BigData Specialization Program

About The Program:

With the belief to build a healthy ecosystem as per the Industry Standards REGex Software brings a Summer Training/Internship Program on “Power BI & BigData”. We organize Summer Training/Internship Program for improving the knowledge and skills of the Students/Professionals, so that they can become expert in the field of BigData and get their Dream Job in Software Development Field in Big MNCs.

REGex Software Services’s Big-Data program is a valuable resource for both beginners and experts. This specialization program will introduce you to the domain of Data Engineering include Hadoop, Map-Reduce, HIVE, Apache Spark, Kafka Streaming ,SQL, Power BI,  Amazon EMR and much more starting from Basics to Advance. If you want to become Data Engineer / Business Analyst, REGex introduce this program for you.  

July Batches Dates

Batch 1: 3rd July 2023
Batch 2: 10th July 2023
Batch 3: 21st July 2023

Location

Physical(Jaipur)
or 
Online(Google Meet)

Duration

8 Months

Participants

15 per Batch

What People Tell About Us

What you will Learn

Python

Duration: 20 Hours

SQL

Duration: 60 Hours

Power BI

Duration: 50 Hours

Hadoop

Duration: 20 Hours

Hive

Duration: 20 Hours

Spark

Duration: 40 Hours

Apache Kafka

Duration: 20 Hours

nosql

No SQL

Duration: 20 Hours

Amazon Emr

Duration: 10 Hours

What you will Learn

  • Linux basics
  • Big Data Analytics & Hadoop
  • HDFS [ Hadoop Distributed File System ]
  • Map-Reduce [ Data Processing ]
  • HIVE
  • Apache Spark on Azure DataBricks
  • NoSQL DataBase
  • Data visualization
  • Power BI
  • SQL
  • Power Query & Editor
  • Dashboard & Graph
  • Amazon EMR
  • Learn how to use these tools in the field of Data Analytics

Study Material

  • E-Notes.
  • Poll Test & Assignments .
  • Over 450+ hours of Live Video Lectures available on demand.
  • Accessing lecture videos and notes.
  • 24*7 Mentorship Support
  • Engaging in real-time project assignments

Output

  • Help you in Data Analytics Domain
  • Able to think out of the box
  • Expertise in different Big Data Tools like HDFS, Hive, Apache Spark, Amazon EMR
  • Become expert in multiple technology domains like: Python, SQL, Power BI etc.
  • Able to solve many Interview Questions of Top MNCs
  • Understand creating Data Insights by connecting data sets, transform & clean the data into data models and then create chars/graphs to provide visuals of the data
  • Build Charts/Graphs/Insights of data sets
  • Work on multiple data sets
  • Become Power BI Analyst / Power BI Developer after completion of this program
  • Able to get package  in Big MNCs upto 30 LPA

Live Sessions

Live Sessions by Expertise Trainers and Access of Recorded Session is also available

Live Projects

Get a chance to work on Industry Oriented Projects to implement your learning

24*7 Support

24*7 Mentorship Support available for all Students to clear all of your doubts

ISO Certification

Get Certificate of Workshop Completion from ISO Certified Company

Package Offered So Far

Minimum Package

5 LPA

Average Package

8 – 12 LPA

Highest Package

36 LPA

Our Students Placed // Partnership

Previous
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Placed Students

Course Content

  • Basics of Python
  • OOPs Concepts
  • File & Exception Handling
  • Working with Pandas, Numpy & Matplotlib ■ Working with Missing Data ■ Data Grouping ■ Data Subsetting ■ Merging & Joining Data Frames
  • Importing Libraries & Datasets
● Introduction to LINUX Operating System and Basic LINUX commands ● Operating System ● Basic LINUX Commands Linux File System
  • LINUX File System
  • File Types
  • File Permissions
  • File Related Commands
  • Filters
  • Simple Filters
  • Advanced Filters
Vi Editor
  • Vi Editor
  • Input Mode Commands
  • Vi Editor – Save & Quit
  • Cursor Movement Commands
Shell Programming
  • Shell Variables
  • Environmental Variables
  • Shell script Commands
  • Arithmetic Operations
  • Command Substitution
  • Command Line Arguments
  •  Business Intelligence
  •  Need for Business Intelligence
  • Terms used in BI
  • Components of BI
General concept of Data Warehouse
  • Data Warehouse
  • History of Data Warehousing
  • Need for Data Warehouse
  • Data Warehouse Architecture
  • Data Mining Works with DWH
  • Features of Data warehouse
  • Data Mart
  • Application Areas
Dimensional modeling
  • Dimension modeling
  • Fact and Dimension tables
  • Database schema
  • Schema Design for Modeling
  • Star, SnowFlake
  • Fact Constellation schema
  • Use of Data mining
  • Data mining and Business Intelligence
  • Types of data used in Data mining
  • Data mining applications
  • Data mining Products

● What’s Big Data?
● Big Data: 3V’s
● Explosion of Data
● What’s driving Big Data
● Applications for Big Data Analytics
● Big Data Use Cases
● Benefits of Big Data

