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Bigdata Training in Chennai

Greens Technology, Rated As Best Bigdata training institute in Chennai. Hadoop is changing the view of taking care of Big Data particularly the unstructured information. How about we know how Apache Hadoop programming library, which is a structure, assumes a key part in taking care of Big Data.

Big data Hadoop training in Chennai with 10 real time industry oriented case study projects on HDFS, MapReduce, Sqoop, Flume, Hive, Pig, HBase, MongoDB, Oozie, Concepts of ETL/ELT, SQL Basic, Unix Basic Commands and prepares you for Cloudera CCA Spark and Hadoop Developer Certification (CCA175) as well as master Hadoop Administration.

bigdata training in chennai

In a few ways, Big data Hadoop is like a fine wine: It shows signs of improvement with age as unpleasant edges (or flavor profiles) are smoothed out, and the individuals who hold up to devour it will presumably have a superior affair.Our Hadoop training chennai review is given as positive by industry experts.

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Awarded as the Best Bigdata Training Center in Chennai - Located in Adyar, OMR, Velachery, Tambaram and Chennai,.



About Myself

Kumaran Ponnambalam has been working with data for more than 20 years.

Kumaran Ponnambalam is a Chief Data Scientist who works with Amazon Web Services and Google Cloud Platform, specializing in Hadoop development.

As a data scientist, he is skilled in optimizing queries and processing large data sets.

Kumaran Ponnambalam specializes in Hadoop projects. Kumaran Ponnambalam has worked with AWS Athena, Aurora, Redshift, Kinesis, and the IoT. He has also done production work with Databricks for Apache Spark and Google Cloud Dataproc, Bigtable, BigQuery, and Cloud Spanner.

In his current role at Amazon, he is working with the Hadoop development team. He specializes in writing and deploying data processing improvements. His accomplishments include programming enhanced metadata processing for A/B , optimizing jobs on a 1,000+ node cluster, and creating a distributed fault injection platform.

He has spoken on data and cloud technologies in North and South America, Europe, Africa, Asia, and Australia.

Flexible Timings / Weekend classes Available.



Talk to the Trainer @ +91-8939915577


What is Big Data Analytics

The field of

Big Data Analytics deal with Information aspects of data — which is voluminous, of multiple variety and which is getting generated aggressively. We can compare it to Arctic Ice. The data that is utilized in business systems is like the arctic ice that is seen above the surface which is tiny compared to what is below. Huge data is getting accumulated around the world from conventional IT systems and from the digital world where business goes beyond the boundary and marries with social networks.

Breaching social boundaries give birth to new data types-the data types becoming more of unstructured social chats to images in photos & videos to audios. This leads to yet another dimension of speed in which data engulfs the boundary less world.

These data convey a meaning when the context is understood and provide an insight when analyzed resulting in newer products, services and better perception of customers. Big data analytics not only enable business to grow faster but also benefit consumers by providing the best possible choice at the lowest cost.

Big Data Analytics is such an area that is attractive to both professionals who are already into IT to find more satisfying career as well as people who want to get into IT not to miss the lucrative opportunities in this space.

Whether you are a Business Analyst or Data Base Administrator in Information Technology, whether you are a Statistician or Economist who can make sense of data you have great opportunity in Big Data Analytics. If you are project manager or a project lead, Big Data projects are awaiting you. If you are a developer, development in Big data provides better scope.

If you are already in Information Technology providing solutions to customers by implementing products or supporting customer or a quality assurance professional with better sense of products and customers you should not miss big data bus opportunity. Architecting for Big data and Designing Big Data are skill areas requiring wider knowledge of tools and technologies with analytical understanding of business.

We can categorize the opportunities into three roles

  • (i) Big Data Analyst
  • (ii) Data Scientist and
  • (iii) Big Data Developer.
Big Data Analyst is a professional who is capable of understanding business, organize & analyze data from disparate sources and produce results for business using existing tools and technologies. Big Data Developer writes programs to create, integrate and interpret large data sets often using existing development environment or using custom tools in order that Big Data Analyst is able to generate required results for business.

