, We provide Corporate Trainings and Online trainings throughout the world. We will give you 100% satisfaction guarantee, After completion of Hadoop Training we provide days technical support for required candidates. We will provide 100% certification support, resume preparation and Placements. HADOOP ONLINE TRAINING COURSE CONTENT: We provide both Hadoop Development and Admin Training. 1. INTRODUCTION What is Hadoop? History of Hadoop Building Blocks – Hadoop Eco-System Who is behind Hadoop? What Hadoop is good for and why it is Good 2. HDFS Configuring HDFS Interacting With HDFS HDFS Permissions and Security Additional HDFS Tasks HDFS Overview and Architecture HDFS Installation Hadoop File System Shell File System Java API 3. MAPREDUCE Map/Reduce Overview and Architecture Installation Developing Map/Red Jobs Input and Output Formats Job Configuration Job Submission Practicing Map Reduce Programs (atleast 10 Map Reduce Algorithms) 4. Getting Started With Eclipse IDE Configuring Hadoop API on Eclipse IDE Connecting Eclipse IDE to HDFS 5. Hadoop Streaming 6. Advanced MapReduce Features Custom Data Types Input Formats Output Formats Partitioning Data Reporting Custom Metrics Distributing Auxiliary Job Data 7. Distributing Debug Scripts 8.Using Yahoo Web Services 9. Pig Pig Overview Installation Pig Latin Pig with HDFS 10. Hive Hive Overview Installation Hive QL Hive Unstructured Data Analyzation Hive Semistructured Data Analyzation 11.HBase HBase Overview and Architecture HBase Installation HBase Shell CRUD operations Scanning and Batching Filters HBase Key Design 12.ZooKeeper Zoo Keeper Overview Installation Server Mantainace 13.Sqoop Sqoop Overview Installation Imports and Exports 14.CONFIGURATION Basic Setup Important Directories Selecting Machines Cluster Configurations Small Clusters: 2-10 Nodes Medium Clusters: Nodes Large Clusters: Multiple Racks 15.Integrations 16.Putting it all together Distributed installations Best Practices Benefits of taking the Hadoop & Big Data course •Learn to store, manage, retrieve and analyze Big Data on clusters of servers in the cloud using the Hadoop eco-system •Become one of the most in-demand IT professional in the world today •Don't just learn Hadoop development but also learn how to analyze large amounts of data to bring out insights •Relevant examples and cases make the learning more effective and easier •Gain hands-on knowledge through the problem solving based approach of the course along with working on a project at the end of the course Who should take this course? This course is designed for anyone who: •wants to architect a big data project using Hadoop and its Eco System components •wants to develop Map Reduce programs to handle enormous amounts of data •you have a programming background and want to take your career to another level Pre-requisites •The participants need basic knowledge of core Java for this course. (If you do not have Java knowledge, then do not worry. We provide you with our 'Java Primer for Hadoop' course complimentary with this course so that you can learn the requisite Java skills) •Any experience of Linux environment will be helpful but is not necessary

