Microsoft Power BI: Beginner to Advanced Intelligence

Learn how to prepare data for Power BI dashboards by entering data by hand or importing from Excel and CSV files, apply transformations, and visualize with charts and tables.

view and explore imported data in power bi using the table view, switch between tables, and use filters, column options, and quick copy to spreadsheets.

Discover the simplest way to enter data in Power BI with Enter Data, create and edit a table (name, age, balance), and load it for viewing.

Import an Excel workbook into Power BI via Get Data, select sheets to load as tables, and use the query editor to set the first row as headers.

Import csv files into Power BI with text/csv, set encoding and delimiter, and load data while fixing headers in the query editor.

Import all sheets from TV shows.xls, plus a CSV and a tab-delimited TSV, into Power BI to practice data preparation.

Import Excel, CSV, and TSV data via Get Data into Power BI, fix the actors headers with the first row, and verify tables in table view.

Explore Power BI data types, configure them correctly, and apply best practices to enhance dashboards. See how proper data types enable date pickers and accurate calculations.

Learn to work with numbers in Power BI by converting data types to decimal, setting decimals, applying currency, and creating calculated columns with bracket references.

Learn to work with text columns in Power BI, concatenate gender and name using the ampersand, and apply double quotes for added text between fields.

Learn to manipulate dates in power bi by extracting month parts, using month numbers, adding or subtracting days, computing date differences, and creating cutoff dates with the date function.

Explore boolean values and blanks in Power BI, test true or false, test for blanks, and combine results with and, or, and not functions.

Explore how visuals enhance dashboards, weigh their advantages and disadvantages, and learn to create bar, line, pie charts, and cards in Power BI using an insurance sales dataset.

Navigate the Power BI visual editor interface, manage pages, create and format visuals, and use data, filters, and date hierarchy to analyze and customize visuals.

Learn to create and customize a bar chart in Power BI to compare sales by gender, including filtering, title and axis cleanup, data labels, and color options for a report.

Learn to build a line chart in Power BI that shows monthly sales trends by configuring sales amount and record date, with precise formatting, markers, and clean axis labels.

Create a pie chart in Power BI to show sales distribution by gender. Adjust the legend, rename the category to gender, and enable detail labels with percentages.

Discover how Power BI visuals share the same underlying table and learn to think in tables first, then convert data into any chart type.

Learn how to filter chart data in Power BI using visual, page, and all-page (report) filters to exclude other and refine sales by gender across multiple visuals and pages.

Create a Power BI card visual to display total sales, format as currency with no decimals, and adjust the title, alignment, and display settings for a clean dashboard.

Learn to build a Power BI table visual illustrating sales by gender. Format advisor IDs with count distinct values, withdrawals, alignment, and a clear title.

Explore how to combine visualizations in Power BI to build a dashboard from City Life Insurance data, answering sales, withdrawals, regional performance, product contribution, and top advisors.

Build a city life dashboard in Power BI from insurance sales data, using cards for totals, a sales trend, regional and product breakdowns, and a top three advisors table.

Explore your first Power BI project with the personal finance dashboard, learn to visualize transactions and determine monthly spending and income without using DAX.

Download your own financial transaction data to power the project dashboard, or use the provided sample data. Compare business vs analyst perspectives as you export via bank CSV.

Create a personal finance dashboard in Power BI that visualizes deposits and withdrawals with month-by-month bars, currency formatting, and a financial outlook title with color-coded deposits and withdrawals.

Learn to verify dashboard data accuracy by cleaning transaction data, filtering out irregular deposits and withdrawals, and analyzing month-by-month trends to reveal realistic spending patterns.

Master data analysis expressions (DAX) to power complex calculations in Power BI visuals, from essentials to advanced techniques across three learning sections.

Create your first dax formula in power bi by adding a calculated column and computing net sales as sales amount minus withdrawal amount in the simple data table.

Define measures in Power BI by returning a single value using a specific table and column, then compare dynamic measures with fixed calculated columns and apply filter context.

Learn how calculation context drives DAX measures and row context in Power BI. This lecture explains how visuals and filters modify context, and how calculated columns use implicit row context.

