TECHWOOD NETWORKS ACADEMY BIG DATA

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TECHWOOD NETWORKS

ACADEMY BIG DATA

Learning | Training | Internship | Project | Placement


Dear Sir/Madam, Greetings!!! We have designed this program for Science, Engineering & IT, Students & Experienced Professional for their training in the latest technologies like Big data/Hadoop, Spark Scala. These technologies are used by various relevant companies in their functioning, with sufficient training in these technologies, students have an upper hand in the recruitment process as well in the future. In the process of the training, we will undertake both theories as well as practical sessions for the students so that they have both conceptual and practical knowledge. Most of the sessions are based on practical.

Thanks & Regards, Techwood Networks Academy


What is BIG DATA/Hadoop?

About Industry – Big data & Data Science are buzzing words in the IT industry for the past few years. There is a huge demand for Hadoop Bigdata in the market. The demand for Hadoop is increasing because data is increasing at a high rate. Only in 2020 Big data/Hadoop, demand increased sharply by 28% in the industry. About Technology – Big data / Hadoop is a highly demanding open-source technology. Big data is a concept and Hadoop is a framework to manage Big data. It can store and process unlimited data in parallel.

Why BIG DATA?

Big Data! A Worldwide Problem? According to Wikipedia, “Big data is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.” In simpler terms, Big Data is a term given to large volumes of data that organizations store and process. However, it is becoming very difficult for companies to store, retrieve and process the ever-increasing data. If any company gets hold on managing its data well, nothing can stop it from becoming the next BIG success! The problem lies in the use of traditional systems to store enormous data. Though these systems were a success a few years ago, with the increasing amount and complexity of data, these are soon becoming obsolete. The good news is - Hadoop, which is not less than a panacea for all those companies working with BIG DATA in a variety of applications has become an integral part of storing, handling, evaluating, and retrieving hundreds or even petabytes of data.


Apache Hadoop! A Solution for Big Data! Hadoop is an open-source software framework that supports data-intensive distributed applications. Hadoop is licensed under the Apache v2 license. It is therefore generally known as Apache Hadoop. Hadoop has been developed, based on a paper originally written by Google on MapReduce system and applies concepts of functional programming. Hadoop is written in the Java programming language and is the highest-level Apache project being constructed and used by a global community of contributors. Hadoop was developed by Doug Cutting and Michael J. Cafarella and just don’t overlook the charming yellow elephant you see, which is named after Doug’s son’s toy elephant! Some of the top companies using Hadoop – The importance of Hadoop is evident from the fact that there are many global MNCs that are using Hadoop and consider it as an integral part of their functioning, such as companies like Yahoo and Facebook! On February 19, 2008, Yahoo! Inc. established the world's largest Hadoop production application. The Yahoo! Search Web map is a Hadoop application that runs on over 10,000 core Linux clusters and generates data that is now widely used in every Yahoo! Web search query. Facebook, a $5.1 billion company has over 1 billion active users in 2012, according to Wikipedia. Storing and managing data of such magnitude could have been a problem, even for a company like Facebook. But thanks to Apache Hadoop! Facebook uses Hadoop to keep track of every profile it has on it, as well as all the data related to them like their images, posts, comments, videos, etc.


Big Data Career Opportunities

Opportunities for Hadoopers are infinite - from a Hadoop Developer to a Hadoop Tester or a Hadoop Architect, and so on. If cracking and managing BIG Data is your passion in life, then think no more and Join Techwood Networks and carve a niche for yourself! ➢ Big Data & Data Science is used in every industry.

➢ Offers high salaries as compare to other technologies.

➢ Better career opportunities.

➢ The exponential growth of the Big data & data science market.

Important References

https://special.siliconindia.com/viewpoint/cxoinsights/big-

data-analytics-market-future-scope-in-india-nwid-

8846.html#:~:text=The%20Big%20Data%20Analytics%20market,in

%20the%20overall%20global%20market.

https://cio.economictimes.indiatimes.com/news/big-data/big-

data-analytics-to-become-16-billion-industry-by-

2025/59418465

https://economictimes.indiatimes.com/tech/ites/big-data-

analytics-to-become-16-billion-industry-by-

2025/articleshow/59410695.cms?from=mdr

https://special.siliconindia.com/viewpoint/cxoinsights/big-data-analytics-market-future-scope-in-india-nwid-8846.html#:~:text=The%20Big%20Data%20Analytics%20market,in%20the%20overall%20global%20market




https://cio.economictimes.indiatimes.com/news/big-data/big-data-analytics-to-become-16-billion-industry-by-2025/59418465



https://economictimes.indiatimes.com/tech/ites/big-data-analytics-to-become-16-billion-industry-by-2025/articleshow/59410695.cms?from=mdr




