Microsoft Power BI Desktop and DAX plus Dashboard creation

Download Microsoft Power BI Desktop on your PC from Google or the Microsoft Store, choose language and 64-bit or 32-bit; store updates are automatic while Google requires manual updates.

Explore essential Power BI desktop settings, including managing current file relationships, disabling auto-detect relationships, enabling shape map and Azure map visuals, and setting regional defaults to English Nigeria.

Navigate Power BI desktop by moving through report view, data view, and modeling view to create visuals, establish relationships between tables, and use Power Query to clean and transform data.

Power BI desktop resources - guided learning, sample data, and tutorials - to start building reports and dashboards, and learn DAX functions through official guides and videos.

Import and transform the adventureworks product data in power query, clean and shape it into a dimensional product table and related fact table for Power BI modeling.

Explore Power Query basics in Power BI: differentiate transform and add column, learn how the home tab tools affect existing versus new columns, and prepare clean data for dashboards.

Explore Power Query in Power BI: merge columns and create full names with column from example, compare transform versus add column, and avoid duplicating columns.

Learn to extract text in Power Query using split column and extract functions, including text before, after, or between delimiters and length, to derive domains and usernames.

Fix date format errors in Power BI by aligning regional settings to English United States and converting date columns in Power Query, ensuring global and current file consistency.

Master append queries in Power BI to stack 2015–2017 data into one table, and use merge queries to add columns from a related table via a common delimiter.

Learn how to append three or more tables in Power BI with append query, create a new combined table, and validate year extraction for a single, scalable data source.

Normalize product data by creating a dim_products_color table, adding an index number as product color ID, removing duplicates, then merging with a left outer join to the main product table.

Master merging multiple columns in Power BI using Power Query, creating a new merged table from product dimensions, and selecting key fields for analysis.

Import and rename the returns fact table, link foreign keys to territory and product, distinguish the dimension territory table, and explore two options for building the date table.

Create a static date table in Power Query by loading an Excel calendar, renaming it, and adding day, month, year, week, and quarter columns for Power BI dashboards.

Learn how to build a dynamic calendar table in Power Query for Power BI, using M code, creating year, month, day, weekday, weekend/weekday, and quarter.

Learn to optimize Power BI refresh by excluding dimensional tables such as territory and date, and refresh only the fact table and the fact table return, via refresh preview.

Identify and fix common pa query errors from file path changes, folder renames, and pbix moves; learn to update paths with the advanced editor and ensure dashboards refresh properly.

Master the advanced method to append queries in Power BI by connecting to a folder, using the combine files feature in Power Query, and auto-updating with new year data.

Explore how to create relationships between tables and connect data to enable slicing, dicing, and merging in a data model, and understand why we should build one.

Learn to build and manage one-to-many relationships in a Power BI data model by connecting date, customer, product, and territory tables, activating and troubleshooting relationships to avoid many-to-many issues.

Explore star schema relationships in Power BI by linking date, order date, start date to a fact table, connecting customer, territory, and product keys with active and inactive relationships.

Explore snowflake relationships in Power BI by linking dimension tables through primary and foreign keys to the fact table, enabling accurate filtering and dashboard building.

Create a date table in Power BI using DAX calendar auto, add a year column, and resolve min/max date issues by guiding calendar auto to a specific table.

Define max date and min date with var from the order date, then filter calendar auto to that range and return the restricted dates using DAX.

Learn two methods to add columns in a Power BI date table, including creating a month number and long or short month using format, then sort by month.

Learn to create date-based columns in Power BI using DAX, including week number and weekday with format date, generate quarters with quarter and concatenation, and flag weekends with IF.

Mark a calendar table as a date table using DAX, validate the date table, and restrict nonessential columns to fit your Power BI report view.

Explore the basics of DAX in Power BI, distinguishing implicit and explicit measures from calculated columns, and learn to write robust measures for dashboards.

Explore implicit measures and explicit measures in Power BI, create and compare them using DAX with total quantity sold and filtered by gender to reveal purchase and return quantities.

Explore calculated column behavior on a table; it computes row by row and creates a physical column, which is not for aggregation—use a measure for aggregation and segmentation and filters.

Pull prices into the fact table with related, compute line revenue from quantity times price, and highlight why calculated columns fail for aggregation; use measures to preserve filter context.

