Analyzing Covid-19 data with Power BI in 2021

Load Covid-19 data into a SQL Server database by importing CSV files, configuring encoding, and setting the correct destination. Verify the data to enable seamless analysis in Power BI.

Load covid-19 data in Power BI desktop using import, preview datasets from a server and the Irish government, then establish relationships and prepare for transformations in later videos.

Learn to build a date table in Power BI with calendar fields such as year, month, quarter, and week. Create and relate columns to timestamps for accurate COVID-19 data analysis.

Mark the calendar table as a database, select the needed columns, and save it; then create a new column using concatenate to generate labels like 'quarter three' and 'quarter four'.

Learn to create a separate measures table in Power BI for initial measures, enabling stable calculations like total cases and total deaths using the data table and calendar table.

Create a bar chart in Power BI by transforming data, converting data types, and applying visual filters and drilldown to compare continents and countries for Covid-19 data in 2021.

Learn to create an animated line chart in Power BI to visualize monthly covid-19 cases, with month sorting and a driving calculated measure.

Explore using a filled map visual in Power BI to map covid-19 cases by continent, customize colors by case counts, and read tooltips for location-specific totals.

Explore how to create and refine card visuals in Power BI to display total Covid-19 cases and deaths, and apply page-level and visual filters to clean blanks.

Explore the Power BI table visual by building a country table with location and total cases, then apply conditional formatting using green, yellow, and red flags based on total cases.

Create and customize a Power BI map visual to display total covid-19 cases by country, color-coded by case counts, with a world filter and map options.

Create a world map visualization of covid-19 total cases using location-based bubbles, applying diverging colors and a base level world filter, and explore map controls for zoom and styling.

Transform imported data for a shape map in Power BI and map Ireland. Create measures for total cases and population, adjust color saturation by Ireland's data, and fix table relationships.

Explore a sparkline custom visual in Power BI to display Ireland COVID-19 cases. Apply formatting like value level, area under the curve, target values, and red color for higher cases.

Build a Power BI table visual using Ireland counties data, displaying cases and population. Apply conditional formatting with data bars and icons to highlight county-level variations and formatting options.

Learn to build a waterfall chart in Power BI to analyze 2021 covid-19 data, using a hierarchical drill-down (year, quarter, month) and country filters with unit adjustments.

Explore Power BI cards to present covid-19 metrics by creating two card visuals for Ireland cases and overall population, format values, and combine map, table, sparklines, and a waterfall chart.

Explore drill-through in Power BI: filter by continents, drill into countries such as Ireland, and navigate to country-specific reports with diverging color visuals for cases.

Learn to compute month-to-date totals in Power BI, create calculated measures, and apply top ten filtering via location filters to display the top ten countries by total covid cases.

Explore how to create and customize a treemap visual in Power BI to compare COVID-19 cases by country, apply top-N filters, enable data labels, and adjust color palettes.

See how the key influencer visual in Power BI analyzes factors by location, enable counts, compare relative and absolute values, and use collapsing, drilling, and formatting options to explore insights.

Learn to use a ribbon chart in Power BI to compare Covid-19 deaths across countries and months, selecting top locations, adjusting colors and layout, and exploring slicers.

Learn how slicers differ from filters and how to use visible slicers to filter Power BI reports by continents and locations, compare values, and enhance user experience.

Learn to format and apply a custom theme in Power BI for covid-19 data, adding logos and images, and arranging visuals to prepare a polished quarterly BARBET report.

Master formatting bookmarks in Power BI to capture a snapshot of current slicer selections, create named bookmarks, and trigger page navigation with actions for streamlined reporting.

Demonstrates configuring actions on images to navigate across pages, using a home button to return to the home page, and testing navigation with control-clicks and bookmarks.

Explore formatting techniques in Power BI by using slicers and bookmarks to control views, manage sections, and enrich tooltips for COVID-19 data analysis.

Format visual headers in Power BI by adjusting the dark background and visibility, turning on the correct options, and preparing the final report.

Final report showcases Power BI visuals, including maps, tables, and a waterfall chart, organized by country and highlighting single-country maps and changes from the previous version, analyzing covid-19 data.

Refine the final Covid-19 data report in Power BI by applying formatting, axis tweaks, and page content changes to enhance clarity and user-friendliness.

Explore how the performance analyzer measures the time taken by each report component to help optimize visuals and export data for further analysis.

Publish your report to the Power BI service, sign in, select your workspace, and verify bookmarks, slicers, maps, and charts. Learn exporting options like PDF, PowerPoint, and Excel.

Learn how to set up Python for data visualization, compare Anaconda and Python installations, configure the environment, and install essential libraries for visualizing data.

Learn to create a Python heat map in Power BI to visualize Covid-19 data, exploring correlations between total cases, new cases, hospital patients, and ICU patients.

Learn to create a Python-powered bar chart in Power BI to visualize Covid-19 data by country, using a top 15 locations filter and flexible color palettes.

Discover Python visualization with violin plots to compare distributions across continents and categorical levels, highlighting density, quartiles, and outliers using seaborn and matplotlib.

Identify common challenges of Python visualizations in Power BI, including lack of interactive output, data size limits, and backend timeouts, and consult the official documentation for details.

Provide a concise thank-you note while reinforcing how to analyze covid-19 data with Power BI in 2021.