Job Opportunities

https://www.northeastern.edu/graduate/blog/highest-paying-big-data-careers/

https://www.naukri.com/big-data-jobs

https://in.linkedin.com/jobs/big-data-analytics-jobs

https://timesofindia.indiatimes.com/business/india-business/big-4-it-companies-may-hire-91k-freshers-for-fy22/articleshow/80338519.cms

https://www.timesnownews.com/business-economy/industry/article/tcs-infosys-hcl-tech-and-wipro-to-hire-91000-freshers-from-campuses-for-fy22/708944

https://kaam.de/news/amp/2021/01/19/731-big-4-it-companies-may-hire-91-000-freshers

https://www.northeastern.edu/graduate/blog/highest-paying-big-data-careers/

https://www.naukri.com/big-data-jobs

https://in.linkedin.com/jobs/big-data-analytics-jobs









About Chief Trainer

Mr. Leela Dhar Jangir is a Software professional with 15+ years of IT experience including 7+ years of classroom and corporate training.

He is having experience in training and working on live projects in multiple tools/technologies like Mainframes, IBM Lotus Notes, BIGDATA-HADOOP, Spark Scala/Python, Blockchain, etc. in various domains like Insurance, Banking, Finance, Retail, Manufacturing, etc.

A skilled architect and developer with strong problem-solving skills and analytical capabilities, who is having the vision to map the Business needs into result-oriented Projects.

He is currently working Bigdata Architect in a leading investment bank.

Professional Skills –

➢ Cloudera Hadoop certified.

➢ Having Strong leadership, mentoring, and interpersonal skills.

➢ Believe in leading by example and built, mentored, and managed multiple development teams.

➢ Self-motivated with an entrepreneurial mindset and Outstanding analytical problem-solving.

➢ Very proactive in learning and leveraging emerging technologies.

Technical Skills -

➢ JAVA MapReduce, Hadoop, Hive, Pig, Sqoop, Flume Cassandra,

➢ HBase, MongoDB, Spark Scala/Python, Data Science, and Blockchain.


Program Objectives

After the completion of the Big Data/Hadoop Course at Techwood Networks, you should be able to – ➢ Master the concepts of Hadoop Distributed File System and MapReduce

framework ➢ Understand Data Loading Techniques using Sqoop. ➢ Program in MapReduce (Both MRv1 and MRv2). ➢ Learn to write Complex MapReduce programs. ➢ Perform Data Analytics using Pig and Hive ➢ Implement HBase, MapReduce Integration, Advanced Usage, and Advanced

Indexing. ➢ Have a good understanding of Zookeeper service. ➢ New features in Hadoop 2.0 -- YARN, HDFS Federation, Name Node High

Availability. ➢ Implement best Practices for Hadoop Development and Debugging. ➢ Implement a Hadoop Project ➢ Work on Big Data Analytics and gain Hands-on Project Experience.

Who should go for this program? This course is designed for professionals aspiring to make a career in Big Data Analytics using Hadoop Framework. Software Professionals, Analytics Professionals, ETL developers, Project Managers, Testing Professionals are the key beneficiaries of this course. Other professionals who are looking forward to acquiring a solid foundation in Hadoop Architecture can also opt for this course.

Pre-requisites – Some of the prerequisites for learning Hadoop include hands-on experience in Core Java and good analytical skills to grasp and apply the concepts in Hadoop. We provide a complimentary Course "Java Essentials for Hadoop" to all the participants who enroll for the Hadoop Training. This course helps you brush up on your Java Skills needed to write Map Reduce programs.


Course Curriculum (Hadoop)

Module 1 The Motivation for Hadoop

Learning Objectives - In this module, you will understand what is Big Data, what are the limitations of the existing solutions for Big Data problems, How Hadoop solves the Big Data problem, what are the common Hadoop ecosystem components. Introduction to Linux command commonly used commands in HDFS and shell scripting.

Module 2 Hadoop Architecture

Learning Objectives - Hadoop Architecture, HDFS, and Map Reduce Framework, Hadoop Server Roles: Name Node, Secondary Name Node, Data Node and Anatomy of File Write and Read.

Module 3 Hadoop Data Loading

Learning Objectives - In this module, you will learn Data Loading Techniques: SQOOP, Hadoop Copy Commands. MapReduce Job execution, Common Hadoop Shell commands

Module 4 Hadoop MapReduce framework

Learning Objectives - In this module, you will understand the Hadoop MapReduce framework and how MapReduce works on data stored in HDFS. Also, you will learn what are the different types of Input and Output formats in the MapReduce framework and their usage

Module 5 Pig and Pig Latin

Learning Objectives - In this module, you will learn what is Pig, Running Pig, Grunt, Pig's Data Model, Pig Latin, Developing Pig Latin Scripts, Filter, Load & Store Functions. how Pig is tightly coupled with MapReduce

Module 6 Hive, HiveQL, and Advance Hive

Learning Objectives - This module will help you in understanding Difference & Comparison with Traditional Database, Loading and Querying Data in Hive. HiveQL: Data Types, Operators and Functions, Hive Tables.