Big Data Scientist is a role which requires predominantly analytical skills with deep sense of data and technology besides knowledge of various algorithms that can be exploited for analysis

Big Data Analyst is a critical role in Big Data projects. As the Big Data Analyst requires knowledge of business, existing Information Technology professionals can easily find an entry. Data Base Administrators with experience enterprise data bases can find their existing experience as a stepping stone to move into Big Data, as Big data projects deals with huge data often using several conventional and unconventional data bases. Most of the analysis involves statistics. People with reasonable background in statistics or mathematics can find their knowledge benefit-Ling entry into the lucrative field of Big Data.Econometrics another subject area knowledge where economics and mathematics come into play will be useful in several big data projects.

Mathematics required for analyst is not more than what is covered in mathematics as one of the subjects in graduate level while Higher Secondary level mathematics or statistics is good enough for highly motivated people entering into this career. Project Leads and Project Managers will find their management skills sought after for big data projects which are to be managed effectively to produce intended resu ltsIt is true that big data is a green pasture for people with various background referred above. But it is not so if they are not prepared for the career by acquiring skills that can complement their existing skills to become Big Data Analytics. Biggest mistake people do is to take up couple of days of training in popular tools such as Hadoop or MapReduce thinking that that would provide them a career in big data space.

Most of the time people spend in such programs is on learning about installing the tools and running one standard example which they can do without spending any money by simply downloading and following various guidance available on the net. At the end of such programs people come out with completely incorrect understanding of the big data application and often miss to recognize and capitalize on potential career opportunities.

An entry level career program should provide a refresher on statistics with the approach to impart 'statistical thinking' rather than listing dry formulae one after another. People should learn how to build models of various business scenarios and analyze using realistic data. They should know how to perform regression analysis, cluster analysis and Segmentation using Decision Trees. It is essential to learn how to build and validate predictive models for business problems and come out with solutions which can be visually communicated. Trainee should get a hang on how to exploit social media, mobile analytics and cloud that complement Big Data Analytics. Hands on experience should include popular open source tools such as Hadoop, MapReduce, Hive and R besides an appreciation of array of commercial tools. Training for less than 100 hours without extensive hand-on using business problems and realistic data will not provide necessary foundation required to enter into big data space.

Big data space is expected to provide accelerated career growth. One can make an entry into the field as Junior Big Data Analyst and graduate to become Senior Big Data Analyst. Experience as Big Data Analyst provides a platform to become Big Data Scientist based on aspiration and background of individuals.

Big data space is expected to provide accelerated career growth. One can make an entry into the field as Junior Big Data Analyst and graduate to become Senior Big Data Analyst. Experience as Big Data Analyst provides a platform to become Big Data Scientist based on aspiration and background of individuals.

  • Basic Unix Commands
  • Core Java (OOPS Concepts, Collections , Exceptions ) — For
  • Map-Reduce Programming
  • SQL Query knowledge – For Hive Queries

Introduction to Hadoop

  • High Availability
  • Scaling
  • Advantages and Challenges
  • What is Big data
  • Hadoop opportunities
  • Hadoop Challenges
  • Characteristics of Big data
  • Hadoop Distributed File System
  • Comparing Hadoop & SQL.
  • Industries using Hadoop.
  • Data Locality.
  • Hadoop Architecture.
  • Map Reduce & HDFS.
  • Using the Hadoop single node image (Clone).

The Hadoop Distributed File System (HDFS)

  • HDFS Design & Concepts
  • Blocks, Name nodes and Data nodes
  • HDFS High-Availability and HDFS Federation.
  • Hadoop DFS The Command-Line Interface
  • Basic File System Operations
  • Anatomy of File Read
  • Anatomy of File Write
  • Block Placement Policy and Modes
  • More detailed explanation about Configuration files.
  • Metadata, FS image, Edit log, Secondary Name Node and Safe Mode.
  • How to add New Data Node dynamically.
  • How to decommission a Data Node dynamically (Without stopping cluster).
  • FSCK Utility. (Block report).
  • How to override default configuration at system level and Programming level.
  • HDFS Federation.
  • ZOOKEEPER Leader Election Algorithm.
  • Exercise and small use case on HDFS.

