First 20 students get 50% discount. Hurry up!

Data Analyst

Course Description

The Data Analyst Program equips learners with the skills and tools needed to analyze, interpret, and visualize data effectively. This hands-on course covers industry-standard software and programming languages, preparing participants for roles in data analysis, business intelligence, and data-driven decision-making.

What You’ll Learn?
  • Work on hands-on projects to build a strong, job-ready portfolio.
  • Analyze real-world datasets to solve practical business challenges.
  • Clean, organize, and prepare data for accurate analysis.
  • Use industry tools such as Excel, Power Query, VBA, SQL, and Power BI effectively.
  • Create clear reports and data visualizations to present insights.
  • Develop both technical expertise and analytical thinking for real-world applications.
Why It Matters:

In today’s data-driven world, businesses rely on insights to stay competitive. This course helps you bridge the skills gap, unlock career opportunities, and transform raw data into actionable insights. Learn to automate workflows, think analytically, and make data-driven decisions that deliver real results.

Step into the world of analytics and become a professional that businesses depend on to make smarter, faster, and more informed decisions.

Course Curriculum

The Data Analyst Course is designed to equip you with practical skills in data analysis using industry-leading tools such as Advanced Excel, Power Query, VBA Macros, SQL, and Power BI. This hands-on program focuses on real-world applications, helping you collect, clean, analyze, and visualize data effectively.

You will learn how to automate tasks with VBA Macros, manage and query databases using SQL, and create interactive dashboards in Power BI to present meaningful insights. Through practical projects and real-world datasets, this course builds your problem-solving abilities and analytical thinking.

By the end of the course, you will be prepared to make data-driven decisions and pursue career opportunities in data analysis and business intelligence.

Advanced Excel

This training program is designed to equip learners with the essential skills needed to master Microsoft Excel, from basic to advanced functionalities. Whether you're a beginner or looking to advance your existing Excel knowledge, this course will guide you through every key aspect of Excel, focusing on both fundamental and complex tools, as well as data analysis, dashboard creation, and MIS Reporting.

  • Introduction to Advanced Excel: An overview of MS Excel's advanced features and functions, emphasizing key functionalities for efficiency.
  • Overview of MS Excel & Shortcut Keys, Data Selection Techniques: Introduction to essential shortcut keys and efficient methods for selecting data in Excel.
  • Arithmetic Operations & Cell Reference (Relative, Absolute, Mixed): Performing calculations in Excel using basic arithmetic operations and understanding different cell reference types (relative, absolute, and mixed).
  • Clipboard, Copy Paste, Paste Special, Format Painter: Mastering the use of the clipboard, copy-pasting techniques, Paste Special for advanced options, and using Format Painter for consistent styling.
  • Font Alignment, Number Formatting & Custom Number Formatting: Customizing text alignment, applying number formatting, and creating custom number formats to enhance data presentation.
  • Conditional Formatting, Format as Table, Cell Styles: Applying rules for conditional formatting, formatting data as tables, and using pre-defined cell styles to improve visual appeal and readability.
  • Insert Row, Column, Cells, Delete Row, Column, Cells, Hide and Unhide: Modifying the worksheet structure by inserting, deleting, and hiding/unhiding rows, columns, and cells for better data management
  • Protection (Worksheet, Workbook, Cells), Move and Copy Sheet/File: Securing data by protecting worksheets, workbooks, and specific cells, and learning how to move or copy sheets and files.
  • Fill, Clear, Sorting & Custom Sorting, Filter & Advanced Filter: Using the fill feature for series, clearing data, sorting (including custom sorting), and applying filters (basic and advanced) to analyze data effectively.
  • Find & Replace, Go To Special: Quickly locating and replacing data using the Find & Replace feature and utilizing Go To Special for advanced selection options.