    • Functional Dependency
    • Closure of Attributes
    • Types of Keys: PrimaryKey CandidateKey & Super Key in DBMS
    • Normalization
    • Indexing
    • Transaction and Concurrency Control
    • Transaction in DBMS
    • ACID Propertise in DBMS
    • Joins in DBMS
    • Create & Alter Table
    • Constraints in SQL
    • Sql Queries & Sub Queries
    • SQL Stored Procedure
    • View, Cursor & Trigger in SQL
    • Common Table Expession
    • Replace Null and Coalesce Function
    • Running Total In SQL
 

Power BI

  • Introduction
  • Meet Microsoft Power BI Desktop
  • Interface & Workflow
  • Helpful Power BI Resources
  • New Power BI Ribbon
    • Introduction
    • Types of Data Connectors in Power BI Desktop
    • The Power BI Query Editor
    • Demo: Basic Table Transformations in Power BI
    • Power BI Demo:

 

  • Working with Text Tools
  • Numerical Values
  • Date & Time Tools
  • Creating a Rolling Calendar
  • Grouping & Aggregating Records
  • Pivoting & Unpivoting Data

 

    •  
    • Merging Queries in Power BI Desktop
    • Appending Queries in Power BI Desktop
    • Configuring Power BI Data Source Settings
    • Configuring Power BI Query Refresh Settings
    • Additional Data Types & Categories in Power BI
    • Defining Hierarchies in Power BI Desktop

 

  • Importing Models from Excel to Power BI

 

 

    • Introduction
    • Types of Data Connectors in Power BI Desktop
    • The Power BI Query Editor
    • Demo: Basic Table Transformations in Power BI
    • Power BI Demo:

 

  • Working with Text Tools
  • Numerical Values
  • Date & Time Tools
  • Creating a Rolling Calendar
  • Grouping & Aggregating Records
  • Pivoting & Unpivoting Data

 

    •  
    • Merging Queries in Power BI Desktop
    • Appending Queries in Power BI Desktop
    • Configuring Power BI Data Source Settings
    • Configuring Power BI Query Refresh Settings
    • Additional Data Types & Categories in Power BI
    • Defining Hierarchies in Power BI Desktop

 

  • Importing Models from Excel to Power BI

 

 

  • Introduction
  • Meet Data Analysis Expressions (DAX)
  • Intro to DAX Calculated Columns
  • Intro to DAX Measures
  • Adding Columns & DAX Measures in Power BI Desktop
  • Implicit vs. Explicit DAX Measures
  • Filter Context Examples in Power BI
  • Understanding DAX Syntax & Operators
  • Common DAX Function Categories
  • DAX Demo: 
    • Basic Date & Time Functions
    • Conditional & Logical Functions (IF/AND/OR)
    • Common Text Functions
    • Joining Data with RELATED
    • Basic Math & Stats Functions
    • COUNT Functions (COUNTA, DISTINCTCOUNT, COUNTROWS)
    • CALCULATE
    • CALCULATE & ALL
    • CALCULATE & FILTER
    • Iterator Functions (SUMX, RANKX)
    • Time Intelligence Formulas

Functions

  • FILTER Function
  • LOGICAL Functions
  • MATHEMATICAL Functions
  • STATISTICAL Functions
  • TEXT Functions
  • TIME INTELLEGENT Functions
  • Other Functions
  • Power Query Editor
  • Power BI Aggregation & Template
    • Introduction
    • Exploring the “Report” View in Power BI Desktop
    • Adding Simple Objects to the Power BI Report Canvas
    • Inserting Basic Charts & Visuals in Power BI
    • Conditional Formatting
    • Power BI Report Formatting Options
    • Power BI Report Filtering Options
    • Power BI Demo:
      • Exploring Data with Matrix Visuals
      • Filtering with Date Slicers

 

  • Showing Key metrics with Cards & KPI Visuals

 

    • Inserting Text Cards
    • Visualizing Geospatial Data with Maps
    • Visualizing Data with Treemaps
    • Showing Trends with Line & Area Charts
    • Adding Trend Lines & Forecasts 
    • Goal pacing with Gauge Chart
    • Adding Drillthrough Filters
  • Editing Power BI Report Interactions
  • Managing & Viewing Roles in Power BI Desktop

Big Data Tools

● History of Hadoop
● Distributed File System
● What is Hadoop
● Characteristics of Hadoop
● RDBMS Vs Hadoop
● Hadoop Generations
● Components of Hadoop
● HDFS Blocks and Replication
● How Files Are Stored
● HDFS Commands
● Hadoop Daemons

● Difference between Hadoop 1.0 and 2.0
● New Components in Hadoop 2.x
● YARN/MRv2
● Configuration Files in Hadoop 2.x
● Major Hadoop Distributors/Vendors
● Cluster Management & Monitoring
● Hadoop Downloads