Module 7 Advance Hive

Learning Objectives - This module will help you in understanding Advance Hive concepts such as Data manipulation, User Defined Functions, Appending Data into existing Hive Table, Custom Map/Reduce in Hive.


Module 8 NOSQL & HBASE

Learning Objectives – In this module, you will understand in-depth knowledge of what is HBase, how you can load data into HBase, and query data from HBase using the client. HBase Architecture, HIVE, and SQOOP Integration

Module 9 HUE/Cloudera Manager

Learning Objectives – How to interact with the Hadoop cluster using apache HUE and how to monitor Hadoop services using hue.

Module 10 Apache Oozie

Learning Objects -This module will cover Apache Oozie Workflow Scheduler for Hadoop Jobs.

Module 11 Project

Learning Objectives - In this module, you will understand how multiple Hadoop ecosystem components work together in a Hadoop implementation to solve Big Data problems. We will discuss multiple data sets and specifications of the project.


Course Curriculum (Spark & Scala)

Introduction Apache Spark 1) What is Spark? 2) Introduction to the distributed system 3) What is the problem in a distributed

system? 4) Why spark? 5) Hadoop Map Reduces Vs Apache spark 6) Spark Component 7) Advantage of Spark 8) Spark use cases

Spark Basics

1) How to start spark-shell 2) Spark context/Spark Session 3) Introduction to Spark RDD/Data frame

Scala Basics Scala Basics

1) Functional language 2) Scala Vs Java 3) Scala Data types Strings, Numbers, List,

Array, Map and Set 4) Scala variables and operators 5) Control Statements, Loop, and collections 6) Functions, methods 7) Scala class and Scala objects 8) Scala singleton objects 9) Scala String methods 10) Higher-order function 11) Currying functions 12) Scala – Traits 13) Pattern matching 14) Scala - Regular Expressions 15) Hands-On Exercise

RDD Fundamentals

1) Purpose and Structure of RDDs 2) How to Create RDD 3) RDD Operation 4) Transformations, Actions, and DAG 5) Key-Value Pair RDDs 6) Reshaping Data to Add Structure 7) Interactive Queries Using RDDs 8) Functional Programming in Spark 9) Anonymous Function 10) Hands-On Exercise ➢ Working with RDD ➢ Working with Pair RDDs


Spark SQL and Data Frames

1) Spark SQL and Data Frame Uses 2) Data Frame / SQL APIs 3) Importing MySQL data into HDFS using

Spark Hands-on 4) Creating (CSV, JSON) Data Frames 5) Querying with Data Frame API and SQL 6) Caching and Re-using Data Frames 7) Process Hive data in Spark Hands-on

Spark Streaming

1) Streaming Sources and Tasks 2) DStream APIs and Stateful Streams 3) Creating DStreams from Sources 4) Operating on DStream Data 5) Hands-on 6) Viewing Streaming Jobs in the Web UI 7) Sample Flink Streaming program

Spark Dataset API

1) Power of Dataset API in Spark 2.0 2) Serialization concept in Dataset 3) Creating Dataset API 4) Process CSV, JSON, XML, Text data 5) Dataset Operation 6) Hands-on

Advanced concepts in Spark

1) Memory management in Spark 2) How to optimize Spark Applications 3) Spark how to integrate with other

Applications


About Training

Qualifications – Students & Experienced Professionals Of B-Tech (All Branches) & M-Tech (All Branches) BCA & MCA M.Sc. IT & M.Sc. CS B.Sc. Physics & Math M.Sc. Physics & Math Duration – For Degree Holder - Approx. 50 to 80 Hours For Undergraduates - Based on different courses, branches & semester Mode of Training Program – Online & Offline Program Include the Following – ➢ Theory Lectures (We cannot ignore theory to understand the concept) ➢ Practical (80% training will be practical only) ➢ Query Sessions ➢ Student Assessment (for each topic there will be assessment) ➢ Project Explanation & Development ➢ Resume Preparation ➢ Interview Preparation

Deliverables ➢ Certificate on successful completion of the training. ➢ 100% assured placement (After Completion of Program) ➢ Six months working support (After Placement)

Fee – 24,999/-


About Internship

Qualifications – B-Tech (All Branches) & M-Tech (All Branches) BCA & MCA M.Sc. IT & M.Sc. CS B.Sc. Physics & Math M.Sc. Physics & Math (Passout & Pursuing Students) Duration – 3 Months Mode of Internship Program – Online & Offline Program Include the Following – ➢ Theory Lectures ➢ Practical (80% training will be practical only) ➢ Project Explanation & Development ➢ Assessment ➢ Query Sessions ➢ Resume Preparation ➢ Interview Preparation

Deliverables ➢ Certification on successful completion of the Internship Program. ➢ Placement assistance (after completion of degree) ➢ Six months working support (After Placement)

Fee – 24,999/-


Contact Us

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TECHWOOD NETWORKS ACADEMY BIG DATA