DATA ENGINEERING AND ANALYTICS: DUAL EXPERTISE PROGRAM

DATA ANALYTICS ESSENTIALS (1 Session)

MODULE-1: DATA-CENTRIC ROLES AND SKILLS

Course Introduction
Data-Centric Job Roles and Required Skills
Distinguish Business Analyst / Data Analyst / Data Engineer / Data Scientist Roles
Data Analysis vs Data Analytics?

MODULE-2: THE DATA ECOSYSTEM

Transactional Systems Functions (Business Operations)
Analytical Systems Functions (Business Intelligence)
Different Types of Data Structures, File Formats, Sources of Data
Various types of Analytical System Repositories: Data Warehouse, Data Mart, Data Lake, Data Pipelines, Big Data, etc.
Data Modeling Concepts: Dimensional Modeling

MICROSOFT POWER BI (10-12 SESSIONS)

MODULE-1: COURSE INTRODUCTION

What is Microsoft Power BI?
Purpose of Training
What to Expect?
Required Resources
Structure of Training
Introduction to Training Project

MODULE-2: INTRODUCING THE POWER BI TOOL

Meeting the Power BI tool: Desktop & Service
How and where to Download Power BI Desktop
Necessary Settings
Familiarizing with Power BI
Data Analysis Expressions (DAX)
Quick Quiz Time

MODULE-3: POWER QUERY - CONNECTING TO DATA SOURCES

Different Types of Connections
Advantages / Disadvantages of each connection type
Frequently used data sources

MODULE-4: POWER QUERY - SHAPING DATA

Power Query Editor
Basic Transformations
Using Multiple tools available on Power Query
Quick introduction to Advanced Editor
Discussing Best Practices
Quick Quiz Time
Exercise

MODULE-5: POWER BI DESKTOP - MODELING DATA

Introduction to Data Model
Describing Modeling Tab
Creating Model
Best Practices
Quick Quiz Time
Exercise

MODULE-6: POWER BI DESKTOP - DAX

What are Measures?
What are Calculated Columns?
Measure vs Calculated Columns
Working session Using DAX
Best Practices
Quick Quiz Time
Exercise

MODULE-7: POWER BI DESKTOP - CREATING VISUALIZATION

Introduction
Working session with Visuals
Using Filters Pane
Using Slicer
Interacting with Visuals
Using Drill through & Drill Down
Editing Interactions
Using "What-if" Parameters
Managing Roles in Power BI
Publishing Report to Power BI Service
Best Practices
Quick Quiz Time
Exercise

MODULE-8: INTRODUCING POWER BI SERVICE

BI as a Service
Setting Expectations
What is Power BI Service?
How Power BI Service look like
Quick Quiz Time
Exercise

MODULE-9: POWER BI SERVICE - DATA CONNECTION FROM SERVICE

Options for Data Connection
Loading Flat files to Power BI Service
Components of Power BI Service
Creating App Workspace
Loading Power BI File to Service
Quick Quiz Time
Exercise

MODULE-10: POWER BI SERVICE - GATEWAYS & REFRESH IN SERVICE

What is a Data Gateway?
Different types of Gateways
Setting up Personal Gateway
Enabling Scheduled Refresh
What are Dataflows?
Quick Quiz Time
Exercise

MODULE-11: POWER BI SERVICE - REPORTS & DASHBOARDS

What are Reports & Dashboards
Pinning Report Visuals to Dashboard
Adding Slicers Visuals
Pinning Live Pages to Dashboards
Setting up alerts
Quick Quiz Time
Exercise

MODULE-12: POWER BI SERVICE - SHARING ON SERVICE

Sharing on Power BI Service
Publishing the Report on the Web
User Roles & Permissions
Publishing Apps and using it
Quick Quiz Time
Exercise

MODULE-13: SUMMING UP

Best Sites for Reference
Best YouTube Channel for Reference

MODULE-14: ADVANCED TOPICS

Working with M Language
Advanced DAX Functions
Calculated Tables
Handling Many-to-Many Relationships
Best Practices in Power Query

COPILOT (1 Session)

MODULE-1: COURSE INTRODUCTION

Understanding Microsoft Copilot
Copilot for Power BI
Use Copilot in Power BI Desktop

MODULE-2: INTRODUCING THE COPILOT FOR POWER BI TOOL

Enhancing Report Design with AI-assisted Tasks
Mastering DAX Formula with Copilot
Enhancing Power BI Reports with Copilot
Risks and Challenges with Generative AI Tools
Best Practices
Quick Quiz Time
Exercise

Python - Intermediate Level (6-8 Sessions)

*The course sessions offer a blend of mentoring, guidance, and self-study*

MODULE-1: INTRODUCTION TO PYTHON

Introduction and History of Python
Various Python Distribution Vendors & Text Editors
Python Installation (Windows, Mac, Linux)
Introduction to Jupyter Notebook
Exercise

