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Python Training in Bangalore

The Big Data Architect Masters Program Training is designed to help you gain end to end coverage of Big Data technologies by learning the conceptual implementation of Hadoop 2.x + Quartz Scheduler + Spark using Scala + Kafka + Cassandra and Zepplein. The entire program is a highly recommended for any working professional who intends to land as a successful Big Data Developer/Architect.

Course Description

The Big Data Masters Program is designed to empower working professionals to develop relevant competencies and accelerate their career progression in Big Data technologies through complete Hands-on training.

Being a Big Data Architect requires you to be a master of multiple technologies, and this program will ensure you to become an industry-ready Big Data Architect who can provide solutions to Big Data projects.

At NPN Training we believe in the philosophy “Learn by doing” hence we provide complete Hands-on training with a real time project development.

Course Objectives

By the end of the course,  you will:

  1. Understand what is Big Data, the challenges of with Big Data and how Hadoop solves the Big Data problem
  2. Understand Hadoop 2.x Architecture, Replication, Single Point of Failure, YARN

Work on a real time project on Big Data

This program comes with a portfolio of industry-relevant POC’s, Use cases and project work. Unlike other institutes we don’t say use cases as a project, we clearly distinguish between use case and Project.

Work is the target audience?

  • Software engineers and programmers who want to understand the larger Big Data ecosystem, and use it to store and analyze.

Hadoop 2.x – Distributed Storage + Batch Processing

Course description: This section of the training will help you understand how Hadoop solves storage and processing of large data sets in a distributed environment .

Module 01 - Understanding Big Data & Hadoop 2.x

Learning Objectives – In this module, you will understand Big Data, the limitations of the existing solutions for Big Data problem, how Hadoop solves the Big Data problem, the common Hadoop ecosystem components, Hadoop 2.x Architecture, HDFS, Anatomy of File Write and Read.

Topics –

  • Introduction to Big Data
  • Challenges of Big Data
  • OLTP VS OLAP Applications
  • Bussiness Usecase – Telecom
  • Limitations of existing Data Analytics
  • A combined storage compute layer
  • Introduction to Hadoop
  • Exploring Hadoop 2.x Core Components
  • Hadoop 2.x Daemon Services
    1. NameNode
    2. DataNode
    3. Secondary NameNode
    4. ResourceManager
    5. NodeManager
  • HDFS Architecture
  • Understanding NameNode metadata
  • File Blocks in HDFS
  • Rack Awareness
  • Anatomy of File Read and File Write
  • YARN
  • Understanding HDFS Federation
  • Understanding High Availability Feature in Hadoop 2.x
  • Exploring Big Data ecosystem

Check E-Learning for more Assignments + Use cases + Project work + Materials + Case studies

 

Quartz – Enterprise Job Scheduler

Course description: This course will help you to learn one of the most popular Job Scheduling Library i.e Quartz that can be integrated into a wide variety of Java applications. Quartz is widely used in enterprise class applications to support scheduling of jobs and to build process workflow.

Module - Quartz Scheduler

Learning Objectives – In this module you will understand about quartz job scheduler

Topics –

  • What is Job Scheduling Framework
  • Role of Scheduling Framework in Hadoop
  • What is Quartz Job Scheduling Library
  • Using Quartz
  • Exploring Quartz API
    1. Jobs
    2. Triggers
  • Scheduling Hive Jobs using Quartz scheduler

This program comes with a portfolio of industry-relevant POC’s, Use cases and project work. Unlike other institutes we don’t say use cases as a project, we clearly distinguish between use case and Project.

Process we follow for project development

We follow Agile methodology for the project development,

  1. Each batch will be divided into scrum teams of size 4-5 members.
  2. We will start with a Feature Study before implementing a project.
  3. The Feature will be broken down into User Stories and Tasks.
  4. For each user story a proper Definition Of Done will be defined
  5. A Test plan will be defined for testing the user story

Real Time Data Simulator

Project description: Creating a project which generates dynamic mock data based on the schema at a real-time, which can be further used for Real-time Processing systems like Apache Storm or Spark Streaming.

Building Complex Real time Event Processing

Project Description:

In this project, you will be building a real-time event processing system using Apache Streaming where even sub seconds also matter for analysis, while still not fast enough for ultra-low latency (picosecond or nano second) applications, such as CDR (Calling Detailed Record) from telecommunication where you can expect millisecond response times.

User Story 01 – As a developer we should simulate Real time Network Data

  1. Task 01 – Use Java Socket programming to generate and publish data to a port
  2. Task 02 – Publish the data with different scenarios

User Story 02 – As a developer we should be able to consume data using Spark Streaming

User Story 03 – As a developer we should consume Google API to convert latitude and longitude to corresponding region names.

