Power BI MasterClass: Learn Data Analytics with Power BI

Install Power BI Desktop on Windows to get data, create relationships, and build reports; learn desktop is free and differs from the online service, with optional sign-in.

Install Microsoft SQL Server and SQL Server Management Studio using the express edition for a quick setup, and follow the installation prompts including admin credentials and required restart.

Learn to install the SQL Server standalone, choose features like machine learning and localdb, and troubleshoot installation issues, including Visual Studio prerequisites and Windows authentication.

Install and configure SQL Server Management Studio, connect with Windows authentication, and restore the Adventure Works 2014 database and data warehouse.

Connect to CSV and text files in Power BI by importing employee records, then transform and clean data—remove empty values and unnecessary columns—to prepare for analysis.

Learn how to connect Power BI to Excel files, load multiple spreadsheets, preview and adjust data types, and begin building reports with clean, unified data.

Connect to a webpage in Power BI, scrape table data from Wikipedia, validate open data sources, transform and clean columns, and build clean datasets for analysis.

Connect to OData to fetch data from websites, load product details from XML, and transform and expand related tables to bring in product, order details, unit price, and employee data.

Connect to a SQL server in Power BI, choosing import or direct query, authenticate, and load and select relevant tables, dimensions, and fact tables for analysis.

Learn how to connect Power BI to a Facebook page to pull posts, likes, and engagement data, enabling analysis for digital marketing decisions.

Explains three methods to change data types in Power BI, shows entering data via enter data, and covers copying, pasting from sources, and renaming tables for better data management.

Learn to manipulate Power BI data with edit queries: duplicate tables and columns, rename or remove columns and rows, reorder fields, add sample columns, and split columns by delimiter.

Merge columns to form a single employee name by concatenating prefix, first name, middle initial, and last name with spaces; demonstrated in the Power BI data transformation steps.

Discover date formatting in Power BI by transforming date fields, extracting year and month from the date of joining, and renaming columns to support hiring analytics.

Connect to a database, import tables, and expand related tables to combine products with their subcategories and categories, building cross-table relationships in Power BI.

Explore grouping using bins to segment data into buckets, define custom bin sizes, and visualize employee salary data in Power BI with pie charts and other visuals.

Create and analyze grouped data with bins in Power BI, setting age and salary bins, and compare counts or averages using visual charts.

Learn to group data in Power BI using lists, create item-type groups such as food items, self-care, household, and build charts and reports to analyze costs, profits, and units sold.

Connect to a school server, import product and internet sales tables, link them by product key to analyze color sales in Power BI, and group colors into an 'other' category.

Create and connect a product hierarchy in Power BI by combining product, product category, and subcategory tables, then design drill up and down paths to enhance analytics.

Learn to create and explore a product hierarchy in Power BI, drill down to subcategories and individual products, and drill up to see category-level totals.

Learn to create query groups in Power BI by organizing tables into dimensions and facts, moving items between groups, naming groups, and managing group structure for easier data access.

Master pivot and unpivot techniques in Power BI by transforming sales records with edit queries, focusing on country, item type, and units sold to reveal insights.

Explore how to use left outer join in Power BI with Power Query to combine tables, compare inner, left, and right joins, and see practical join examples.

Explore the right outer join by joining department's manager with the employees table, compare left join and inner join behavior, and see how unmatched records appear in the results.

Explore inner join and full join concepts in Power BI by merging department and employee data. Observe how joins affect which rows appear and how gaps are handled.

Master left anti and right anti joins in Power BI, using minus logic to return records only from the left or right table, illustrated with employees and departments.

discover how to perform append queries in Power BI, combining two or more tables with matching columns and data types, handling duplicates, and understanding union versus union all.

Explore area charts in Power BI by turning product category and sales data into visual area charts, learning axes, measures, dimensions, and formatting options.

Explore area charts in Power BI by sorting data by product name or region and comparing sales to production costs to reveal profit margins.

Learn to build and customize power bi bar and column charts, compare sales and production costs with stacked and clustered layouts, and apply color, labels, and city sorting.

Explore Power BI line and stacked charts, including 100 percent stacked and column charts, to analyze sales by geography and occupation with filters and data labels.

Learn to visualize flows with waterfall and ribbon charts in Power BI, using color to show value across country regions and applying category and occupation breakdowns.

