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This comprehensive course is designed to transform aspiring data professionals into skilled data analysts by equipping them with actionable knowledge of Excel, SQL, Power BI, and AI-powered analytics. Through a hands-on, project-based learning approach, students will master core data handling, business intelligence, and visualization techniques, crucial for real-world business decision-making.
Starting with the fundamentals of data analytics and Excel operations, the course delves into advanced formula integrations, dynamic pivot tables, Power Pivot data modeling, and DAX calculations. Learners will also gain expertise in data cleaning using Power Query, building interactive business dashboards, and leveraging SQL for data extraction and analysis.
As the program progresses, participants will be introduced to cutting-edge AI features in Excel and Power BI, preparing them for the future of data analytics. By the end of the course, learners will be confident in transforming raw data into actionable insights, presenting professional dashboards, and contributing to data-driven business strategies.
Prerequisite
Basic Computer Skills: Familiarity with operating systems (Windows/Mac), file management, and internet usage.Fundamental Understanding of Spreadsheets (Optional but Helpful): Some experience with Microsoft Excel or Google Sheets will be helpful but not mandatory.
Logical Thinking and Problem-Solving Skills: A willingness to approach problems methodically and think critically.
No Prior Experience with SQL, Power BI, or Data Analytics Required: This course is designed to take you from beginner to professional level, step-by-step.
Learning Outcome:
By the end of this course, you will be able to:
-Understand the fundamentals of data analytics.
-Master Excel for advanced data handling and business formulas.
-Perform data cleaning, transformation, and modeling with Power Query and Power Pivot.
-Build dynamic dashboards and reports using Excel and Power BI.
-Write SQL queries for data extraction and analysis
Part 1:
● Introduction to Data Analytics
● Component of Data Analytics
● Tools need to be a Data analyst
● Scope of a Data Analyst
● Why Data Analyst
● Cell formatting: Copy, Cut and Paste
● Formatting Shortcut
● Text function (Join and Split)
● Freezing Panes
Part 2:
● Cell referencing (Relative vs absolute)
● Self-Finance handle in Excel
● Conditional formatting
● Data Structure: Shorting and Filtering
● Customizing header and footer
● Using Print area and print related tutorial Excel
Part 1:
● Logical Function(Filter ,IF, And , OR )
● Carefulness of VLOOKUP, HLOOKUP
● Using SUMIF, COINTIF, SUMIFS, COUNTIFS, COUNTA, INDEX & MATCH function
● MAXIFS, MINIFS, AVERAGEIFS
Part 2:
● What if analysis
● Inserting calculated filed and calculated items
● Shorting and filtering technique with pivot table
● Slicer in Pivot table (creating, changing and formatting)
● Dynamic pivot table using slicer
Part 1:
● Understand table structure
● Understand various relationships
● Understand primary key and foreign key
Part 2:
● Using Measure in power pivot
● Data Analysis with Power pivot
● Dax in power pivot
Part 1:
● What is power query
● Understand the table structure
Part 2:
● Creating data model
● Data analysis with Powerpivot
Part 1:
● Using power query | Power Pivot| Web scrapping data | Dax

Data Analytics Faculty

Data Science Specialist & Faculty
Get Course Completion and Assessment Certificate at the end of the course
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