Power BI Pro: Mastering Projects for Data-Driven Excellence

Explore the Olympics historical data spanning 120 years in a Power BI project, analyzing trends by country, state, and athletes using diverse visualizations to build a reference Power BI report.

Clean and unify the Olympics dataset in Power BI by importing Excel data, fixing headers, removing unused columns, and merging with the country definitions to produce the final Olympics dataset.

Explore Power BI visuals by building a gender-based pie chart and a top ten country medals matrix, using filters, color schemes, and focus mode for clean insights.

Power BI Pro: Mastering projects for data-driven excellence teaches advanced Olympics dataset visualizations, including stacked column charts and tree maps, with Power Query Editor tips, filters, and medal insights.

Explore how to create visualizations in Power BI using the Olympics dataset, applying age and year parameters, ribbon charts, line charts, and card visuals to compare medals, participants, and countries.

Finalize a Power BI report by harmonizing visualizations and data cards (medals earned, countries participated, sports played) on an Olympics dataset analysis, with background wallpaper and transparency adjustments.

Analyze the email marketing dataset to reveal target age, category, and residence location using a Power BI report. Consider gender, status, enrollment time, and location to guide marketing decisions.

clean and standardize a Power BI dataset by transforming data in the Power Query Editor, removing unused columns, fixing nulls, and splitting enrolled on into date and time.

Create visualizations in Power BI Pro from a cleaned email marketing dataset, exploring gender, activity, marital status, living status, and state with bar, donut, and pie charts.

Explore how to clean an email marketing dataset and build targeted power bi visuals, using top-five state and city filters, labeled charts, and interactive cards for active users.

Create a final Power BI report by consolidating visualizations, applying data transformations with Power Query Editor, and adding shapes and text to highlight the email marketing dataset insights.

Introduces a Power BI report analyzing global terrorism data, showing bombing and explosives as deadliest attack methods, private citizens as most targeted, and a post-2000 rise with a recent downtrend.

Import a csv into Power BI, transform the data to remove inconsistencies, keep only nine columns, rename headers, and prepare the final dataset for visualizations.

Explore how to create visualizations and build Power BI reports by analyzing a global terrorism dataset, filtering success rates, and comparing top three attack types with donut charts.

Explore building map visualizations in Power BI with normal and filled maps, using country locations, size by success rate, and slicers to filter by country, region, and year.

Create and customize slicers, use year-range filters, and build area charts and cards to analyze terrorism data; apply top filters and add background images for final reporting.

Explore the unemployed citizens data analysis by year, gender, and age categories to identify vulnerable groups. Build a Power BI report like the example, examining trends from 2006 to 2014.

Learn how to clean and manipulate unemployment dataset in Power BI by importing from Excel, transforming data in Power Query Editor, and building a month-year column from month and year.

Create visualizations from the unemployment data set, using stacked column charts by age and gender and a pie chart to reveal trends and build a Power BI report.

Create pie charts by age and line charts with trend lines in Power BI to predict unemployment; use cards and filters for top age and gender insights.

Learn to finalize a Power BI unemployment project by configuring cards and filters to reveal the year of max and min unemployment, and tailor visuals and formatting.

Discover how to analyze a bank customer dataset in Power BI to identify target demographics for signups using age, gender, job class, and region.

Import a csv dataset into Power BI, clean the data by removing the customer ID column, merge name and surname, and create an age group column in Power Query Editor.

Create and refine Power BI visualizations to analyze customer balance and counts by age group, gender, region, and job classification using line, stacked column, and donut charts.

Format and refine Power BI visuals by adjusting data colors, legend positions, and titles across donut charts and a line chart for bank customer analysis.

Build a Power BI report analyzing sales and inventory for a fruits dataset, featuring top customers, price and discount visuals, age spend insights, and best versus least selling products.

Import data from Excel and clean it in the Power Query editor to merge customer, product, and sales into a unified dataset, then load it for Power BI visualizations.

Explore constructing diverse Power BI visuals for a fruit store, including funnel, scatter, and line charts, with category colors, top five filters, and data labels to reveal sales patterns.

Learn to create data cards and donut charts, customize titles and colors, and apply top-three by sales amount and bottom-three by quantity filters for the fruit dataset.

Analyze a 2013–2019 cricket world cup dataset in Power BI, exploring an interactive report with dropdown filters for batsmen and bowlers, and charts of runs, wickets, and margins.

Power BI guides you through batsman data from cricket world cup dataset, importing csv files and cleaning data, then creating a batsman slicer and cards for runs, balls, and sixes.

Build a Power BI report for cricket world cup data by creating dynamic cards for top batsman and bowler statistics, and clean and transform data with Power Query.

Explore Power BI Pro to analyze Cricket World Cup match results using dropdowns, donut charts, and matrices, with filters to remove hyphens and highlight margins for insights.

Create two complex visualisations for cricket data using Power BI Pro. Apply top five filters, display maximum scores and wickets, and customize labels and colors for a polished report.