  • Pivot Table: Learning how to summarize, analyze, and present data dynamically using Pivot Tables, including grouping, filtering, and aggregating large datasets.
  • Aggregation: Use functions like Sum, Average, Count, Min, Max.
  • Group Data: Group data by categories, dates, or ranges.
  • Row Labels: Arrange data into categories.
  • Column Labels: Display categorized data in columns.
  • Values Area: Show summarized values like totals or averages.
  • Filters: Apply filters to view specific data.
  • Interactive Filtering: Use slicers and filter tools.
  • Refresh Data: Update pivot tables when source changes.
  • Group by Dates: Year, Quarter, Month, Day.
  • Group by Numbers: Create ranges like 0–10, 11–20.
  • Group by Text: Manually categorize similar data.
  • Calculated Fields: Create formulas in pivot tables.
  • Calculated Items: Add custom calculations within items.
  • Sorting: Sort data ascending/descending.
  • Advanced Filters: Filter by conditions or top/bottom values.
  • Data Sources: Create pivot tables from multiple or external sources.
  • Pivot Charts: Create dynamic charts linked to pivot tables.
  • Slicers & Timelines: Improve visual filtering.
  • Conditional Formatting: Highlight key data visually.
  • Illustrations: Insert images, shapes, SmartArt, and graphics.
  • Charts: Create and customize bar, line, pie charts, etc.
  • Sparkline: Mini charts inside cells to show trends.
  • Hyperlink: Link sheets, files, websites, or cells.
  • Header & Footer: Add titles, page numbers, and dates for print.
  • Page Layout: Adjust margins, orientation, and paper size.
  • Print: Set print area, scaling, and preview options.
  • Page Setting: Configure headers, footers, and repeating rows/columns.

  • Formula Writing Skills: Mastering the basics of constructing and using formulas, ensuring correct syntax, and utilizing appropriate referencing for calculations.
  • Complex Formulas: Building advanced formulas by combining multiple functions, operators, and references to solve more complex data challenges.
  • Text Functions: Using functions like CONCATENATE, CONCAT, UPPER, LOWER, PROPER, TEXTJOIN, TEXT, TRIM, CLEAN, CHAR, CODE, FIND, SEARCH, EXACT, LEFT, RIGHT, MID, SUBSTITUTE, REPLACE, TEXTBEFORE, TEXTAFTER, TEXTSPLIT, ARRAYFORMULA, VALUE, NUMBERVALUE and LEN to manipulate and format text data.
  • LOGICAL FUNCTIONS: Applying functions such as IF, IFS, AND, OR, XOR, NOT, IFERROR, SWITCH, TRUE, and FALSE to create conditional formulas that control the flow of data.
  • DATE & TIME FUNCTIONS: Leveraging functions like DATE, DATEDIF, DATEVALUE, DAY, DAYS, DAYS360, EDATE, EOMONTH, HOUR, ISOWEEKNUM, MINUTE, MONTH, NETWORKDAYS, NETWORKDAYS.INTL, NOW, SECOND, TIME, TIMEVALUE, TODAY, WEEKDAY, WEEKNUM, WORKDAY, WORKDAY.INTL, YEAR and YEARFRAC to work with dates and time values for calculations and data manipulation.
  • LOOKUP & REFERENCE FUNCTIONS: Using ADDRESS, CHOOSE, COLUMN, COLUMNS, FILTER, FORMULATEXT, GETPIVOTDATA, HLOOKUP, HYPERLINK, INDEX, INDIRECT, LOOKUP, MATCH, OFFSET, ROW, ROWS, SORT, SORTBY, TRANSPOSE, UNIQUE, VLOOKUP, XLOOKUP and XMATCH to find and retrieve data from large datasets.
  • STATISTICS FUNCTIONS: Applying functions like AVERAGE, AVERAGEA, AVERAGEIF, AVERAGEIFS, COUNT, COUNTA, COUNTBLANK, COUNTIF, COUNTIFS, FREQUENCY, GROWTH, LARGE, MAX, MAXIFS, MIN, MINIFS, RANK.AVG, RANK.EQ, SMALL, and MEDIAN for data analysis and summarizing statistical insights.
  • MATH & TRIG FUNCTIONS: Using mathematical and trigonometric functions such as ABS, AGGREGATE, CEILING, CEILING.MATH, INT, MOD, ODD, Even, PRODUCT, RANDBETWEEN, ROUND, ROUNDDOWN, ROUNDUP, SQRT, SUBTOTAL, SUM, SUMIF, SUMIFS, SUMPRODUCT and PI for complex calculations.
  • FINANCE FORMULAS: Utilizing financial functions such as PMT, IPMT, PPMT, FV, NPV, IRR, and RATE to perform financial calculations like loan payments and investment returns.
  • DATABASE FUNCTIONS: Using DSUM, DCOUNT, DAVERAGE, DGET and similar functions to work with and analyze large datasets or databases.
  • DEFINED NAMES: Defining and using named ranges and constants to simplify formulas and improve worksheet readability.
  • INFORMATION FUNCTIONS: Working with functions like ISBLANK, ISNUMBER, ISERROR, and TYPE to analyze and check data types or status in cells.
  • ERROR HANDLING: Managing errors in formulas by using functions like IFERROR, ISERROR, and IFNA to prevent issues and improve accuracy.
  • ARRAY FUNCTIONS: Creating array formulas that perform multiple calculations on a range of data, returning either single or multiple values.
  • NESTED LEVEL FORMULAS: Combining multiple functions within a single formula to create more advanced logic and calculations (e.g., nested IF or SUMIF functions).
  • FORMULA AUDITING: Using tools like Trace Precedents, Trace Dependents, Evaluate Formula, and Show Formulas to troubleshoot and analyze formulas in the worksheet.
  • CALCULATION: Configuring Excel's calculation options to choose between automatic or manual recalculation, and understanding how Excel recalculates formulas.
  • INTERVIEW QUESTIONS AND ANSWERS: A focused section on common Excel interview questions and answers to help prepare for job interviews that require advanced Excel skills.

