Power BI Desktop –Management & IT in a Real Business Context

Power BI provides an end-to-end BI lifecycle from identifying needs to publication, and emphasizes data preparation, modeling, visualization, and secure distribution across desktop, service, and mobile.

Explore Power BI licensing, from free Power BI Desktop for solo work to Pro for sharing and collaboration, and Premium per user or capacity for scalable analytics and paginated reports.

Prepare your Power BI Desktop environment: Windows 10 or later, at least 2 gb free storage, a modern browser, stable internet; a Microsoft account and Excel familiarity help.

Download Power BI Desktop from the official Microsoft site, run the pbidesktopsetup.exe, accept the license, keep the default folder, finish, and start using Power BI Desktop.

Explore the Power BI Desktop interface, import Excel data, and build a mini-dashboard with visuals, filters, measures, and publishing options.

Explore how Power BI connectors link flat files, relational databases, and cloud services, and compare import mode, direct query, and hybrid mode, noting effects on performance, responsiveness, and data freshness.

Explore local data sources in Power BI Desktop by importing pdf and excel files, cleaning with Power Query, and merging multi-page tables to compare targets with actual sales.

Power BI Desktop's folder connection automatically consolidates weekly ERP export files into a single table; drop new files in the folder, refresh, and Power BI combines and updates the report.

Connect Power BI to a relational database using import for sales and direct query for stock, forming a hybrid composite mode that enables high performance and near real-time stock updates.

Connect to cloud sources like SharePoint online lists with Power BI Desktop, transform data in Power Query Editor, analyze opportunities by stage and quarter, then publish and enable automatic refresh.

Connect to the frankfurter.dev web API in Power BI, transform exchange rate data with Power Query, and automatically convert sales from USD to pounds using daily rates with scheduled refresh.

Connect Power BI Desktop to a SaaS like Microsoft Dynamics 365 CRM to visualize opportunities, monitor the CRM pipeline, and gain revenue insights.

Align data sources with business needs to build an effective dashboard. Connect sources smartly to anticipate performance constraints and ensure information freshness.

Improve Power BI visuals by ensuring data quality through proper preparation, cleaning, and structuring of datasets. Learn key transformations to produce clean, consistent data and become independent in data preparation.

Remove unnecessary columns to reduce data volume, improve performance, and simplify modeling in Power BI. Evaluate usefulness for analysis, relationships, measures, filters, and visualizations.

Identify and remove duplicates in dimension tables, such as product and client tables, in Power BI using Power Query to ensure reliable analysis and accurate relationships.

Identify and fix null values in primary keys and category fields with Power Query Editor, remove empties, replace nulls with labels or zeros, and refresh visuals for reliable analysis.

Explore practical text transformation in Power Query to clean data, derive category codes from product codes, build full addresses for accurate maps, anonymize names, and segment prospects by email domain.

Filter rows in Power Query to keep only invoices or credit notes from the last five years (since 2021), excluding zero quantities and documents like quotes, orders, and returns.

Learn to calculate total amount per transaction in Power Query by multiplying quantity by net unit price. Create a custom column and round to two decimals for compliant financial visuals.

Structure time in Power BI by building a calendar table and extracting week, month, and year components. Use these transformations to enable reliable weekly sales analysis and accurate period comparisons.

Create a custom Power Query to append current sales and history as a new consolidated table, then merge to enrich client and product data and optimize the model.

Structure data in Power BI using the star schema to optimize performance and readability, transforming raw exports with pivot, unpivot, and transpose into analysis-ready datasets.

Explore using chatGBT within Power Query to automate discount categorization into four categories by customer type (B2B/B2C), generating an analysis-ready M code table and insights for pricing strategy.

Harness ai-assisted correction to fix typos in customer names, extract and correct entries in Excel, and reintegrate via Power Query for a clean Power BI dataset.

Automate email verification in Power Query within Power BI Desktop by generating an M function with ChatGPT to flag invalid addresses and populate the invalid emails table for corrections.

Enrich customer data by generating salutations with ChatGPT and integrating them into Power BI via Power Query. Enable personalized reports and targeted campaigns using a complete client list.

Power BI detects relationships automatically when key columns share names and types. Enable auto detect in file options, and create manual relationships like clients and sales when needed.

Master cardinality in Power BI by evaluating one-to-one, one-to-many, many-to-one, and many-to-many relationships to ensure accurate data filtering and a coherent star or snowflake schema.

Understand how to manage cross-filter direction in Power BI by using single-direction versus bi-directional filtering to ensure visuals reflect filters across related tables, such as company, sales, and product category.

Build and enrich a calendar date table in Power BI with Power Query, then mark it as a date table and connect it for time-based analysis using Time Intelligence DAX.