Explore how DAX measures drive visuals in Power BI, creating implicit and explicit measures, using sum or average aggregations, and exploring how filters reveal advisor gender breakdowns.

Explore renaming and deleting measures and columns in Power BI, including automatic formula updates and visual adjustments. Learn to fix visuals after deletions.

Learn how to aggregate values in DAX using calculation context to produce scalars, with common methods for numbers, texts, and dates, including sum, average, min, max, count, and distinct count.

Learn to aggregate numbers in Power BI by creating measures for sum, minimum, maximum, and standard deviation using the cells amount and the insurance data.

Learn how to aggregate text in Power BI using min, max, count, distinct count, and concatenate, and build measures that respond to visuals.

Aggregate dates in DAX using the minimum and maximum functions, and create measures like the minimum of record date and latest date of birth, and observe dates as numbers.

Master DAX conditional functions with the if function in Power BI. Build if-else calculated columns, test conditions on fixed values or columns, and return values or blank.

Explore the switch function in Dax to replace nested ifs, use the flexible form for multi-column checks, and rebrand product ratings to top, mid, bottom with an else.

Learn to compare values in Power BI with DAX operators such as =, >, <, >=, <=, and not, test text and numbers, and handle blanks with is blank.

Explore the calculate function in DAX, which blends an aggregation with a calculation context to return a scalar value. Shrink or expand the context with optional filters.

Learn to use calculate with filters in Power BI to constrain the calculation context, create a total insurance sales measure with the filter function, and understand context modifiers.

Explore how the calculate function combines aggregation with context to return a single value, then build insurance and investment measures and their ratio with filters that exclude 0.5 withdrawals.

Discover how visuals apply implicit context to measures, filtering total sales by product and product rating. Understand the DAX behind the scenes and how to adjust implicit context when needed.

Discover how Power Query transforms and automates data into polished tables for dashboards, using the what you see is what you get editor to replay steps.

Explore the Power Query Editor to clean and transform data before loading it into Power BI. Navigate the interface, edit queries, switch tables, and track applied steps for data preparation.

Explore how to clean data in Power Query by removing top, bottom, alternate, blank, and duplicated rows, with practical examples and a roadmap for applying these techniques.

Remove top rows in Power Query after importing data from Excel, promote the first row as headers, and fix column names to enable accurate visuals and formulas.

Master cleaning data in Power BI by removing bottom rows, removing alternate rows, and removing blank rows with Power Query, leaving the real data intact.

Learn how to remove duplicated rows in Power BI by selecting the row column or multiple columns (hold ctrl) or all columns (ctrl-a), keeping the first record.

Learn how to remove and rename columns in Power BI using Power Query Editor, deleting the employee id column and renaming the row column to position, then applying changes.

Replace values in Power Query Editor with clear text labels using match entire cell contents, ensuring correct replacements and verifying results in Data Explorer.

Learn to filter rows in Power Query for Power BI using text and number filters, convert tenure in month to a whole number, and remove steps to speed calculations.

Master filter rows in Power Query within Power BI, including positive and negative filters, and learn to test results and avoid missing data.

Learn to clean transaction data with Power Query by removing top comments and bottom footnotes, delete an empty column, and remove deposit rows to enable withdrawal analysis in Power BI.

Learn to clean data in Power BI by importing an excel power query file, removing top and bottom rows, and filtering deposit amounts or transaction descriptions.

Learn how to convert data types in Power Query, including numbers, date, and text, with practical tips on handling conversion steps, preserving decimals, and avoiding data loss.

Identify and fix common Power Query errors in Power BI by validating file paths and addressing file not found, renamed, and data type conversion issues.

Use Power Query to import and reduce data size before loading into Power BI. Use DAX for calculations after data is loaded.

Practice data import and data transformation for a personal finance dashboard in Power BI. Learn to prepare the spreadsheet by removing non-data rows and system information to enable clean visualization.

Import and clean personal finance data in Power BI by loading an Excel workbook, removing top rows, promoting headers, and validating data types, then rename the table to transaction.

Translate a real-life sales request into a Power BI dashboard for CityLife, delivering total sales and withdrawals with regional breakdowns and top advisor insights to drive 8% growth.