  • Sort & Advanced Filter: Learning how to organize data by sorting it in various ways (e.g., alphabetically, numerically) and using advanced filters to extract specific data based on complex criteria.
  • Text to Column: Using the Text to Columns feature to split text into separate columns based on delimiters (such as commas, spaces, or custom delimiters).
  • Flash Fill: Automating data entry using the Flash Fill feature, which recognizes patterns and completes data automatically (e.g., splitting or combining names, formatting numbers).
  • Remove Duplicates: Identifying and removing duplicate entries in a dataset to clean up and ensure unique data values.
  • Data Validation: Applying Data Validation rules to control the type of data entered into cells, such as setting limits, drop-down lists, and custom validation rules.
  • Consolidate: Using the Consolidate feature to combine data from multiple worksheets or workbooks into a single summary table, facilitating data analysis across sources.
  • What-If Analysis: Utilizing What-If Analysis tools such as Scenario Manager, Goal Seek, and Data Tables to analyze different outcomes based on variable inputs.
  • Forecast Sheet: Creating a Forecast Sheet to predict future trends and visualize data based on historical patterns using Excel's forecasting features.
  • Group and Ungroup: Grouping and ungrouping rows or columns to organize data into collapsible sections for better data management and presentation.
  • Subtotal: Using the Subtotal function to automatically calculate subtotals and summary statistics (like sum, average, count) for grouped data.
  • Comments: Understanding how to add, edit, and format comments in Excel to provide additional information or notes within cells.
  • Show All Comments: Displaying all comments in a worksheet at once, making it easier to review and manage feedback or notes.
  • Show/Hide Comment: Using the Show/Hide Comment feature to control the visibility of individual comments in cells.
  • Workbook Views: Exploring different Workbook Views (e.g., Normal, Page Layout, and Page Break Preview) to optimize your worksheet for editing, printing, or reviewing.
  • Show: Learning how to Show hidden elements in the workbook such as sheets, comments, or formulas.
  • Zoom: Adjusting the zoom level in Excel to focus on specific areas of the worksheet, making it easier to work with large data sets.
  • New Window: Opening a New Window for the same workbook, allowing you to view and work with different parts of the workbook simultaneously.
  • Split: Using the Split feature to divide the worksheet window into multiple panes, enabling easier navigation and viewing of different areas of the worksheet.
  • Freeze Panes: Freezing specific rows or columns with the Freeze Panes feature to keep headings visible as you scroll through large datasets.
  • Switch Windows: Quickly switching between open windows in Excel (such as multiple workbooks) to compare or work with different sheets simultaneously.

Power Query

This course covers how to import, clean, and combine data from various sources using Power Query, allowing you to create efficient and accurate reports and visualizations. Key topics include data transformation, merging and appending queries, using custom functions, filtering and sorting data, creating calculated columns, and connecting to external data sources like databases, web services.

