Advanced Excel Institute -Excel | Power BI | Tableau & SQL Training in Chandigarh
Course Content
Module 1: Excel Foundations & Data Handling
- 1. Getting Started with Excel
- Navigating the Excel interface: ribbons, tabs, and quick access toolbar
- Understanding the difference between workbooks and worksheets
- Opening, saving, and managing Excel files efficiently
- Customizing the Excel environment for better productivity
- 2. Working with Data Entry
- Entering and editing data accurately
- Using keyboard shortcuts for faster work
- Understanding data types: numbers, text, dates, and currency
- Preventing common mistakes in data entry
- 3. Formatting for Clarity
- Applying number formats, date formats, and custom formats
- Adjusting column widths, row heights, and alignment for readability
- Using cell styles for consistency
- Adding borders, shading, and themes for professional-looking sheets
- 4. Formulas & Basic Functions
- Understanding the formula bar and how Excel calculates
- Using basic arithmetic formulas (+, –, *, /)
- Introduction to common functions: SUM, AVERAGE, MIN, MAX, COUNT
- Understanding cell references (relative, absolute, mixed) and when to use them
- 5. Organizing & Structuring Data
- Sorting data alphabetically, numerically, and by custom order
- Filtering data to find exactly what you need
- Freezing panes and splitting windows for large datasets
- Grouping and outlining rows or columns for better navigation
- 6. Data Cleaning Essentials
- Removing duplicates and fixing empty cells
- Trimming extra spaces and correcting inconsistent text
- Handling errors like #DIV/0! and #N/A
- Converting text to numbers or dates
- 7. Introduction to Data Validation
- Creating drop-down lists for consistent data entry
- Setting rules for acceptable inputs
- Preventing invalid entries with custom messages
Module 2: Advanced Excel for Data Analysis
- 1. Logical Functions for Smarter Decisions
- Understanding the IF function for simple decision-making
- Combining multiple conditions with AND & OR
- Writing nested IFs for multi-step logic
- Real-world examples: pass/fail results, sales commission calculation, and project status flags
- 2. Lookup Functions to Find Data Quickly
- Mastering VLOOKUP for vertical data searches
- Using HLOOKUP for horizontal data searches
- Introducing XLOOKUP for faster, more flexible lookups
- Handling errors with IFERROR in lookups
- Practical examples: pulling product prices, matching employee IDs, retrieving customer details
- 3. Text Functions for Data Cleaning & Manipulation
- Extracting specific text with LEFT, RIGHT, and MID
- Finding text positions with FIND and SEARCH
- Combining text with CONCATENATE and TEXTJOIN
- Cleaning messy data with TRIM, PROPER, UPPER, LOWER
- Real-world uses: cleaning customer names, splitting codes, formatting phone numbers
- 4. Date & Time Functions for Reporting
- Understanding Excel’s date and time system
- Calculating differences with DATEDIF and NETWORKDAYS
- Extracting day, month, and year from a date
- Creating dynamic reports with TODAY and NOW
- Practical examples: project deadlines, employee age, workdays between two dates
- 5. Named Ranges & Dynamic Formulas
- Creating and managing named ranges for easier formulas
- Making formulas dynamic with OFFSET and INDEX
- Using structured references in tables
- Real-world use: updating reports automatically when new data is added
- 6. Conditional Formatting for Instant Insights
- Applying color scales, data bars, and icon sets
- Creating custom rules for highlighting important data
- Using formulas in conditional formatting for advanced logic
- Examples: highlighting top performers, overdue tasks, and sales below target
- 7. Working with Tables for Structured Data Management
- Converting data into Excel tables for better organization
- Understanding table features like auto-fill and structured references
- Sorting, filtering, and applying slicers to tables
- Benefits for automation and Power Query integration
Module 3: Data Analysis Tools in Excel
- 1. PivotTables – The Heart of Data Analysis
- Understanding what PivotTables are and why they’re powerful
- Creating PivotTables from raw data
- Rearranging (pivoting) fields to view data from different angles
- Summarizing data with counts, sums, averages, and percentages
- Grouping data by dates, numbers, or categories
- Real-world uses: monthly sales summaries, employee performance reports, expense tracking
