Power BI MasterClass: Learn Data Analytics with Power BI

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.

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.

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.

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.

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.

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.

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 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.

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.

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 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.

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.

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.