Mastering Data Analysis with Power BI

Learn to import data from Excel into Power BI desktop, load the customers and orders worksheets, and start analyzing and visualizing key metrics like revenue and expenses.

Connect Power BI to CSV files by choosing Get data, selecting Text/CSV, and loading the csv_orders file to import and analyze data, noting CSV files handle millions of rows.

Connect Power BI to a MySQL database using MySQL Workbench to access the deliverycompany database with customers and orders tables, then load or transform data in the Power Query Editor.

Learn basic data preparation in Power BI using the Power Query Editor, including renaming tables and columns, changing data types, reordering and removing columns, and creating a duplicate column.

Extract date parts in Power BI using Power Query Editor, creating columns for year, month, quarter, and day of week from order dates.

Split the customer id column into two new columns to separate product type code from the actual id, enabling future table relationships in Power BI.

Learn to create conditional columns in Power BI, grouping customer ages into ranges and mapping gender from initials to full labels to analyze client segments.

Create a calculated column in Power BI to compute net profit by subtracting operational expenses from revenue, using a custom column and DAX formulas.

Calculate descriptive statistics in Power BI's query editor by selecting a column and using transform statistics to compute the sum of net profit and the median cost of products.

Apply transformations in Power BI: add date column, split customer ID, define age groups and gender names, calculate net profit with DAX, then load two tables and start analysis.

Master data analysis in Power BI by creating and managing relationships between customers and orders, using one-to-many connections via customer ID, and performing simple data transformations.

Create bar charts in Power BI using state and net profit data. Add category legends, format titles and data labels, and explore stacked bar, stacked column, and clustered bar options.

Create a 100 percent stacked column chart in Power BI using states on the axis, net profit as values, and year of order as the legend.

Create pie and donut charts in Power BI using orders data with product category as the legend and net profit as values, then apply formatting, colors, labels, and legend placement.

Create a combo chart in Power BI by merging a column and a line, using orders data to count orders and show net profit with title and label formatting.

Create a treemap in Power BI to show net profit by product subcategories, using net profit as values and subcategory as the group, highlighting top contributors like TV and oven.

Create map charts in Power BI by visualizing net profit by states, drag measures to the size field, customize colors and titles, and explore filled map options for dashboards.

Learn to create a waterfall chart in Power BI to visualize steps from initial amount to final amount, using net profit across four years, with formatting tips for audience-friendly insights.

Learn to create a gauge chart in Power BI to compare actual net profit with a planned target, filter the chart by year (e.g., 2016), and customize colors and titles.

Learn how to create and format cards and multi-row cards in Power BI to display key metrics like revenue, operational expenses, net profit, and number of orders on your dashboard.

Create table and matrix visuals in Power BI using measures from two related datasets to analyze orders by education, gender, age, and marital status.

Learn to use the Power BI slicer to make dashboards interactive, filtering charts, tables, and cards by year with single or multi-select options, including gauge charts.

Enrich your Power BI dashboard by adding an image logo, shapes, and a textbox with the key business metrics, then adjust position and size for presentation readiness.

Demonstrate visual relationship in Power BI by using a slicer to filter two charts and show their connection with a translucent rectangle.

Duplicate Power BI pages with a right-click to quickly create visualizations by renaming, deleting, or hiding pages, then customize charts by changing net profit, state, and product category.

Learn to view the underlying data of a Power BI chart and export it as a CSV file from the dashboard, using the show data option and export data feature.

Enter data manually in Power BI to create a new dataset with score of review and name of review, then relate it to orders to analyze orders by review score.

Refresh Power BI dashboards after updating the Excel data to reflect new orders, profits, and Texas in charts and maps, enabling easy daily, weekly, and monthly reports.

Explore how Excel add-ins such as Power Query, Power Pivot, Power View, and Power Map extend data analysis from millions of rows to dashboards, aligned with Power BI principles.

Publish reports to the Power BI service to visualize and analyze data quickly in the cloud, share insights with colleagues, and explore charts and machine learning insights.

Wrap up the Power BI course by reviewing installation, data import from Excel, SQL Server, and CSV, and building interactive reports with charts, map chart, and slicers for two dashboards.

Take the next steps in mastering data analysis with Power BI by applying core techniques to analyze, visualize, and interpret data for informed decision making.