MODULE-2: VARIABLE AND DATA TYPES

Operators and Order of Operations
Naming and Using Variables
Data Types (Strings, Numbers)
Working, Concatenation, and Conversion of Strings
String Operations
Expression, Comments, Using the Input() function
Exercise

MODULE-3: DATA STRUCTURES: LISTS & SETS

Create a List
List of Lists
Subsetting Lists
Manipulating Lists
Delete List Elements
Inner working of Lists
Slicing and Dicing
Properties of Sets
Access to Sets
Manipulating Sets
When to use Sets
Exercise

MODULE-4: DATA STRUCTURES: TUPLES & DICTIONARIES

Understanding of Immutability Nature
Creating a Tuple
Access Tuples
When to Use Tuples
Idea Behind Dictionaries
Create a Dictionary
Access a Dictionary
Dictionary Manipulations
Dictionaries to Data Frames
Exercise

MODULE-5: CONDITIONAL STATEMENTS AND LOOPS

IF, IF-ELSE, IF-ELIF-ELSE Statements
Multiple Conditions and Multiple IF Statements
WHILE and FOR Loops
Nesting Loops
Break Command and Avoiding Infinite Loops
Understanding Iterators
Applying Iterators on Data Structures
Exercise

MODULE-6: FUNCTIONS AND EXCEPTIONS HANDLING

Methods and Functions Overview
Defining and Calling Functions
Returning a Value & Modules
Working with Functions and Comprehensions
Lambda Expressions, Map and Filter Functions
Handle Possible Errors
Exception Handling (Try-except, Try-except-finally, etc.)
Exercise

MODULE-7: PROGRAMMING ALGORITHMS

Algorithm Basics
Search
Sort
Factorial
Even or Odd
Target Sum
Print Pattern
Recursion
Time Complexity
Two Pointer

MODULE-8: DATA ANALYSIS (NumPy and Pandas)

Data Analysis Introduction
Data Analysis using Pandas
Pandas Series
Pandas Data Frames
Manipulating Data in Data Frames
Exercise

MODULE-9: DATA VISUALIZATION

Introduction to Matplotlib
Installation of Matplotlib
Plotting Line Graphs, Histograms, Bar Charts, Scatter plots and more
Exercise

MODULE-10: OBJECT-ORIENTED PROGRAMMING

Object Oriented Programming
Defining Classes and Objects
Defining Methods
Inheritance and Polymorphism
Exercise

CLOUD INFRASTRUCTURE (3-4 SESSIONS)

*The course sessions offer a blend of mentoring, guidance, and self-study*

MODULE-1: INTRODUCTION TO AMAZON WEB SERVICES (AWS)

Cloud Providers (AWS, AZURE, GCP, etc.)
Cloud Computing
AWS Cloud Services
Virtual Private Cloud (VPC)
Exercise

MODULE-2: AWS SETUP, INSTALLATION AND CONFIGURATION

Elastic Compute Cloud (EC2) Instance Setup (Python / Java Installation) / File Transfer
EMR (Cluster) Setup for Big Data Processing
Relational Database Service (RDS) Setup
Connection using WinSCP and Putty
S3 Bucket
Exercise

DATA ENGINEER (6-8 SESSIONS)

*The course sessions offer a blend of mentoring, guidance, and self-study*

MODULE-1: INTRODUCTION TO DATA ENGINEERING

What is Data Engineering
Roles of a Data Engineer
Tools of Data Engineering

MODULE-2: RELATIONAL Vs NoSQL

Databases and Design
SQL vs NoSQL (MY SQL vs MongoDB)
Pandas vs SQL
Database Schemas
Exercise

MODULE-3: APPLICATION PROGRAMMING INTERFACE (API)

What is API
Building an API
Storing data in MySQL and MongoDB.

MODULE-4: APACHE SPARK

Introduction Apache Spark Framework
Reasons to move with Spark Framework.
Spark installation on AWS
Spark-Submit job with Word Count Program
Running Programs using Pyspark vs Spark Framework
Exercise

MODULE-5: PYSPARK

Introduction to PySpark
Work with PySpark on the Spark Framework
Working on Data Set on Spark Framework with PySpark
Exercise

MODULE-6: APACHE KAFKA

Introduction to Kafka
Data Delivery and Stream Processing
Project Structure and Running Samples on the EMR Cluster
Exercise

SELF STUDY TOPICS

*We offer guidance and mentorship for certifications, but students are responsible for their own preparation and certifications*

@BI_Courses YouTube Videos

Tableau BI

SQL Queries

Agile Scrum Methodology

Microsoft Co-Pilot or Similar AI-driven Automation Tools

Microsoft Azure, including Azure Data Factory and Azure Synapse Analytics

Certification in Power BI (Power BI Data Analyst Associate from Microsoft)

Certification in Python (Certified Associate/Professional Python Programmer from OpenEDG Python Institute)

Certification in AWS Data Engineer Associate

Certification in Microsoft Azure Data Engineer Associate or Microsoft Fabric Data Engineer

Certification in Google Professional Data Engineer