Power BI Course: Build Job-Ready BI & Dashboard Skills

Create a pie chart to display segment sales and profit, then explore a donut chart and funnel chart with clear labels, colors, and titles.

Explore the decomposition tree and KPI charts to analyze sales by year, month, and product, expand hierarchy with plus icons, and customize visuals with trend axes and KPI formatting.

Explore creating and formatting area charts and 100% stacked area charts in Power BI, including adding data labels, customizing fonts and headers, and applying formats across visuals.

Explore creating ribbon charts to compare monthly segment sales with customizable colors, borders, and bold axis labels, and learn to use gauge charts to visualize sales toward targets.

Learn to create Power BI cards to display KPI values such as sum of sales, profit, and units sold, using slicers to filter by product and format cards.

Explore creating table and matrix visuals in Power BI, comparing row-wise table aggregations with multiple measures to pivot table–style matrices by product and segment, plus formatting options.

Explore how to build a scatter plot of sales vs profit, show each transaction, and distinguish products by color or shape, with markers, legend, and trend line options.

Create and customize a tree map to visualize sales by year and segment, using category and details fields to color and size rectangles.

Create a Power BI waterfall chart to display month-by-month profit in incremental order, from January onward, and note that more than five or six levels enhance attractiveness.

Create a simple area chart and a stacked area chart in Power BI, using month, sales, and segments; colors show segments while the line shows months for cross-segment comparisons.

Load data from the web into Power BI by selecting the web option, choosing the desired table, and creating visuals with basic charts.

Learn to build a Power BI sales dashboard by loading the sample financials data and creating bar, line, pie, and donut visuals with a consistent orange and green theme.

Build a sales and profit dashboard in Power BI using a scatter plot to show sales versus profit, with color, shape, and country legend, and a play axis for sums.

Showcase how to compare sales and profit across products and months using clustered bar and stacked area charts, with theme tweaks and legend placement.

Build a Power BI treemap dashboard that compares sales and profit by segment, with color boundaries, formatting, and data labels in millions, plus a parameter to switch fields.

Build a parameter-driven Power BI scatter plot by creating categorical and numeric parameters, using slicers to switch segment, product, country, revealing how sales and cost of goods sold interact.

Explore how to use categorical and numerical parameters with synced slicers to drive a pie chart and bar chart, switching measures and fields on a single visual.

Explore map charts in power bi to visualize sales by country and region, using bubbles, filled maps, and color legends, with segment-based filters for country, month, and product.

Explore how artificial intelligence enhances Power BI visuals with AI analysis, Q&A chatbot, and Copilot-driven chart creation. Create narratives, forecast future trends, and detect anomalies to build AI-powered dashboards.

Learn to build stacked column charts in Power BI, apply parameters and slicers, and analyze sales by region, ship mode, and product category for cross-categorical insights.

Construct and interpret clustered column charts with and without parameters to compare sales, profit, quantity, and other measures across regions, categories, and dimensions.

Learn to build and analyze a 100% stacked column chart in Power BI, using product, region, and customer segment to reveal percentage contributions with data labels and slicers.

Learn how Power BI line charts visualize time-based data, using monthly sales and profits, regional comparisons, and multi-line insights to study trends and determine when line charts fit best.

Learn to use the line chart in Power BI to reveal trends in yearly and monthly sales, drill down via date hierarchies, and use slicers for category and region.

Apply conditional formatting in Power BI to highlight top and bottom sales with background and font color, and use icons in tables and matrices to show period-to-period progress.

Master the Power Query Editor to clean data, fix headers, split columns, and merge or append queries while loading from Excel and renaming fields.

Split columns in Power Query to separate model, color, and memory from product names using comma and bracket delimiters, trim spaces, and rename columns for clean data.

Learn to clean data with choose columns and duplicates, then group by in Power Query to summarize populations by city and state and sales, profit, units by country and product.

Explore arithmetic operations in Power Query to combine columns, calculate totals, profits, and percentages, and derive MRP and discounts from sales, quantity, and discount data.

Explore date functions in Power BI, calculating days between order date and ship date with DAX, and extracting year, month, quarter, week, and start/end dates in Power Query.