● What is distributed computing
● Introduction to Map Reduce
● Map Reduce components
● How MapReduce works
● Word Count execution
● Suitable & unsuitable use cases for MapReduce

● Architecture
● Basic Syntax
● Import data from a table in a relational database into HDFS
● import the results of a query from a relational database into HDFS
● Import a table from a relational database into a new or existing Hive table
● Insert or update data from HDFS into a table in a relational database

● Define a Hive-managed table
● Define a Hive external table
● Define a partitioned Hive table
● Define a bucketed Hive table
● Define a Hive table from a select query
● Define a Hive table that uses the ORCFile format
● Create a new ORCFile table from the data in an existing non-ORCFile Hive table
● Specify the delimiter of a Hive table
● Load data into a Hive table from a local directory
● Load data into a Hive table from an HDFS directory
● Load data into a Hive table as the result of a query
● Load a compressed data file into a Hive table
● Update a row in a Hive table
● Delete a row from a Hive table
● Insert a new row into a Hive table
● Join two Hive tables
● Use a subquery within a Hive query

● What is Spark?
● History of Spark
● Spark Architecture
● Spark Shell

● RDD Basics
● Creating RDDs in Spark
● RDD Operations
● Passing Functions to Spark
● Transformations and Actions in Spark
● Spark RDD Persistence

● Pair RDDs
● Transformations on Pair RDDs
● Actions Available on Pair RDDs
● Data Partitioning (Advanced)
● Loading and Saving the Data

● Accumulators
● Broadcast Variables
● Piping to External Programs
● Numeric RDD Operations
● Spark Runtime Architecture
● Deploying Applications

  •  Spark SQL Overview
  • Spark SQL Architecture

Data Frame

  • What are dataframe
  • Manipulating Dataframes
  • Reading new data from different file format
  • Group By & Aggregations functions
  •  What is Spark streaming?

  • Spark Streaming example

  • Understand the fundamentals of Kafka.
  • Understand the distributed nature of Kafka and its scalability.
  • Understand how data is organized into topics and partitions.
  • Install and set up Kafka on your local machine or a cluster.
  • Learn how to create topics, produce messages, and consume messages using
    Kafka APIs.
  • Overview of Amazon EMR and its features.
  • Setting up and configuring Amazon EMR clusters.
  • Running big data processing jobs on EMR.
  • Integrating Amazon EMR with other AWS services.
  • Monitoring and optimizing EMR clusters.
  • Security considerations for EMR.

● Introduction of HBase
● Comparison with traditional database
● HBase Data Model (Logical and Physical models)
● Hbase Architecture
● Regions and Region Servers
● Partitions
● Compaction (Major and Minor)
● Shell Commands
● HBase using APIs

NO SQL

  • Introduction to NoSQL databases and their characteristics.
  • Types of NoSQL databases: Document-oriented, Key-Value, Column-Family, Graph.
  • Use cases for NoSQL databases.
  • MongoDB: A popular document-oriented NoSQL database.
  • Redis: A widely used key-value NoSQL database.
  • Cassandra: A column-family NoSQL database.
  • Understand the fundamentals of ETL (Extract, Transform, Load) processes.
  • Learn how to install and configure Taland.
  • Explore Taland’s interface and understand its key components.
  • Practice using Taland to extract data from different sources, perform
    transformations, and load it into target systems.

● Pre-requisites
● Introduction
● Architecture

● Installation and Configuration
● Repository
● Projects
● Metadata Connection
● Context Parameters
● Jobs / Joblets
● Components
● Important components
● Aggregation & working with Input & output data

● Pseudo Live Project (PLP) program is primarily to handhold participants who are fresh into the technology. In PLP, more importance given to “Process Adherence”
● The following SDLC activities are carried out during PLP
o Requirement Analysis
o Design ( High Level Design and Low Level Design)
o Design of UTP(Unit Test Plan) with test cases
o Coding
o Code Review
o Testing
o Deployment
o Configuration Management
o Final Presentation

Extra Sessions

Additinal Session on GIT, Linux, Docker, AWS Basics, Jenkins and many more for all students.

Fee Structure

Indian Fee

Price: ₹1,39,999/- (Flat 75% off) => ₹34,999/- 

International Fee

Price: $4000 (Flat 75% off) => $1000
Fee can be paid in No Cost EMI @3500/month

Cashback Policy

  • You will get your Unique Referral Code after successful paid registration.
  • You will get ₹2000 Cashback directly in your account for each paid registration from your Unique Referral Code on monthly basis(After Closing Registrations of this program) .
  • For Example:- If we received 10 paid registration from your Unique Referral Code then you will receive ₹2000*10 = ₹20,000 on monthly basis.

Goodies

You may get Goodies like: REGex T-shirt, REGex Stickers, REGex Key Chain, REGex Cap, REGex Bag etc. after successfully enrollment in this program.

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(Batches Start from  May, June & July 2023)

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*Extra off is applicable on 1 time payment only. Seats can be filled or Price can be increased at any time. Refund policy is not available*