Map Reduce

  • Functional Programming Basics.
  • Map and Reduce Basics
  • How Map Reduce Works
  • Anatomy of a Map Reduce Job Run
  • Legacy Architecture ->Job Submission, Job Initialization, Task Assignment, Task Execution, Progress and Status Updates
  • Job Completion, Failures
  • Shuffling and Sorting
  • Splits, Record reader, Partition, Types of partitions & Combiner
  • Optimization Techniques -> Speculative Execution, JVM Reuse an
  • Types of Schedulers and Counters.
  • Comparisons between Old and New API at code and Architecture Level.
  • Getting the data from RDBMS into HDFS using Custom data types.
  • Distributed Cache and Hadoop Streaming (Python, Ruby and R). YARN.
  • Sequential Files and Map Files.
  • Enabling Compression Codec’s.
  • Map side Join with distributed Cache.
  • Types of I/O Formats: Multiple outputs, NLINEinputformat.
  • Handling small files using CombineFileInputFormat.

Map/Reduce Programming – Java Programming

  • Hands on “Word Count” in Map/Reduce in standalone and Pseudo distribution Mode.
  • Sorting files using Hadoop Configuration API discussion
  • Emulating “grep” for searching inside a file in Hadoop
  • DBInput Format
  • Job Dependency API discussion
  • Input Format API discussion
  • Input Split API discussion
  • Custom Data type creation in Hadoop.

NOSQL

  • ACID in RDBMS and BASE in NoSQL.
  • CAP Theorem and Types of Consistency.
  • Types of NoSQL Databases in detail.
  • Columnar Databases in Detail (HBASE and CASSANDRA).
  • TTL, Bloom Filters and Compensation.

HBase

  • HBase Installation
  • HBase concepts
  • HBase Data Model and Comparison between RDBMS and NOSQL.
  • Master & Region Servers.
  • HBase Operations (DDL and DML) through Shell and Programming and HBase Architecture.
  • Catalog Tables.
  • Block Cache and sharding.
  • SPLITS.
  • DATA Modeling (Sequential, Salted, Promoted and Random Keys).
  • JAVA API’s and Rest Interface.
  • Client Side Buffering and Process 1 million records using Client side Buffering.
  • HBASE Counters.
  • Enabling Replication and HBASE RAW Scans.
  • HBASE Filters.
  • Bulk Loading and Coprocessors (Endpoints and Observers with programs).
  • Real world use case consisting of HDFS,MR and HBASE.

Hive

  • Installation
  • Introduction and Architecture.
  • Hive Services, Hive Shell, Hive Server and Hive Web Interface (HWI)
  • Meta store
  • Hive QL
  • OLTP vs. OLAP
  • Working with Tables.
  • Primitive data types and complex data types.
  • Working with Partitions.
  • User Defined Functions
  • Hive Bucketed Tables and Sampling.
  • External partitioned tables, Map the data to the partition in the table, Writing the output of one query to another table, Multiple inserts
  • Dynamic Partition
  • Differences between ORDER BY, DISTRIBUTE BY and SORT BY.
  • Bucketing and Sorted Bucketing with Dynamic partition.
  • RC File.
  • INDEXES and VIEWS.
  • MAPSIDE JOINS.
  • Compression on hive tables and Migrating Hive tables.
  • Dynamic substation of Hive and Different ways of running Hive
  • How to enable Update in HIVE.
  • Log Analysis on Hive.
  • Access HBASE tables using Hive.
  • Hands on Exercises

Pig

  • Installation
  • Execution Types
  • Grunt Shell
  • Pig Latin
  • Data Processing
  • Schema on read
  • Primitive data types and complex data types.
  • Tuple schema, BAG Schema and MAP Schema.
  • Loading and Storing
  • Filtering
  • Grouping & Joining
  • Debugging commands (Illustrate and Explain).
  • Validations in PIG.
  • Type casting in PIG.
  • Working with Functions
  • User Defined Functions
  • Types of JOINS in pig and Replicated Join in detail.
  • SPLITS and Multiquery execution.
  • Error Handling, FLATTEN and ORDER BY.
  • Parameter Substitution.
  • Nested For Each.
  • User Defined Functions, Dynamic Invokers and Macros.
  • How to access HBASE using PIG.
  • How to Load and Write JSON DATA using PIG.
  • Piggy Bank.
  • Hands on Exercises

SQOOP

  • Installation
  • Import Data.(Full table, Only Subset, Target Directory, protecting Password, file format other than CSV,Compressing,Control Parallelism, All tables Import)
  • Incremental Import(Import only New data, Last Imported data, storing Password in Metastore, Sharing Metastore between Sqoop Clients)
  • Free Form Query Import
  • Export data to RDBMS,HIVE and HBASE
  • Hands on Exercises.

HCATALOG.