Learn to fix percentage errors in Power BI by using a measure (sum of line margin over sum of line revenue), avoiding calculated columns for aggregation, and format as percentage.

Use a calculated column to label orders as single or multiple by order quantity, enabling filters and slicers, while noting that measures can handle aggregations where appropriate to optimize performance.

Learn to create a calculated column that computes customer age from birthday using date diff and today in Power BI, then bucket ages with if and switch for customer segmentation.

Discover how DAX measures use DAG-based calculations with filter context for proper aggregation, not row-by-row processing, and why they’re suited for aggregation rather than segmentation, unlike calculated columns.

Create a disconnected measures table in Power BI Desktop to collect all measures, move them from the fact table, and learn that calculated columns cannot be moved.

Master DAX measures for aggregations in Power BI using SUMX and RELATED to pull prices, then compute total revenue, total cost, and profit margin.

Learn to build DAX measures in Power BI to calculate total returns, return values, and transactions returned, then derive return and refund rates using related tables and total quantity sold.

Explore how to use Power BI DAX count functions—count, count rows, count blanks, counta, countx, and distinct count—to measure transactions, products, and returns in dashboards.

Explore the calculate function in Power BI and how it modifies the filter context by adding, removing, or changing filters, embedding explicit measures and using all, filter, and sum X.

Master count functions in Power BI with DAX, using count rows and distinct count across tables to track purchased and sold over time with proper filter context.

Explore building Power BI KPI measures with DAX, including accessories revenue, quantity thresholds, and monthly revenue using the calculate function and a dynamic date table.

Learn to fix a Power BI measure for Canada transactions using the calculate function with a country filter, avoiding unnecessary relationships, and preserving filter context across related tables.

Discover why the Microsoft Learn site is the must-know resource to learn DAX functions, including cube filter, calculate function, and filter context.

Learn to use the calculate, all, and all selected functions in Power BI to modify filter context, compute grand totals, and build a percent-of-grand-total measure for product subcategories.

Learn how to use the all function across multiple tables to remove filters and create accurate, flexible measures for category, subcategory, and territory dashboards.

Master the all selected function with calculate to yield correct percentages in Power BI, using all selected around the fact table to reflect grand total and slicer filters like country.

Learn how to add and manage comments in Power BI to document code, suspend or freeze sections, and use single-line and multi-line comments with keyboard shortcuts.

Explore DAX table functions such as all, filter, and values to retrieve unique values, filter data, and convert text to numbers, while distinguishing virtual from physical tables.

Master the and function and ampersand to set multiple conditions in Power BI. Use all, filter, and calculate to build revenue measures like Australia and Pacific by continent and country.

Learn to build advanced DAX filters using the calculate function across multiple tables, filtering by category name, continent, and dynamic calendar constraints like month and weekend.

Enable Copilot in Power BI Desktop and learn to generate DAX measures with natural language; compare outputs with hand-written DAX using calculate and in operator.

Learn how to convert row context into filter context in DAX using calculate or existing measures like quantity sold, to compute customer-level purchases from the fact table.

Learn how to convert row context to filter context in Power BI using the calculate function and context transition, enabling accurate per customer totals and dashboard segmentation with DAX measures.

Use context transition to segment customers by revenue in Power BI, creating a calculated column with nested ifs to label good, average, and bad customers.

Explore creating a drill-through dashboard in Power BI to know your customers by segment, using a customer table, total revenue, and numbers of customers to reveal segment insights.

Discover how to use DAX variables with var, mastering syntax and naming to distinguish variables from functions. Apply return statements to compute results in Power BI dashboards.

Discover how to name and use DAX variables, avoid reserved words with underscores, and use return to display max and mean calculations on Power BI dashboards.

Create a DAX measure using VAR and calculate to compute the percentage of each product color against the grand total, using all to remove filters and divide by total revenue.

Use Power BI Desktop to add a customer full name and total revenue in a table, then fix missing names by editing Power Query steps and adding a prefix.

Create a disconnected table with rank type and rank value, populate top two, three, five, ten, twenty, and thirty, and filter with a slicer using a selected value measure.

Build a top N customer ranking measure in Power BI using DAX, including values, variables, rankx, all, and calculate to filter and display top customers.

Build a top-N report in Power BI with a what-if parameter and parameter table to automate selection and rank customers by revenue.