Power BI for Data Analysis

Transform data in pocket editor by removing the raw id and converting post code to text, then load into Power BI to build visuals of sales, quantity, discount, and profits.

Learn how to format Power BI visuals, adjust axis titles, fonts, and units, reposition legends, and add analysis features like average lines for monthly sales charts.

Create a top five cities by sales bar chart in Power BI, format the x and y axes to thousands, and apply top five filtering with the filters pane.

Explore Power BI data analysis by creating a donut chart to compare ship modes, revealing that standard shipping dominates sales and that same-day shipping increases costs.

Explore how to create a bottom five series by sales using a clustered bar chart in Power BI, filter by city, and adjust sorting for clear insights.

Learn to filter and slice Power BI reports using the filters pane and slicers, enabling segment-level analysis for consumer, corporate, and home office data.

Add and arrange date and segment slicers on a Power BI dashboard, tune their size and interactions, and address a month-year visual distortion by excluding a chart from slicer actions.

Explore the quiz solution by formatting a Power BI visual: set the x axis display units to thousands and ensure consistent units across the sales by month and year report.

List headers and identify events to begin a data model, group events to reveal relationships, assign a key for granularity, break data into dimension and fact tables with primary keys.

Build a data model to reduce repetition and optimize data handling by identifying keys and relationships across customers, geography, and products.

Break down the data into linked tables—customer, geography, product, and orders—establishing primary and foreign keys to minimize duplicates and build an efficient data model for analysis.

Create four data model tables—orders, customer, product, geography—in the Parkway editor, then select key fields from orders: sales quantity, discount, profit, order date, ship date, and ship mode.

Build a Power BI data model by linking orders to customer, geography, and product tables with primary and foreign keys, while removing duplicates to maintain unique lists and fix links.

Create robust relationships in Power BI by merging columns to form geographic and product keys, then link geography, customer, and products tables after removing duplicates.

Build a calendar table in Power BI with DAX calendar auto to generate dates from your data model. Learn to use optional fiscal year and month arguments.

Add a quarter column to the calendar table in Power BI using DAX, appending 'Q' or with a backslash method, and verify relationships with the data model.

Investigate your data model in Power BI report view, create a month number column, and sort months by this column to display January through December with consistent sales totals.

Create a dates table, integrate calendar dates into the data model in Power BI, and build a revenue measure by summing sales from orders, then visualize by month.

Develop a month on month variance measure in Power BI by subtracting the previous month’s revenue, then compute percent month on month variance with divide and format as a percentage.

Create a line chart to visualize revenue on a dashboard, add cards for current and previous month revenue, and set year and month slicers with dropdowns, refining interactions.

Build and format Power BI visuals by configuring line charts and a waterfall chart, setting revenue by date, and displaying values in thousands for monthly forecasting.

Build a matrix table with month rows and year columns to display revenue, block slicer interactions, and use data bars in cells to show revenue strength.

Explore Power BI for data analysis by adjusting visuals, blocking slicer interactions, and analyzing revenue by month and year, including waterfall charts, variance, and future forecasting.

Forecast your business revenue with Power BI by setting units to years, choosing forecast length, and applying a 95% confidence interval; then build a clear, titled report.