  • Overview of Power Query: Understanding what Power Query is and how it fits in Excel.
  • Loading Data: Importing data from various sources (Excel, CSV, Web, etc.).
  • Power Query Interface: Familiarizing with the Power Query Editor interface.
  • Basic Data Transformation: Simple transformations like renaming columns, removing data.

  • Data Cleaning Techniques: Removing duplicates, handling missing data, etc.
  • Filtering and Sorting Data: Sorting and applying filters to your Dataset.
  • Adding and Removing Columns: Techniques to add calculated columns, remove unwanted columns.
  • Merging Queries: Combining data from multiple sources using merge. Simple transformations like renaming columns, removing data.

  • Grouping and Aggregating Data: Using Group By function and applying aggregations.
  • Pivoting and Unpivoting Data: Reshaping data for better analysis and reporting.
  • Conditional Columns: Creating new columns based on conditional logic.
  • Advanced Filtering and Sorting Techniques: Advanced options for sorting, filtering, and splitting data.

  • Query Dependencies and Optimization: Understanding query dependencies and optimizing performance.
  • Refreshing Data: Automating data refresh and scheduling updates.
  • Finalizing and Loading Data to Excel: Exporting transformed data into Excel for reporting.
  • Power Query Best Practices: Tips and best practices for efficient use of Power Query.

Power Pivot

Power Pivot is an Excel add-in for advanced data modeling, allowing users to handle large datasets and create relationships between tables. It uses DAX (Data Analysis Expressions) for calculations, aggregations, and data analysis, making it essential for business intelligence and reporting.

  • What is Data Modeling?
    Organizing and structuring data for effective analysis
    Enabling insightful analysis by creating relationships between tables (fact and dimension)
  • Key Concepts:
    Understanding fact and dimension tables
    Importance of data modeling in analytics

  • Tables and Relationships:
    Use Excel Tables (Ctrl + T) to organize data
    Create relationships between tables using PowerPivot
  • Normalization:
    Break down data into separate tables to avoid duplication (e.g., Customers, Orders, Products)
  • Star Schema:
    Structure data with one fact table (e.g., Sales) and multiple dimension tables (e.g., Customers, Time)
  • Power Query:
    Load, clean, and transform data from different sources

  • PivotTables:
    Summarize and analyze data using relationships in the data model
  • Building Relationships:
    Understand one-to-many vs. many-to-many relationships
    Use “Manage Relationships” in PowerPivot to link tables
  • Key Tools for Data Modeling in Excel:
    PowerPivot: Create data models, establish relationships, and write DAX formulas
    Power Query: Transform, clean, and load data
    PivotTables: Visualize and analyze data

  • What is DAX?
    Data Analysis Expressions (DAX) is a formula language used for data modeling and analysis in Excel
  • Basic DAX Functions:
    SUM: Adds values in a column
    AVERAGE: Calculates the mean of a column
    COUNT: Counts rows in a column
    MIN/MAX: Returns the smallest or largest value
  • Filtering Functions:
    CALCULATE: Modifies filter context and evaluates expressions
    FILTER: Returns a filtered table
    ALL: Removes filters from a column or table
    ALLEXCEPT: Removes all filters except specified columns
  • Time Intelligence Functions:
    YTD (Year-to-Date): Calculates cumulative totals for the current year
    DATEADD: Shifts dates by intervals (months, years)
    SAMEPERIODLASTYEAR: Compares data with the same period in the previous year
  • Conditional Functions:
    IF: Returns results based on conditions
    SWITCH: Evaluates multiple conditions
    IFERROR: Handles errors in calculations
  • Advanced DAX Functions:
    RELATED: Retrieves related values from another table
    LOOKUPVALUE: Fetches values based on matching criteria
    EARLIER: Refers to an earlier row context
  • Optimizing DAX:
    Write efficient formulas and resolve common errors (circular references, incorrect relationships)
    Use DAX Studio to analyze and optimize queries
  • Business Use Cases:
    Profit Margin calculation
    Running Totals (cumulative analysis)
    Percentage Change and growth analysis

VBA Macros

This VBA & Macros training program helps learners master automation in Excel. From basic to advanced skills, you'll learn to automate repetitive tasks like formatting, data compiling, data splitting, report automation, email automation, calculations, and more through real-time live projects using the Visual Basic for Applications (VBA) programming language. This course focuses on both recording macros and writing custom VBA code to save time and improve efficiency.