Hadoop Develoment Course Contents: Big Data Concepts: 1.What is Big Data 2.How it differs from traditional data 3.Characteristics of big data Hadoop: 1.Overview 2.Components of Hadoop 3.Performance and scalability 4.Hadoop in the context of other data stores 5.Differences between noSQL and Hadoop Unix: 1.installation 2.Basic commands 3.Users and groups Hadoop installations: 1.Standalone mode 2.Pseudo distributed mode HDFS: 1.Architecture 2.Configuring HDFS 3.Blocks, name node and data nodes 4.Job tracker and task tracker 5.Hadoop fs command line interace 6.Basic file system operations & file system api 7.Executing default map reduce examples in hadoop MapReduce: 1.What is MapReduse and how it works 2.Configuring eclipse with Hadoop 3.Mapper, reducer and driver 4.Serialization 5.Custom writable implementation examples in java 6.Input formats 7.Output formats 8.Counters 9.Writing custom counters in java 10.Streaming 11.Sorting (partial, total and secondary) 12.Joins (map side and reduce side joins) 13.No reducer programs 14.Programs in map reduce Hive 1.What is Hive 2.How is data organizes in Hive 3.Data units 4.Data types 5.Operators and functions 6.Creation of tables and partitions 7.Loading the data into HDFS 8.Partition based query 9.Joins 10.Aggregations 11.Multi Tables file inserts 12.Arrays, maps, union all 13.Altering and dropping tables 14.Custom map reduce scripts HBase 1.Zookeeper 2.Data organization in hbase 3.Creating, altering, dropping, inserting the data 4.Joins, Aggregations 5.Custom map reduce scripts 6.Integration of HBase, hive and Hadoop Hadoop Adminstration: The following are common from the above course BigData concepts, Hadoop, unix, Hadoop installations, HDFS. Mapreduce (introduction only) Extra concepts: 1.Hadoop fully distributed mode installation 2.Execution of map reduce programs in fully distributed mode 3.Job scheduling with oozie 4.Monitoring with nagios 5.Logging with Flume 6.Data transfer from other RDBMS using Sqoop Contact us for more details ELEGANT IT SERVICES

Mule Introduction •Need of ESB and how it helps resolve the existing problems. •What is Mule and its Features •What is Any point Studio in Mule Developing Applications using Anypoint Studio •Creating Mule Applications Using Any point Studio. •Mule Expression Language Basics. •Understanding of Mule Flow, sub flow, Transformers, filters Message processors, inbound and Outbound Endpoints MUnit Testing •Understanding of MUnit and various asserts. •Creating MUnit flows. •Creating mocks in MUnit. Filters &Mule Message: •Understanding about various filters •Payload type •filter Expression •filter,Regex filter •Regex filter •Wildcard filter •And- Filter, Or-filter etc… •Mule Message Structure in Detail. Web Services •Understanding Restful and SOAP web services •Creating and Exposing Restful webservice using Java Component •Developing Restful services using RAML is and how it can be used •Consuming Restful web services with and without RAML definitions •Developing and Consuming SOAP web services Connecting to Additional Resources •Connecting to files, •databases, and •JMS queues •Connecting to SaaS applications Data Weave data transformation Language •Writing Data Weave expressions •Adding Sample data to view •Previewing transformations in studio •Externalizing Data weave expressions into DWL file •Writing Expressions for XML, JSON and JAVA •Writing Expressions for transforming XML to Json and viceversa •Using Message Variables in DWL •Creating multiple transformations to create Flow variables, Session variables and Outbound properties in Transform Message transformer •Transforming complex data structures using DWL •Working with collections in DWL using map operator Exception Handling •What happens when exception happens in a flow? •How to handle System Exceptions? •What is reconnection strategy ? •Default Exception Strategy •Catch Exception Strategy •Rollback Exception Strategy •Reference Exception Strategy •Choice Exception Strategy Routing, Spliiter and Aggregators •Choice router •Scatter- Gather router •How Splitter and Aggregators works Processing Records •Processing items in a collection individually •Understanding what batch jobs are and when to use them •Creating batch jobs to process items in a CSV file or a database •Restricting record processing to new records Building Restful Interfaces with Any point Platform for APIs •Understanding the benefits of Restful APIs and web services •Using the API Designer to define APIs with RAML •Implementing a RAML file as a Restful web service with Any point Studio and APIkit

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As big data becomes big business, IT has the opportunity to add value by finding new insights in unstructured data.� Hadoop, a distributed, reliable processing and storage framework for very large data sets, is one of the most valuable tools for mining big data. In this deep dive, find out how Hadoop works and reap its benefits. BigData Training.in has today grown to be amongst world�s leading talent development companies offering learning solutions to Individuals, Institutions & Corporate Clients. India�s Leading BigData Consulting & Training Experts Visit Us: #67, 2nd Floor, Gandhi Nagar 1st Main Road, Adyar, Chennai-20 To register for upcoming classes weekends(Classroom) April - Fast Track (Classroom)- April