Power BI for Data Analytics:
1.Introduction to Power BI Desktop:
Installing and Running Power ,BI Desktop, The parts of Power BI, Core areas of Power BI,
Workflow of PBI, Data Load Process, The Power BI Desktop Window.
2.Loading Data with Power BI Desktop:
Data Sources, Loading Data, Web Pages, CSV Files, Text Files, Excel, Databases.
3.Transforming Data in Power Query:
Power BI Desktop Queries,Transforming Data The Power Query Editor, The Applied Steps
List Dataset Shaping, Renaming/Reordering/Removing Columns, Removing Error Records,
Removing Duplicate Records Sorting Data, Filtering Data.
4.Data Cleaning & Data Mashup:
Changing Data Type,Detecting Data TypesReplacing Values,Transforming Column Contents
Filling Down,Using the First Row As Headers,Grouping Duplicating,Splitting & Merging
Columns,Custom/ Index Columns,Merging & Appending Data, Adding the Contents of One
Query to Another,Adding Multiple Files from a Source Folder,Changing the Data Structure
Pivoting & Unpivoting ,Query Duplicates & References.
5.Creating & Designing Data Model:
Data Modeling in the Power BI Desktop Environment Star Schema Design Principal, Creating
Relationships Manually & Automatically Cardinality- Many to One, One to One, Many to
Many. Deleting, Managing, Deactivating Relationships.
6.Data Analysis Expressions (DAX):
Introduction to DAX, Calculated Measures,Calculated Columns, Calculated Tables,
DAX Aggregation Functions like SUM,SUMX,COUNT,COUNTX,AVERAGEX etc.
DAX Filter Functions like CALCULATE,CALCULATE TABLE ,REMOVE FILTERS,ALL etc.
DAX Logical Functions like IF,AND,OR,SWITCH,TRUE
DAX Relationship Functions like RELATED,RELATEDTABLE, USERELATIONSHIP.
DAX Table Manipulation functions like ADDCOLUMNS,CROSSJOIN,NATURALINNERJOIN.
7.Power BI Visualizations:
Canvas, Visualizations and Fields,Power BI Desktop, Dashboards ,Creating a Basic Table,
Creating a MatrixMulti-Row Cards,Column ChartsLine Charts,Pie Charts,Donut Charts,Funnel
Charts,Stacked Column and Bar Charts Scatter Charts,Filled Map visual Tree Maps Q&A AI
based Visual AI Based Key Influences Visual Decomposition Tree.
8.Filtering Data:
Filters, Visual-Level Filters,Page-Level Filters,Report-Level Filters,Removing Filters,Using the
Filter Hierarchy,Using Slicers,Formatting Slicers,Specifying Visual Interactions,
Choosing the Correct Approach to Interactive, Data Selection
9.Power BI Deployment on Cloud:
Power BI Workspace, Publishing report on workspace, Report Sharing
SQL for Data Analytics:
1.Introduction to SQL and Databases :
Understanding SQL: Definition and Importance Overview of Databases: Types and Uses
Installing and Setting Up MySQL and MySQL Workbench
2. Exploring SQL Data Types:
Understanding Primary Keys and Foreign Keys
Applying Constraints: NOT NULL, UNIQUE, CHECK, DEFAULT
3.Creating and Managing Databases:
Creating Databases and Tables, Modifying Table Structures with ALTER TABLE
Dropping Tables and Databases
4.Data Manipulation:
Inserting Data into Tables (INSERT), Updating Data in Tables (UPDATE),Deleting Data from
Tables (DELETE),Best Practices for Data Integrity
5.Querying Data:
Writing Basic SELECT Statements, Filtering Data with the WHERE Clause, Using Logical
Operators (AND, OR, NOT),Sorting Data with ORDER BY
6.Importing and Exporting Data:
Importing Data from CSV Files into SQL, Exporting Data from SQL to CSV Files
Handling Large Data Imports Efficiently
7.Functions in SQL:
Using String Functions: CONCAT, SUBSTRING, LENGTH, etc. Exploring Numeric Functions:
ROUND, AVG, SUM, etc. Date and Time Functions: NOW(), CURDATE(), EXTRACT(), etc.
8.Aggregate Functions and Grouping Data:
Using Aggregate Functions: COUNT, MAX, MIN, AVG, SUM Grouping Data with GROUP BY
Filtering Groups with HAVING Clause
9.Advanced Data Analysis Techniques:
Working with Subqueries: Types and Usage, Using Window Functions: ROW_NUMBER,
RANK, DENSE_RANK, Applying Conditional Logic with CASE Statements
10. Joining Data from Multiple Tables:
Understanding SQL Joins: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN
Advanced Joins: SELF JOIN, CROSS JOIN, Combining Results with UNION and UNION ALL
11. Common Table Expressions (CTE) and Views:
Writing and Using Common Table Expressions (CTEs), Creating and Managing Views
12.Performance Optimization:
Indexing for Faster Query Performance, Analyzing and Optimizing Query Execution
Plans.
13.Advanced Topics in SQL:
Understanding and Implementing Triggers, Working with Stored Procedures and
Functions