  • Quick Recap of Microsoft Excel
  • Introduction to the Developer Ribbon Tab
  • What is VBA/Macro in Excel?
  • Introduction to the Visual Basic Editor (VBE)
  • Navigating the VBE Interface
  • Customizing the VBE Environment
  • Introduction to the Macro Recorder
  • Executing and Modifying Recorded Macros
  • Saving Macro-Enabled Workbooks
  • Introduction to Sub and Function Procedures
  • Understanding the Excel VBA Object Model (Essential for VBA Mastery)
  • Properties and Methods in VBA
  • Working with the Application Object: Key Properties
  • Working with Range Objects
  • Writing and Using Comments in VBA Code
  • Variables, Data Types, and Constants
  • Finding the Last or Next Available Row/Column
  • Selecting Rows, Columns, and Tables (Statically and Dynamically)

  • Introduction to Loops and Conditional Statements
  • Working with Conditional Statements (If, Else, ElseIf, Select Case)
  • Working with Loops (For, For Each, Do While, Do Until)
  • Working with Message and Input Boxes
  • Understanding With-End With Constructs
  • Controlling Program Flow (Exit, GoTo)
  • Introduction to Arrays in VBA
  • Introduction to Excel VBA Functions and Worksheet Functions
  • Understanding the Difference Between R1C1 and A1 Cell Referencing Styles
  • Distinguishing Between Worksheet Functions and Active Cell Formulas
  • Using VBA to Work with Excel Functions
  • Using Worksheet Function in VBA
  • Creating and Using Function Procedures
  • Introduction to User Defined Functions (UDF)
  • Fixing Formula Arguments in VBA
  • Creating and Working with Custom Functions
  • Error Handling and Debugging Techniques

  • Working with Pivot Tables Using VBA
  • Automating Chart Creation with VBA
  • Sorting and Filtering Data with VBA
  • Understanding Add-ins in Excel
  • Exploring Different Types of Excel Events
  • Launching External Applications from Excel
  • Interacting with Other Microsoft Office Applications (Word, Outlook, etc.)
  • Controlling Excel from Another Application (e.g., Word, PowerPoint)
  • Sending Personalized Emails via Outlook
  • Sending E-mail Attachments from Excel
  • File Management: Working with Files and Folders in VBA
  • Converting and Saving Excel Files as PDFs Using VBA

  • Understanding Excel Events (Workbook, Worksheet, etc.)
  • Introduction to UserForms
  • Exploring Form Controls vs ActiveX Controls
  • Working with UserForm Controls (TextBox, ComboBox, ListBox, etc.)
  • Step-by-Step Process for Creating UserForms
  • Validating User Inputs in UserForms
  • Testing and Debugging UserForms
  • UserForm Design Tips and Best Practices
  • Practical Projects Using UserForms
  • Projects like Data Compiling, Data Splitting, Report Automation, Email Automation

SQL Server

This advanced course offers a deep dive into SQL Server and the core concepts of Database Management Systems (DBMS). Covering everything from foundational database design to advanced T-SQL programming, performance optimization, and real-world application, it equips professionals with the essential skills to efficiently manage and scale databases.

  • Overview:
    Understand the core principles of DBMS and RDBMS, and get familiar with the SQL Server environment
  • Topics Covered:
    Introduction to DBMS & RDBMS.
    SQL Server History and Evolution.
    Key Database Design Features.
    Data Types and their Usage in SQL Server.
    Data Integrity Constraints (PK, FK, UK, NULL, CHECK).
    System Databases in SQL Server.

  • Overview:
    Master the foundational SQL commands and develop proficiency in writing complex queries and understanding T-SQL syntax.
  • Topics Covered:
    SQL Commands Overview (DDL, DML, TCL, DCL).
    Writing and Optimizing Queries.
    T-SQL Programming Essentials.
    Views and Indexed Views – Concepts and Use Cases.
    Triggers: Setup, Usage, and Benefits.

  • Overview:
    Explore advanced SQL features such as stored procedures, functions, cursors, transactions, and performance tuning techniques.
  • Topics Covered:
    Stored Procedures: Creation and Management.
    Functions: Types and Applications.
    Working with Cursors and their Impact on Performance.
    Transactions: Managing Data Consistency and Integrity.
    Concurrency, Locks, and Deadlocks.
    Indexing Strategies and Performance Tuning.