User Story 04 –  Perform computation to calculate some important KPI’s (Key Performance Indicator) on the real time data.

More detailed split up will be shared once you start the project.

Technologies Used :

  • Java Socket Programming
  • Google API
  • Scala Programming
  • Spark Streaming

Data Model Development Kit

Project Description :

This project helps data model developer to manage Hive tables with different tables, storage types, column types and column properties required for different use case development.

Roles & Responsibility

  1. Building .xml files to define structures of hive tables to be used for storing process data generated.
  2. Actively involved in development to read .xml files, create data models and load data in hive.

Technologies Used

Java, JAXB, JDBC, Hadoop, Hive,

Sample User Stories

[Study User Story 01] – Come up with a design to represent data model required to handle the following scenarios

  • To Handle different operations like “CREATE”, “UPDATE”,”DELETE”
  • Way to define partition table
  • To Store columns in Orders
  • To Store column Name
  • To Handle Update of Column type and Name

[User Story 02] – HQL Generator – As a developer, we have to provide a functionality to create table

**Tasks**
– [ ] . Building Maven project and adding dependency
– [ ] . Integrate Loggers
– [ ] . Code Commit
– [ ] . Create a standard package structure.
– [ ] . Utility to read xml and create Java Object
– [ ] . Utility code to communicate to Hive DB
– [ ] . Check for Hive Service before executing queries
– [ ] . Code to construct HQL query for create.
– [ ] . Exception Handling.

Definition of Done
– [ ] Package structure should be created.
– [ ] Table has to be created in Hive
– [ ] Validate all required schema is created
– [ ] Validation of Hadoop + Hive Services

**Test Cases**
1.If table already exists we need to print “Table already exists”
2.Verify schema with xml
3.If services are not up and running,it should handle and log it.

 

Course hours

90 hours extensive class room training30 sessions of 3 hours eachCourse Duration : 5 Months

Assignments

For each module multiple Hands-on exercises, assignments and quiz are provided in the E-Learning

Real time project

We follow Agile Methodology for the project development. Each project will have Feature Study followed by User stories and Tasks.

Mock Interview

There will be a dedicated 1 to 1 interview call between you and a Big Data Architect. Experience a real Mock Interview.

Forum

We have a community forum for all our students wherein you can enrich their learning through peer interaction and knowledge sharing.

Certification

From the beginning of the course, you will be working on a project. On completion of the project NPN Training certifies you as a “Big Data Architect” based on the project.

Oct 13th

Batch: Weekend Sat & Sun
Duration: 5 Months
 30,000

Enroll Now

Nov 10th

Batch: Weekend Sat & Sun
Duration: 5 Months
 30,000

Enroll Now

Dec 15th

Batch: Weekend Sat & Sun
Duration: 5 Months
 30,000

Enroll Now

Batches not available

Is Java a pre-requisite to learn Big Data Masters Program?

Yes Java is a pre-requisite, there are institutes who says Java is not required all those are false information

Can I attend a demo session before enrollment?

Yes, You will be sitting in an actual live class to experience the quality of training.

How will I execute the Practicals?

We will help you to setup NPN Training’s Virtual Machine + Cloudera Virtual Machine in your System with local access. The detailed installation guides are provided in the E-Learning for setting up the environment.

Who are the Instructor at NPN Training?

All the Big Data classes will be driven by Naveen sir who is a working professional with more than 12 years of experience in IT as well as teaching.

how do I access the eLearning content for the course?

Once you have registered and paid for the course, you will have 24/7 access to the E-Learning content

What If I miss a session?

The course validity will be one year so that you can attend the missed session in another batches.

Do I avail EMI option?

The total fees you will be paying in 2 installments

Are there any group discounts for classroom training programs?

Yes, we have group discount options for our training programs. Contact us using the form “Drop Us a Query” on the right of any page on the NPN Training website, or select the Live Chat link. Our customer service representatives will give you more details.

Reviews

Testimonial

Sai Venkata Krishna
Capgemini
Linkedin

Naveen is an excellent trainer. Naveen mainly focus on HANDS ON and REAL TIME SCENARIOS which helps one to understand the concepts easily.I feel that NPN training curriculum is best in market for Big Data.
Naveen is very honest in his approach and he delivers additional concepts which are not present in the syllabus of particular topics.E learning and assignments are very informative and helpful.The amount you pay for the Big data course is worth every penny.
Thank you NPN Training for your support and motivation.

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