Learn to append multiple data sets with the same layout in Power Query, merging 2021–2023 into one dataset. Explore initial data cleaning and introduce transpose, pivot, and unpivot concepts.

Learn to group data by department and region with multiple aggregates such as sum and average in Power Query, and master pivoting and unpivoting for Power BI dashboards.

Apply Power Query cleaning techniques in Power BI to normalize messy data through unpivoting, transposing, and fill down, using first-row headers for tabular clarity.

Open the Power Query Editor to combine and clean data, then add and rename columns such as MRP, discount in dollars, cost, month, and weekday for dashboard visuals.

Merge datasets in power query using left outer join to combine 2011 and 2013 population data by state, expanding results while keeping originals intact with merge queries as new.

Create a days to ship metric by subtracting order date from ship date, rename it days to ship, and analyze shipping times by region, state, or category with a slicer.

Load data from diverse sources, join into a master dataset, and model star and snowflake schemas in Power BI to create a dashboard.

Explore how Power BI handles joins: left outer, right outer, full outer, inner, left anti-join, and right anti-join; and examine one-to-one, one-to-many, many-to-one, and many-to-many relationships in the model view.

Learn how to merge age and tenure data using full outer join and inner join in Power BI, create a new table, expand results, and handle nulls.

Master left and right outer joins and left and right anti joins in Power BI by merging age and tenure data, handling nulls, and building a star schema.

Build a star schema in Power BI by linking Netflix titles as the fact table to cast, category, countries, and directors as dimensions, including a many-to-many relationship and manage relationships.

Build a data model in power bi by merging netflix titles, cast, directors, and countries, then create visuals like matrix, pie, and bar charts to analyze releases.

Create a unified Power BI data model from a multi-sheet bookshop dataset by loading, cleaning headers, merging data, and building visuals with interconnected relationships.

Learn to create conditional columns and custom columns in Power Query, manage parameters, apply filters, and build a trend forecast within Power BI for data from multiple sources.

Learn to create categorical and numerical parameters in Power BI, and apply them to visuals like column and line charts using slicers, legends, and DAX-based aggregates.

Learn to apply visual, page, and report filters in Power BI, using categorical and numerical criteria to refine states, sales, regions, and months across multiple visuals and pages.

Explore how Power BI filters drive interactivity by using visual, page, and report level filters; enable cross filter; and implement drill-through between index and details pages.

Explore how to customize tooltips, manage visual interactions, and drill down in hierarchical data within Power BI to build more insightful dashboards.

Create and customize Power BI visuals using tooltip to display country, product, sales, profit, units sold, and discounts, and explore segment wise details with a multi row card.

Learn to create product and date hierarchies in Power BI, enabling drill down, drill up, and expand all to explore sales by category, subcategory, product, and date.

Learn to use drill-through and bookmarks to navigate Power BI reports, add action buttons, and create reset bookmarks for detailed subcategory and region insights.

Learn to use Power BI buttons for navigation, drill through to detailed subcategory reports, and bookmarks with a reset button to restore the original view across region and segment visuals.

Master drill through across multiple pages in Power BI to analyze month-wise sales by category and subcategory with clear visuals and navigation back to the index.

Explore building a navigation page with a page navigator to switch between index, detail report, and month wise sales using chevron arrows and configurable orientation.

Create and use bookmarks and a reset button in Power BI to enable drillthrough details for subcategories and display sales by category, subcategory, year, and segment.

Understand what DAX means and how Data Analysis Expressions power calculations in Power BI for tables, calculated columns, and measures, using aggregation, date-time, filter, financial, information, logical, and mathematical functions.

Explore table, column, and measure DAX commands to build calculations in Power BI, including creating a Germany data subset, a cost column, a total-sales measure, and a quick measure.

Learn to build date tables in Power BI with DAX calendar auto, creating continuous date ranges across multiple years and aligning with financial year endings in March.

Create new data tables from existing data using DAX and the summarize function to group by year and country, then by category and subcategory with sum, average, or count distinct.

Learn to build filter tables in Power BI by summarizing data with DAX, applying year and region filters, and using slicers to produce country-wise and category/region/segment sales views.

Apply two filters on different columns, category and region (furniture and west), using calculate table and summarize to show sales totals.