  • Overview:
    Apply the skills learned to solve real-world database challenges through case studies and hands-on exercises.
  • Topics Covered:
    Practical Case Studies (3 real-world scenarios).
    Analyzing and Solving Complex SQL Problems.
    Advanced Query Optimization Techniques.
    Database Performance Benchmarks and Best Practices.
    Troubleshooting and Database Scalability Solutions.
  • Learning Outcomes:
    Design, implement, and optimize relational databases using SQL Server.
    Write efficient SQL queries and T-SQL code for real-world applications.
    Develop stored procedures, functions, triggers, and manage transactions.
    Optimize SQL Server performance through indexing, tuning, and troubleshooting.
    Apply advanced SQL techniques to improve database scalability and integrity.
  • This streamlined, practical course offers clear, actionable knowledge for professionals aiming to master SQL Server and advanced database management.

Power BI

This Power BI course equips professionals with the skills to turn raw data into actionable insights. Covering data acquisition, modeling, reporting, and security management, the course offers hands-on experience with data preparation, creating interactive reports, and implementing security measures. Ideal for beginners or those looking to advance their skills, it empowers learners to use Power BI for data-driven decision-making.

  • 1. Introduction to Power BI
    Overview:
    Explore the core concepts of Power BI, its significance in data analytics, and its role in business intelligence (BI) solutions. Understand how Power BI integrates with the Microsoft ecosystem.
    Topics Covered:
    Introduction to Business Intelligence
    Why Power BI is essential for modern analytics
    Benefits of Power BI over traditional BI tools
  • 2. Navigating Power BI Interface
    Overview:
    A comprehensive tour of the Power BI Desktop interface, emphasizing the workspace, ribbons, panes, and the functionality of different tabs.
    Topics Covered:
    Overview of Power BI Desktop components
    Introduction to the Report, Data, and Model views
    Key features like filters, fields pane, and visualizations pane
  • 3. Connecting to Data Sources
    Overview:
    Learn to connect Power BI to a wide variety of data sources, both on-premises and cloud-based, ensuring seamless data extraction.
    Topics Covered:
    Connecting to databases (SQL Server, Oracle, etc.)
    Importing data from Excel, CSV, web APIs, and online services (e.g., Google Analytics, SharePoint)
    Connecting to cloud platforms (Azure, Google BigQuery, etc.)
  • 4. First Steps: Importing and Transforming Data
    Overview:
    Learn to connect Power BI to a wide variety of data sources, both on-premises and cloud-based, ensuring seamless data extraction.
    Topics Covered:
    Using Power Query Editor for data cleaning
    Basic transformations: filtering, merging, appending, and grouping data
    Handling nulls, missing values, and error handling
  • 5. Data Preparation Best Practices
    Overview:
    Learn how to prepare data effectively for analysis by applying industry best practices for data cleaning and shaping.
    Topics Covered:
    Removing duplicates, handling errors, and standardizing data
    Creating calculated columns and custom transformations
    Merging and appending data from different sources

  • 1. Building Robust Data Models
    Overview:
    Understand the importance of data modeling in Power BI and learn how to design effective models using tables, relationships, and data types.
    Topics Covered:
    Principles of relational data modeling
    Creating and managing tables, defining relationships (one-to-many, many-to-many)
    Managing data types and understanding the impact of relationships
  • 2. Creating and Using Dimensions and Hierarchies
    Overview:
    Learn how to define dimensions and hierarchies to facilitate deeper insights and more flexible data exploration.
    Topics Covered:
    Building date, time, and geographical hierarchies
    Utilizing dimensions for drill-down and filtering
    Enhancing user experience through hierarchical structures
  • 3. Introduction to DAX (Data Analysis Expressions)
    Overview:
    Learn the fundamentals of DAX to perform calculations, aggregations, and build dynamic metrics.
    Topics Covered:
    Understanding the syntax and structure of DAX
    Creating calculated columns and measures
    Working with row context and filter context
  • 4. Advanced DAX Functions
    Overview:
    Dive deeper into advanced DAX functionalities, such as time intelligence and complex aggregations.
    Topics Covered:
    Time intelligence functions (YTD, QTD, MTD, etc.)
    Advanced aggregation techniques (SUMX, AVERAGEX, etc.)
    Complex calculations (CROSSJOIN, CALCULATE, etc.)
  • 5. Optimizing Data Models
    Overview:
    Learn strategies to optimize Power BI models for improved performance, efficiency, and scalability.
    Topics Covered:
    Best practices for optimizing data models (e.g., reducing table size, limiting columns)
    Managing relationships for faster querying
    Tips for improving query performance and reducing processing time