- 2. PivotCharts – Visualizing Your Analysis
- Converting PivotTables into interactive charts
- Choosing the right chart type for your data
- Formatting PivotCharts for clarity and impact
- Updating charts automatically when PivotTables change
- 3. Grouping, Filtering & Slicers for Interactive Insights
- Grouping data by months, quarters, or custom categories
- Using filters to focus on relevant information
- Adding slicers for quick, visual filtering of PivotTables and PivotCharts
- Practical examples: region-based sales filters, department-wise HR reports
- 4. Data Validation & Drop-Down Lists
- Creating drop-down menus for consistent data entry
- Restricting inputs to specific ranges or formats
- Custom error messages to guide users
- Real-world use: product selection lists, employee role assignment, category tagging
- 5. What-If Analysis – Testing Different Scenarios
- Using Goal Seek to find the value needed to reach a target
- Exploring different possibilities with Scenario Manager
- Understanding Data Tables for quick “what-if” calculations
- Examples: pricing adjustments, budget forecasts, and target planning
- 6. Quick Analysis Tools
- Using the Quick Analysis button for instant formatting, charts, and totals
- Spotting trends and summaries in just a few clicks
- When and why to use Quick Analysis over manual setup
Module 4: Power Query in Excel
- 1. Introduction to Power Query
- What Power Query is and why it’s important for data analysis
- The difference between Power Query in Excel and Power Query in Power BI
- Navigating the Power Query Editor interface
- Understanding the concept of query steps and applied transformations
- 2. Connecting to Multiple Data Sources
- Importing data from Excel files, CSV, text, and XML
- Connecting to databases such as SQL Server, Access, and MySQL
- Pulling data from online sources and web pages
- Combining data from multiple files in a folder into one dataset
- 3. Basic Data Cleaning Techniques
- Removing unwanted rows, columns, and blank records
- Renaming columns for clarity and consistency
- Changing data types (text, number, date, currency)
- Sorting and filtering data inside Power Query
- 4. Advanced Data Transformation
- Splitting columns by delimiter or character position
- Merging multiple columns into one
- Extracting specific portions of text (e.g., first name from full name)
- Trimming spaces and fixing inconsistent text entries
- Replacing values across datasets
- 5. Combining & Merging Data
- Appending queries to stack datasets vertically
- Merging queries to combine datasets horizontally based on a key column
- Understanding join types: inner join, left join, right join, full outer join
- Practical uses: combining monthly sales files, merging customer lists with transaction data
- 6. Adding Calculated Columns & Custom Logic
- Creating custom columns with formulas in Power Query
- Adding conditional columns for automated categorization
- Real examples: calculating discounts, grouping customers by spend level
- 7. Automating Data Refresh & Loading Options
- Setting up refresh so reports update with one click
- Understanding data load options (load to table, load to PivotTable, connection only)
- Best practices for maintaining a clean and efficient Power Query workflow
Module 5: Introduction to Power BI
- 1. Understanding Power BI
- What Power BI is and how it fits into modern data analytics
- Key components: Power BI Desktop, Power BI Service, and Power BI Mobile
- Difference between Excel and Power BI — when to use each tool
- How Power BI connects to different data sources
- 2. Navigating the Power BI Desktop Interface
- Overview of the ribbon, fields pane, and visualizations pane
- Understanding the three main views: Report View, Data View, Model View
- Customizing the interface for a smoother workflow
- 3. Importing Data into Power BI
- Connecting to Excel, CSV, databases, and cloud-based sources
- Using Power Query in Power BI for data transformation
- Setting data types and field properties
- Best practices for importing clean and well-structured data
- 4. Introduction to Data Modeling
- Understanding tables, fields, and relationships
- Creating relationships between multiple datasets
- Primary keys, foreign keys, and cardinality explained
- Avoiding common data model mistakes
- 5. Working with Columns, Measures & DAX
- Difference between calculated columns and measures
- Introduction to DAX (Data Analysis Expressions) for calculations
