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Big Data Architect Training:

  • COURSE INTRODUCTION: The program is inclusive of full-fledged training, starting from Java, Hadoop developer course, MongoDB, Scala Programming, and Spark and Scala Development Training, all of which are found to be quite essential skills for the Big Data Architects. These modules put together will provide a solid foundation and give a further edge in the learning process.
  • PRE-REQUISITES: This course is designed for tech-savvy individuals who seek in-depth knowledge in the field of Big Data. Moreover, it offers promising benefits to fresher, experienced developers and architects, corporate IT professionals, engineers, and other professionals.
  • DURATION: 6 Days(48 HRS)
  • CERTIFICATON: At the end of the course you will get the certificate for completing the training.

Course Content:

JAVA TRAINING

  • Core Java
  • Java Servlet Technology
  • Java Server Pages Technology

SCALA PROGRAMMING

  • Introduction to Scala
  • Key Features of the Scala Language
  • Basic Programming in Scala
  • OO Development in Scala
  • Functional Programming in Scala
  • Exception handling in Scala
  • Try catch with case
  • Pattern Matching in Depth
  • Test Driven Development in Scala
  • Writing standard JUnit tests in Scala
  • Conventional TDD using the ScalaTest tool
  • Behavior Driven Development using ScalaTest
  • Using functional concepts in TDD
  • XML Manipulating in Scala
  • Writing Concurrent Apps

Scala web

  • Introduction
  • Starting Up
  • Routing
  • Controllers, Actions, and Results
  • Views
  • Data Access
  • The Global Object

BIG DATA HADOOP DEVELOPER

  • Introduction to Linux and Big Data Virtual Machine (VM)
  • Understanding Big Data
  • HDFS Overview and Architecture
  • How HDFS addresses fault tolerance?
  • HDFS Interfaces
  • Advanced HDFS features
  • Map Reduce – 1 (Theoretical Concepts)
  • MapReduce overview
  • MapReduce Architecture
  • MR Algorithm and Data Flow
  • Alternatives to MR – BSP (Bulk Synchronous Parallel)
  • Map Reduce – 2 (Practice)
  • Hadoop Streaming (developing and debugging non Java MR program s – Ruby and Python)
  • MR algorithm s (Non- graph)
  • MR algorithm s (Graph)
  • Higher Level Abstractions for MR (Pig)
  • Higher Level Abstractions for MR (Hive)
  • Comparison of Pig and Hive
  • NoSQL Databases – 1 (Theoretical Concepts)
  • NoSQL Concepts
  • Different types of NoSQL databases
  • Columnar Databases concepts NoSQL Databases – 2 (Practice) HBase Architecture
  • Interfaces to HBase (for DDL and DML operations)
  • Advance HBase Features
  • Spark
  • Setting up a Hadoop Cluster using Apache Hadoop
  • Using EC2 ( Elastic Compute Cloud)
  • SSH Configuration
  • Hadoop Ecosystem and Use Cases
  • Proof of concepts and use cases

SPARK DEVELOPMENT

·Scala Basics

·Scala Essentials

·OOP’s and FP

·Prerequisite: BigData and Hadoop Framework

APACHE SPARK

·Introduction to Spark

·Spark Basics

·Working with RDD’s

·Writing and Deploying Spark Applications

·Spark RDD

·Spark SQL

·Spark Job Execution

·Spark Streaming

·Spark Mllib

·GraphX

·Performance Tuning

·Course Deliverables

MONGODB

·Introduction to NoSQL and MongoDB

·MongoDB Installation

·Importance of NoSQL

·CRUD Operations

·Data Modeling & Schema Design

·Data Management & Administration

·Data Indexing and Aggregation

·MongoDB Security

·Working with Unstructured Data

·MongoDB Project