Plan a Power BI dashboard by outlining key measures: sales, withdrawals, and net sales, and by region and advisers; implement cards, a region bar chart, and an advisor details table.

Import insurance data from an Excel workbook into Power BI, load insurance data tab, review fields like advisor, sales, withdrawal, region, and product details, and compute net sales for visuals.

Develop a complete Power BI dashboard for life insurance by building current and past year sales, withdrawals, and net sales visuals with DAX filters.

Validate Power BI dashboard data by comparing totals and breakdowns against the insurance data source across early data stages, ensuring accuracy in the final visuals.

Learn to style Power BI visuals by formatting currency and decimals, adding card backgrounds and borders, aligning layouts, and enabling current year and past year sales comparisons, color tweaks.

Explore how data models in Power BI unify data from multiple sources and enable efficient storage by linking tables with relationships in the workbook.

Power BI relationships act as filters, not joins, guiding what rows appear across related tables. For example, a relationship filters sales by advisor, not duplicating records.

Explains directional relationships in Power BI data models, showing how filters flow from the product info table to the sales table along the arrow, while filtering does not go backward.

Master Power BI data modeling by mapping 1-to-1, 1-to-many, and many-to-many relationships between tables. Identify the correct relationship by checking column uniqueness and duplicates in sample product and sales data.

Explore active and inactive relationships in Power BI, learn how filters pass through, and how to toggle relationships on and off using model view, apply changes, DAX.

Configure relationships in power bi by creating 1-to-1, 1-to-many, and many-to-many links between tables, using drag-and-drop or manage relationships, and ensure active paths without ambiguous paths.

Explore organizing data as one big table, its pros and cons, and its limitations for large datasets, with a merged object table enabling easy filtering of advisors and products.

Organize data with a star schema, linking a central fact sales table to dimension tables like product and advisor via product ID and advisor ID for Power BI analysis.

Use one big table for simplicity until performance bottlenecks around 10 million rows, then switch to star schema for larger data; if not in charge, follow team choice.

Learn how the related function pulls a value from a related table via a one-to-many relationship in a calculated column, using row context to bring sales data into organization table.

Enable a measure to use the relationship function, temporarily enabling an existing relationship between two tables to selectively affect that measure while keeping others unchanged.

Master cross filter in Power BI by adjusting existing relationships with the cross filter function, choosing direction, and combining with use relationship to apply temporary relationships.

Practice challenge teaches you to connect the tables and fix the dashboard in Power BI by inspecting table relationship and star schema with dimension advisor, dimension product, and fact sales.

Learn to connect tables in Power BI by fixing relationships, activating filters, and using product ID to ensure dimension tables filter the fact table, building a working star schema.

Explore advanced DAX topics by using the ALL function to modify the calculation context and see CALCULATE in action with total sales from a simple table and insurance data.

Learn how the allexcept function removes all filters except on the product column, enabling the calculation of total sales by product in Power BI.

Use the remove filter function to clear filters on specific columns in Power BI, demonstrating how removing product rating filters affects sales measures across visuals.

Use the selected value function to reveal the current filter context, returning the single product rating when unique, or an alternative result when multiple ratings exist.

Learn to concatenate texts with DAX's concatenate function and the ampersand operator, use selected value for dynamic labels, and apply results to breakdown tables and measures.

Learn how to split text in Power BI using left, find, and mid functions to extract first and last names from advisor names, handling dynamic lengths with length and subtraction.

Learn how to replace text in Power BI with the DAX substitute function, including replacing spaces with underscores and controlling occurrence counts.

Explore Power BI text transformations using upper, lower, and trim to standardize case and clean spaces, with trim removing extra spaces and compressing multiples to one.

Practice manipulating the calculation context to extract fund name and rating, calculate sales by fund name and rating, filter mature funds at or above five million, and build visuals.

Demonstrates cleaning and transforming the mutual fund sales dataset in Power BI: split fund name, extract rating, compute total sales, and apply advanced filtering for more than five million.

Leverage DAX variables to store results, reuse calculations, and simplify Power BI formulas. Learn to define variables, return values, and use if logic for net sales.

Use DAX variables to compute total sales per product in Power BI. Create a calculated column that captures the product ID and filters the sales table, independent of relationships.