Explore real-world Power BI techniques to structure, customize, and enrich analytical reports using visuals, advanced formatting, and dynamic filters like slicers to support decision-making.

Learn to use line and area visuals in Power BI to track sales over time, compare multiple series, visualize contributions with stacked and combo charts, and update with filters.

Visualize the share of each sales channel with a pie chart and the distribution of payment methods with a donut chart, using dynamic filters and a center total card.

Explore how Power BI card visuals and CAPII indicators present key metrics, such as conversion rate and revenue by point-of-sale, with dynamic filters and real-time insights.

Compare and present data using Power BI table and matrix visuals, detailing row-by-row tables with totals and a cross-tab matrix for representative and period analysis, with dynamic filters.

Discover how slicers and filters in Power BI create an interactive report experience, enabling multi-select year filters, date range slicers, region and city slicers, and synchronized visuals across pages.

Master visual, page, and report filters in Power BI using the filters pane. Apply top N, contains, starts with, and multi-condition criteria to focus on specific products and cities.

Explore the Power BI marketplace to install certified and non-certified visuals, free and paid, and build dashboards with a timeline slicer and radar chart for multi-axis insights.

Create a custom Power BI theme by extracting logo colors with Adobe Color, building a JSON palette in PowerBI.tabs, and applying it to align visuals with your brand identity.

Explore how the AI-powered Key Influencers visual identifies factors driving customer rating and negative reviews, revealing role and topic drivers and actionable segment insights without DAX.

Use the Key Influencers visual in Power BI to explain why targets are met or missed by linking Target Achieved to factors such as discounts, loyalty tier, and delivery time.

Power BI's Q&A visuals enable natural-language queries to quickly reveal insights, such as top 5 products by revenue in 2024 or loyal versus new client revenue by month.

Explore how measures drive dynamic calculations in Power BI, covering implicit measures, calculated columns, and DAX measures to enhance reports and analytics.

Explore implicit measures and DAX-based calculated columns in a practical Power BI report, showing sum aggregation of quantity and a total weight column from unit weight and quantity.

Use the related function to retrieve unit volume from the products table, multiply by quantity from the sales table, and create a calculated column showing total delivered volume per sale.

Create dax measures for average, minimum, and maximum sales in Power BI, visualize them with card visuals and tables, and see dynamic updates when filtering by year 2024.

Create two DAX measures: distinct count of clients per product and total sales per product, and compare them in a table visual to assess product popularity and loyalty.

Create three margin measures in Power BI: minimum margin, maximum margin, and average margin, using minX, maxX, and averageX to analyze profit across products.

Master aggregation functions in Power BI Desktop to deliver reliable reports that align with business objectives, enabling advanced analysis and informed decision making.

Master the calculate function and filter control to build reliable indicators in power bi, using minX and maxX for year targeting and averages or medians by period with geographic filters.

Create DAX measures for min, max, and average net price in New York and outside New York, using the filter function and displaying results in a table visual.

Define dynamic sales that respond to user filters, and fixed sales for 2023 and 2024 using calculate with year filters, illustrating locked filters in Power BI.

Explore how the all function in Power BI builds a dynamic table to compare local city sales against global revenue, with weighting and a fixed national benchmark.

Discover how calculate and related functions drive time analysis, enable a two-year performance comparison, reveal pricing strategies through price evolution, and support geographic price trend comparisons.

Develop your skills with time intelligence functions through practical business scenarios. Progressively master each function and apply it in Power BI for non-technical profiles.

Explore Power BI's previous time functions to compare month, quarter, and year performance using a table visual, DAX measures for previous month, quarter, and year, and date table for alignment.

Analyze sales evolution by client with the samePeriodLastYear function in Power BI Desktop, using a table visual. Create a RevenueLastYear measure with RevenueSamePeriodLastYear and compare across year, quarter, or month.

Apply DAX time intelligence with DatesYTD and ParallelPeriod to compare sales for the same period across fiscal years, using a reference date like July 12, 2025, and assess growth.

Explore last date and dates in period functions in a real business context to monitor inactivity and purchase frequency with measures for last sale date, inactivity, and rolling 12-month frequency.

Power BI reveals information through variations over time using DAX time intelligence functions, turning numbers into actionable insights.

Learn AI-assisted forecasting in Power BI by building DAX measures for actual and forecast sales using a reference date and lending date, including linear projection and forecast revenue.

Design a Power BI replenishment dashboard using ChatGPT-assisted DAX to forecast three months from last year's sales, compute open quantity, propose purchases by supplier, and highlight critical items.

Explore how to measure supplier quality using Power BI and DAX, including on-time delivery rate, product conformity, and responsiveness to complaints, to generate a composite supplier performance score.