  • Installation.
  • Introduction to HCATALOG.
  • About Hcatalog with PIG,HIVE and MR.
  • Hands on Exercises.

FLUME

  • Installation
  • Introduction to Flume
  • Flume Agents: Sources, Channels and Sinks Avro Source
  • Log User information using Java program in to HDFS using Tail Source
  • Log User information using Java program in to HBASE using LOG4J and Avro Source
  • Log User information using Java program in to HBASE using Tail Source
  • Flume Commands
  • Use case of Flume: Flume the data from twitter in to HDFS and HBASE. Do some analysis using HIVE and PIG

More Ecosystems

  • HUE.(Hortonworks and Cloudera).

Oozie

  • Workflow (Action, Start, Action, End, Kill, Join and Fork), Schedulers, Coordinators and Bundles.
  • Workflow to show how to schedule Sqoop Job, Hive, MR and PIG.
  • Real world Use case which will find the top websites used by users of certain ages and will be scheduled to run for every one hour.
  • Zoo Keeper
  • HBASE Integration with HIVE and PIG.
  • Phoenix
  • Proof of concept (POC).

SPARK

  • Overview
  • Linking with Spark
  • Initializing Spark
  • Using the Shell
  • Resilient Distributed Datasets (RDDs)
  • Parallelized Collections
  • External Datasets
  • RDD Operations
  • Basics, Passing Functions to Spark
  • Working with Key-Value Pairs
  • Transformations
  • Actions
  • RDD Persistence
  • Which Storage Level to Choose?
  • Removing Data
  • Shared Variables
  • Broadcast Variables
  • Accumulators
  • Deploying to a Cluster
  • Unit
  • Migrating from pre-1.0 Versions of Spark
  • Where to Go from Here


Greens Technology Reviews given by our students already completed the training with us. Please give your feedback as well if you are a student.

Bigdata training in Velachery Reviews from our Students

Bigdata training chennai

Kumaran Ponnambalam Prabhakar j! I am really delighted about the Bigdata course and i am surprised to see the depth of your knowledge in all aspects of the software . I see that many architects with over 15+ yrs experience doesn't have the knowledge that you have. I really enjoyed your sessions, definitely look forward to learn more from you in the future. Thanks again.""

Best Bigdata training institute in Adyar

Bigdata training chennai

Friends I am from Mechaniacl background having 6+ years experienced. I planned to Move into Bigdata. I Came to know about Greens technologies and Kumaran Ponnambalam who is working in Bigdata. They Really helped me to clear the interview. Thanks to Kumaran Ponnambalam Sir. Knowledgeable Presenters, Professional Materials, Excellent Support" what else can a person ask for when acquiring a new skill or knowledge to enhance their career. Greens Technology true to its name is the place to gather,garner and garden the knowledge for all around the globe. My Best wishes to Greens Technology team for their upcoming bright future in IT sector.

Best Bigdata training center in OMR

Bigdata training in chennai

" I am glad to have taken complete Bigdata course in Greens Technologys. It helped me a lot in understanding various concepts before which I was depending on many other sources. I will recommend this Bigdata course to beginners as well as experienced developers / Testers to attend the courses offered by Kumaran Ponnambalam @ Greens Technologies Adyar. The course curriculum is meticulously prepared and also followed without any compromise. Thus, the beginners can understand how to begin learning a vast technology without any confusion. In my case, attending this course, helped me firstly how to learn the subject in a different approach (understandings basics level to in depth concepts), instead of rushing through various text books or online sources. Kumaran Ponnambalam explains every concept in a very interesting way and it always creates an excitement in learning more about Bigdata. Moreover the material, notes from training also helps us prepare for interviews, certification, real time projects as well.

Learn Bigdata Training In Chennai From The Experts!

Looking for best Bigdata training in Chennai, Greens Technology is the no 1 Bigdata Training institute in Chennai offering placement focused Bigdata course by Bigdata experts. Call +91 89399-15577 for more details.


Bigdata Training in Chennai

Our Reviews 5 Star Rating: Recommended - Best IT Training in Chennai

5  out of 5  based on 12263 ratings.

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Bigdata Training in Chennai

Highlights of Bigdata Training

  • The presence of experts in Bigdata real time as the training faculty.
  • Provides the best learning environment.
  • Limited students per each batch.
  • Faculty’s interaction with each and every student for the better subject retention.
  • Well, affordable Course Fee.