  • 1. Designing Compelling Reports
    Overview:
    Learn how to craft engaging, professional reports that convey actionable insights to stakeholders using Power BI's extensive visualization tools.
    Topics Covered:
    Selecting the right visualizations for different types of data
    Designing clear, readable reports with proper layout and alignment
    Using conditional formatting, themes, and custom visuals
  • 2. Customizing Reports for Audience Impact
    Overview:
    Customize reports to ensure maximum engagement and understanding, tailoring the visuals to suit specific business needs.
    Topics Covered:
    Optimizing layouts, color schemes, and visual hierarchies
    Enhancing interactivity with tooltips, slicers, and buttons
    Creating narratives with visuals to simplify decision-making
  • 3. Advanced Report Features
    Overview:
    Enhance the user experience with advanced reporting features that make dashboards and reports more interactive and responsive.
    Topics Covered:
    Using slicers, filters, and dynamic visuals
    Drill-through and drill-down for detailed analysis
    Cross-filtering and synchronizing visuals
  • 4. Creating Dashboards
    Overview:
    Learn how to design effective dashboards that deliver a high-level overview of key metrics in a visually cohesive format.
    Topics Covered:
    Designing real-time dashboards for executive-level reports
    Combining multiple visual elements into a single, cohesive story
    Monitoring KPIs with live data and real-time updates

  • 1. Row-Level Security (RLS)
    Overview:
    Implement Row-Level Security (RLS) to control access to sensitive data, ensuring that each user sees only the data relevant to them.
    Topics Covered:
    Setting up dynamic RLS roles based on user attributes
    Applying security filters to tables and reports
    Best practices for managing security policies
  • 2. Managing Datasets and Parameters
    Overview:
    Learn how to efficiently manage datasets, use parameters for flexibility, and improve interactivity in reports.
    Topics Covered:
    Creating and managing datasets and dataflows
    Using parameters to dynamically adjust queries
    Best practices for dataset versioning and refresh management
  • 3. Optimizing Power BI Performance
    Overview:
    Explore techniques to enhance Power BI report and model performance for faster load times and better user experience.
    Topics Covered:
    Using DirectQuery mode vs. Import mode
    Data compression and optimization techniques
    Aggregations and indexing to improve performance
  • 4. Workspace Management
    Overview:
    Master the use of Power BI Workspaces for organizing and managing reports, dashboards, and dataflows within teams or departments.
    Topics Covered:
    Creating and managing workspaces for team collaboration
    Setting up workspace security and permissions
    Organizing datasets and reports within workspaces
  • 5. Data Refresh & Scheduling
    Overview:
    Learn how to set up automatic data refresh schedules, ensuring that reports and dashboards are always up-to-date.
    Topics Covered:
    Configuring scheduled data refresh for datasets
    Managing refresh failures and error handling
    Best practices for optimizing refresh performance
Author Images
Edward Norton
Founder & CEO

Consectetur adipisicing elit, sed do eiusmod tempor incididunt labore et dolore magna aliqua enim minim veniam quis nostrud exercitation ulla mco laboris nisi ut aliquip ex ea commodo consequat. duis aute irure dolor in reprehenderit in voluptate.

Course Rating

5.00 average rating based on 7 rating

5.0
(7 Review)
5
7
4
0
4
0
4
0
4
0

Reviews

Comment Images
Haley Bennet
Oct 10, 2024

Lorem ipsum dolor sit amet, consectetur adipisicing elit sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.

Comment Images
Simon Baker
Oct 10, 2024

Lorem ipsum dolor sit amet, consectetur adipisicing elit sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.

Comment Images
Richard Gere
Oct 10, 2024

Lorem ipsum dolor sit amet, consectetur adipisicing elit sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.

Write a Review

Rating Here