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BIG DATATraining @ObjectArena Chennai We at OBJECT ARENA offer advanced IBM courses as well as programming languages in the Industry designed for both fresher and corporate folks. Our courses are created to be the most effective with an objective to provide the best ROI possible. Courses range from taking an individual from introduction to certification, while advanced classes provide a test play ground to refresh their knowledge using intense break-it fix-it lab exercises. We balance lectures with extensive business case oriented intense labs along with daily computerized testing to gauge a student’s progress. Our goal is to provide the best ROI possible. ADVANTAGES Globally Recognized Program Structured & result-oriented training Interactive training session Certified Instructors from the Industry Industry standard Course Materials Industry Certification Frequently Asked questions Industry tour for top students Project exposure for top students Industry mentors for Top students Course content for Big Data BIG DATA - Simple Definition to the technology, 3 V’s of Big Data Big Data Use Cases -Social media, Log files etc., What can be done with the big data -Importance of big data, insights from the data, how is it associated in day-to-day life Big Data Architecture -Introduction to Hadoop, Pig, JAQL, Hive, Hbase, Zookeeper etc., Big data is not just hadoop -The complete picture of how it is done IBM’s proceedings in Big Data Platform -Introduction to BigInsights, InfoStreams etc., BigInsights -Explain about Big sheets (i.e., Live Demo) Text Analytics -Introduction and an example of the terminology Importance of the technology -Some statistical information about the shortage of employees with these skills Case Studies -Case studies in real time scenarios and the future of Big Data. Course content for hadoop Course Content Introduction and Overview of Hadoop What is Hadoop?  History of Hadoop Building Blocks – Hadoop Eco-System Who is behind Hadoop? What Hadoop is good for and what it is not Hadoop Distributed File System (HDFS) HDFS Overview and Architecture HDFS Installation Hadoop File System Shell File System Java API Map/Reduce Map/Reduce Overview and Architecture Installation Developing Map/Red Jobs Input and Output Formats Job Configuration Job Submission HDFS as a Source and Sink HBase as a Source and Sink Hadoop Streaming HBase HBase Overview and Architecture HBase Installation HBase Shell CRUD operations Scanning and Batching Filters HBase Key Design Pig Pig Overview Installation Pig Latin Pig with HDFS Hive  Hive Overview Installation Hive QL Sqoop Sqoop Overview Installation Imports and Exports Zoo Keeper  Zoo Keeper Overview Installation Server Mantainace Putting it all together Distributed installations Best Practices For further details: go through this url Object Arena Software Solutions.pvt.ltd Address:no 1 nehru street co-operative nagar adambakkam,chennai-(Off Velachery Inner ring road) phone: - prasanna:

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Transactions aren�t the only goal, creating knowledge-sharing networks is, based on the insights gained from big data analytics. �Big data is having an impact on organizations� reaction time to supply chain issues (41%), increased supply chain efficiency of 10% or greater (36%), and greater integration across the supply chain (36%). �Embedding big data analytics in operations leads to a 4.25x improvement in order-to-cycle delivery times, and a 2.6x improvement in supply chain efficiency of 10% or greater. �Big data has the potential to provide improved traceability performance and reduce the thousands of hours lost just trying to access, integrate and manage product databases that provide data on where products are in the field needing to be recalled or retrofitted. �Increasing supplier quality from supplier audit to inbound inspection and final assembly with big data. �The advertised salary for technical professionals with Big Data expertise is $ �net of bonuses and additional compensation. The most in-demand skills are VMWare expertise, application development, open source technology, data warehousing and Python programming skills. The Hiring Scale is 72 for jobs that require big data skills with 11 candidates per job opening as of June . � The enormity of big data is not confined to only volume and velocity; it is also referred by the variety, variability and complexity of the data. So it requires more than just some tweaks and upgrades for fully realising the potential of big data. � The big deal about big data analytics is the way organisations use it to leverage their business performance, innovate and provide better customer service �Analysing the big data, organisations can understand better what customers want and with the help of this, they can provide better after-sales service. 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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

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