- Simple DAX formulas for totals, averages, and conditional results
- 6. Introduction to Visualizations
- Adding different chart types: bar, line, pie, map, card, and table
- Choosing the right visual for your data
- Formatting visuals for clarity and better storytelling
- 7. Saving & Sharing Reports
- Saving Power BI Desktop files (.pbix)
- Publishing to Power BI Service for online access
- Overview of how to securely share reports with others
Module 6: Building Interactive Reports in Power BI
- 1. Choosing the Right Visuals for Your Data
- Overview of visual types: bar, line, pie, maps, cards, gauges, tables, and matrices
- Matching visuals to data types for effective storytelling
- Avoiding over-complication by keeping visuals clear and relevant
- 2. Creating and Formatting Visuals
- Adding visuals to the report canvas
- Customizing colors, labels, titles, and legends for better readability
- Using built-in themes or creating custom ones for brand consistency
- Aligning and grouping visuals for a clean, professional look
- 3. Adding Interactivity with Filters and Slicers
- Applying visual-level, page-level, and report-level filters
- Adding slicers for quick category or date-based filtering
- Using multiple slicers together for deeper drill-down analysis
- Real-world examples: filtering sales by region, department, or time period
- 4. Drill-Down, Drill-Up & Drill-Through Navigation
- Setting up hierarchies for drill-down (e.g., Year → Quarter → Month → Day)
- Allowing users to explore details without leaving the main report
- Creating drill-through pages for focused insights on specific data points
- 5. Creating Calculated Fields & Measures with DAX
- Using calculated columns for custom data categories
- Building measures for KPIs, growth rates, and performance metrics
- Common DAX functions for advanced calculations (CALCULATE, DIVIDE, SUMX)
- 6. Designing Effective Report Layouts
- Placing KPIs and key visuals in priority positions
- Grouping related visuals to guide user attention
- Using whitespace strategically for a clean look
- Optimizing for mobile view with responsive layouts
- 7. Publishing & Sharing Your Reports
- Publishing to Power BI Service for online access
- Managing permissions and secure sharing
- Setting up scheduled data refresh for real-time dashboards
Module 7: Advanced Power BI Features
- 1. Advanced Data Modeling
- Managing relationships between multiple datasets
- One-to-many, many-to-many, and bidirectional relationships explained
- Using role-playing dimensions (e.g., Order Date vs. Ship Date)
- Designing efficient star and snowflake schemas for faster performance
- 2. Advanced DAX for Deeper Insights
- Understanding filter context vs. row context
- Using CALCULATE, FILTER, and ALL for flexible calculations
- Time intelligence functions (YTD, QTD, MTD, SAMEPERIODLASTYEAR)
- Creating running totals, ranking, and percentage of total metrics
- 3. Custom & Advanced Visualizations
- Installing visuals from the Power BI Marketplace
- Using decomposition trees, waterfall charts, gauges, and KPI cards
- Creating bookmarks for guided storytelling and presentations
- Adding dynamic tooltips with additional insights
- 4. Working with Hierarchies
- Building date, location, and product hierarchies
- Enabling drill-down and drill-up navigation
- Grouping related fields for better report usability
- 5. Conditional Formatting & KPIs
- Applying conditional formatting to tables, matrices, and charts
- Creating color-coded KPIs for performance tracking
- Designing dynamic status indicators (red/yellow/green)
- 6. Automation & Collaboration
- Publishing reports to Power BI Service workspaces
- Setting up row-level security (RLS) to control data access
- Automating report refresh with scheduled updates
- Creating data alerts and subscriptions for key metrics
- 7. Performance Optimization
- Reducing file size and improving report speed
- Using aggregation tables for large datasets
- Writing efficient DAX formulas to prevent slow calculations
Module 8: Real-World Business Projects
- Operations and inventory management dashboard
- Sales performance analysis dashboard
- Financial reporting and forecasting in Power BI
- HR analytics – employee performance and attrition trends
- Marketing campaign analysis and ROI tracking
Offce Address
SCO 85-86, 4th Floor, Sector 34A,
Chandigarh, 160034.
Mohali Branch
204, Divine World, Kharar Landran Road,
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