Bigdata Training in Chennai

Adyar

No.11 , First Street ,
Padmanabha Nagar , Adyar ,
Chennai-600 020.

OMR

No.19, Balamurugan Garden, OMR Road, Thoraipakkam,
Kancheepuram (DT).

Velachery

No.28, Nagendra Nagar, Opposite Phoenix Mall, Velachery, Chennai - 600 042.

Tambaram

No.1, Appa Rao colony,
Tambaram,
Sanatorium,
Chennai - 600 047.

Anna Nagar

SDV Arcade
4th floor, AB-5, 2nd Ave, Anna Nagar, Chennai - 600 040.


Bigdata Training in Chennai




Greens Technologys Overall Reviews


Greens Technologys Overall Reviews

5 out of 5 based on 17,981 ratings. 17,981 user reviews.

Bigdata Training in Chennai
best Bigdata training center in chennai

"I thought I knew Bigdata until I took this course. My company sent me here against my will. It was definitely worth and I found out how many things I was doing wrong. Karthik is awesome. but i got a lot inspired by you. I will keep in touch and will always try to learn from you as much as I can. Thanks once again Karthik"


Bigdata training in chennai

"Extremely positive!. This could summarize my experience with this institute for Bigdata. Karthik is sprit filled teacher. It was surprising to see him bother so much to make us understand simple mathematical problems which are related to Bigdata, particularly we were impressed when we came across concepts such as Linear Discriminant Analysis / Principal Component Analysis where he gave us geometric understanding of these concepts for the first time in 6 years (after my college) I was able to understand what is eigen Value / eigen Vector. He is expert in Bigdata with vast experience combined with his enthusiasm he has for a teaching makes the experience very pleasant. It was rigorous session. I would recommend Greens Technology for Bigdata."


Bigdata training classes in chennai

"This is one of very few places where our expectation (from reviews) meets reality. The quality of the content and the Content delivery style is top notch. The quality of knowledge one will be able to earn from Karthik creates a benchmark in one’s career provided the learner is willing to delve into Bigdata / Hadoop. Worth every penny and time that we spent in Greens Technology. He is an optimistic Trainer would repeat class if we didn’t understand even the simple mathematical concepts. Karthik is Passionate about explaining Bigdata to non-technical business audiences that makes the classes more enjoyable"


Bigdata training in Chennai Reviews from Urvashi


Bigdata training in chennai

I’m glad to have taken Bigdata Training under Mr. Karthik. When I approached Greens Technology I was a Junior data Analyst, so I could say I know a thing or two about Bigdata at least that was the perception I carried into the class, but as sessions progressed I could see what ever little knowledge I had was completely exhausted in first 4 classes of Mr. Karthik. He is an IIT grad and expect nothing short of amazing class experience which is very helpful for students, at the end I had participated in online hackathon events for Bigdata and even won 5th position in those competition. I’m now a successful Data Analyst with 2+ years of experience.


Bigdata training in Chennai Reviews from Chetan


Bigdata training in chennai

I’m a business analyst working in insurance sector, I was looking for Machine learning course with good number of algorithms and insight into mathematical concepts from statistics and numerical analysis. Fortunately, I came across Greens Technologys, Course Instructor was Karthik he is a through professional the way he conducted class was inspiring, content was comprehensive and when it came for Machine learning I had apprehension for mathematical understanding. But he took care of that problem his approach was simple and effective he gave us a geometrical insight for algebra (for PCA, LDA) and we had a mini project session at the end of our class, where we had to do analysis of employee churn ratio. I’m not working in R as well as Python implementing customer segmentation for our client. I would gladly recommend anyone to take machine learning with R/ Python in Greens Technology.


Bigdata training chennai

"Friends I’m from SQL background with 8+ years of experience, I had planned to move into Analytics department, when I was looking for various training institutes to take course on R with Bigdata I came to know about Greens Technology Adayar and Karthik who is the course instructor. The way he took sessions was inspiring us to learn further in R and machine Learning. No wonder with such intellect his class did wonders to us, I even got great insights from him regarding data scientist job interviews. His class and materials which he shared is of great knowledge base. Using those materials and capstone projects I could clear interviews and I’m a data scientist for almost two years. This move was defining moment for a better change in my career."


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Greens Technologys Overall Reviews


Greens Technologys Overall Reviews 5 out of 5 based on 17981 ratings. 17981 user reviews.