Learn to build and customize tree map and scatter chart visuals in Power BI, configuring details, legend, axes, bubble size, and geography like country region and occupation.

Explore pie and donut charts in Power BI, using legend, details, and values to visualize sales by country and product category and reveal market share.

Learn how to create funnels and matrices in Power BI, configure group and values attributes, format colors, and interpret two‑dimensional metrics across rows and columns.

Explore Power BI cards and maps, comparing the single value card with the multiracial card to analyze sales, tax, and profits by country.

Learn to build and interpret clustered column charts and line charts in Power BI, using shared axis, column series, and line values with examples across product categories, geography, and demographics.

Demonstrates using slicers in Power BI MasterClass to filter multiple visuals by country, region, and occupation, enabling dynamic, dashboard-level data analytics for executives.

Learn to use Power BI slicers to select single or multiple values, enable show all, and adjust format, text size, and headers, while exploring visual and page filters.

Discover visual level filters in power BI: use basic filters for single or multiple selections, advanced filters with wild cards and contains, and top end filters for top N values.

Learn to apply filters on measures within visuals, including advanced, visual, and page level filtering. See how to filter sales amount and quantity by geography using maps, charts, and slicers.

Learn to use visual, page, and report level filters in Power BI, and master advanced rules such as contains, does not contain, and is blank with proper precedence.

Explains how to use drill through filters with a geography hierarchy (country, state, city) to drill up and down, and apply page and report level filters across visuals.

Explore gauge charts in Power BI to track current values against minimum, maximum, and target levels and visualize progress toward goals. Analyze KPI trends and key influencers to understand performance.

Learn how the key influencers visual in Power BI uses a fresh dataset to reveal factors like country and team that influence customer ratings.

Explore data modelling concepts in Power BI by comparing star and snowflake schemas, defining facts, dimensions, and measures, and designing robust relationships.

Explore cardinality in power bi by distinguishing one-to-one, one-to-many, and many-to-one relationships, and learn how active and inactive relationships affect filtering in the model.

Learn to build your own data relationships from scratch in Power BI by creating customer, product, and sales tables, entering data, and managing relationships.

Discover how Power BI detects and edits table relationships across sales, customer, and product tables. Convert one-to-one to one-to-many and explore bidirectional versus active relationships in Power BI.

Learn how bidirectional filtering works in Power BI by enabling cross-filtering between fact and dimension tables, letting geography, product, and time attributes affect related data from both sides.

Create calculated columns in Power BI using DAX functions to compute profits from sales data and build a measure totaling profits across internet and factory sales channels.

Create a calculated table from an existing table and add a conditional column in Power BI, using distinct countries and sales ratings like good, great, excellent, and amazing.

Create a calendar table with the DAX calendar function, generating dates between start and end dates; explore today and now, end-of-month, and weekday calculations for Power BI analytics.

This lecture demonstrates creating measures with DAX aggregate functions such as sum, average, divide, min, max, and sumx on internet sales data, showing single-column calculations and table-based expressions.

Explore DAX logical functions in Power BI, including if and switch statements, nested conditions, and end-of-month and date difference calculations, with practical column and measure examples.

Explore DAX text functions in Power BI, including concatenate for words or columns and handling spaces, and replace and substitute for targeted text edits with examples.

Explore DAX text functions 2, including find and replace, find, search, uppercase, left, right, trim, and substitute. Learn differences in case sensitivity, starting positions, wildcards, and building new columns.

Master DAX filter functions in Power BI by using calculate and filter, exploring related and all, to compute year-specific internet sales across geography such as country and province.

Build and relate a calendar table in Power BI, then apply DAX time intelligence functions to compute year-to-date, quarter-to-date, dates between, and opening/closing balances from sales records.

Connect and shape COVID-19 data in Power BI by pulling confirmed, deaths, and recovered cases from web sources. Transform and merge these into a single COVID-19 dataset for visualization.

clean COVID-19 data in Power BI by merging tables, refreshing removed columns, and build DAX measures for total confirmed, deaths, recovered, and new cases using max date and previous day.

Create a Power BI dashboard for covid-19 data showing total confirmed, deaths, and recovered, with a country map, top 10 countries, daily new cases, and velocity charts.