Power BI Bootcamp: Build Real World Power BI Projects

Learn to build a real-world COVID-19 data analysis report in Power BI, using data and visuals like cards and scatter plots to track cases, deaths, and median age across countries.

Create visualizations in Power BI from a cleaned COVID-19 data set. Build area and pie charts, filter to top ten countries and by continent, and format titles and labels.

Learn to craft complex Power BI visualizations with storytelling, including area charts by continent and country, median age analyses, and interactive cards linked to other visuals.

Learn to create multiple instances of the same covid 19 dataset in Power BI, transform data with Power Query, and build focused visualizations that are combined into a single report.

Create a Covid-19 dataset analysis report by assembling total and new case visuals, pie charts, and median age data into a Power BI report, then export to PDF.

Analyze the Olympics dataset across 120 years, examining countries, states, and athletes, and build a Power BI report using tree maps, line charts, ribbon charts, pie charts, tables, and matrices.

Import the Olympics dataset into Power BI, clean and transform the athlete events data, merge country definitions, replace codes with full values, and produce the Olympics final dataset for reporting.

Load and clean the Olympics final dataset, then build simple visualizations in Power BI, including a pie chart and a matrix for gender and country medal distribution.

Demonstrates advanced Power BI visualizations on the Olympics dataset, including top players by medals, a sports distribution tree map, and season-based stacked bar charts.

Create Power BI visualizations from all dataset parameters using the Olympics data, building ribbon and line charts, filtering ages 10-45, and designing cards for medals, countries, and sports.

Learn to assemble a polished power bi report by aligning visuals, adjusting color schemes and transparency, and placing data cards on a themed Olympics background for the dataset analysis.

In this Power BI bootcamp module, analyze a 10,000-record email marketing dataset to visualize target age, category, and residence, and build a report identifying Telangana as a key market.

Clean and standardize the email marketing dataset in Power Query by removing unnecessary columns, handling nulls, formatting text, renaming fields, and splitting date and time, then load into Power BI.

Learn to build simple visualizations in Power BI from an email marketing dataset, using gender, activity, marital, and living status with bar, pie, and donut charts.

Build real-world Power BI projects by cleaning a marketing dataset, creating top five states and top five cities visuals, and refining labels, colors, and titles for signup trends.

Deliver the final Power BI report by organizing visuals, applying data transformations in power query editor, replacing values, and adding shapes and text to describe the dataset.

Explore a global terrorism dataset and build a Power BI report analyzing attack types, targets, weapons, and regional patterns. Track trends over time, including post-2000 growth and recent declines.

Learn to import a csv terrorism dataset into Power BI, clean and trim columns with Power Query, rename headers, and create a final, ready-to-visualize dataset.

Learn to create visualizations and Power BI reports from a global terrorism dataset, mastering basic report creation, focusing on top three attack types, success rate, and focus mode filtering.

Explore building map visualizations in Power BI, using country and region data, and apply slicers and search to filter by country; enhance with bar and line charts.

Create a final report for the global terrorism dataset by adding advanced Power BI visuals, slicers, area charts, cards, and weapon and target data visuals in a guided slideshow.

Explore a real-world Power BI project analyzing unemployed citizens data to identify vulnerable groups by year, gender, and age using a prebuilt report and trend insights.

Import the unemployment dataset from Excel, clean and shape it in Power Query by splitting columns, removing irrelevant data, and creating a month-year column before loading the data.

Create and compare unemployment data using Power BI visualizations, including stacked column and pie charts, with focus mode, sorting by age, and data labels for clarity.

Create visualizations of unemployment data, including a pie chart by age and a line chart with trend lines to predict future values, plus gender comparisons and top-unemployed cards.

Explore final steps in building a Power BI unemployment dashboard, using card visuals to show max and min unemployment by year, and applying top and bottom filters for a report.

Explore the customer analysis project in the Power BI bootcamp, analyzing bank customer data to identify trends by age and gender and to target high-potential groups with a sample report.

Clean and prepare a CSV dataset in Power BI by removing the customer id, merging name and surname, and creating an age-group column in the Power Query Editor before loading.

Build Power BI visualizations from a banking dataset to analyze balance by age and gender, line charts, region distribution, and counts by age group and job classification.

Gain hands-on techniques for formatting Power BI visuals, adjusting data values and titles, configuring chart positions, and building balance by gender and age analyses for bank customer analysis.

Explore a Power BI sales and inventory analysis for a fruits dataset, presenting a from-scratch report with customer, product, and discount visuals and top sellers like asparagus.

clean and customize a power bi dataset by importing data from excel, transforming via power query, and merging customer and product tables for a final, report-ready dataset.

Explore creating and styling Power BI visuals, including funnel, scatter, line, donut, and clustered bar charts, with filters, data labels, and color adjustments to reveal sales and customer insights.

Design Power BI reports by adding data cards and doughnut charts, customize titles, and highlight the top three products by sales amount and by quantity, plus bottom performers.

Explore a Power BI interactive report for the 2019 Cricket World Cup data analysis, built from 12,000 matches (2013–2019), and featuring top batsmen and bowlers, margin insights, and country–opposition comparisons.

Import and clean the cricket world cup batsman dataset in Power BI, transform missing values, create a batsman slicer, and build visuals for runs, balls faced, fours, and sixes.

Build a real world Power BI project by creating dynamic cards for top batsman and bowler metrics and transforming the cricket world cup dataset with Power Query for clean visuals.

Build real-world dashboards by analyzing cricket world cup results, using dropdown filters for country and opposition, and creating pie or donut charts, matrices, and margins insights.

Master two complex Power BI visuals for the cricket world cup dataset, highlighting top five batsmen by maximum score and top five bowlers by wickets, with final touches.