PL-300 | DA-100 Microsoft Power BI Certification - Exam Prep

Move a connected csv file to a new local location and update the data source path in Power BI using data source settings.

Learn to use the Power Query Editor to load and clean raw sales data, apply and manage transformation steps, and shape data for effective Power BI visuals.

Identify header row (row 3), remove the first two rows, promote the first row to headers in Power Query Editor, and remove the row and column while applying naming conventions.

Use user-friendly naming conventions for tables, columns, and values with descriptive, common-sense terms; remove prefixes like fact, replace underscores with spaces, and keep names clear for the end user.

Learn to resolve data inconsistencies with replace values, removing sales and NA values, converting to nulls, removing duplicates and blanks, and applying type changes before loading to the data model.

Evaluate and assign correct data types in Power BI by detecting types from the first 1000 rows, then fix text and NA issues to enable accurate visuals and date hierarchies.

Append queries to consolidate yearly sales data from multiple CSV files into a single master table in Power BI, load merged data, and ensure identical column names and data types.

Learn to merge tables in Power BI using a common column such as order ID, apply left outer, inner, or full join types, and expand merged data while removing duplicates.

Load cost data from a CSV into Power Query, unpivot year columns into a single cost column with a month field, then pivot to create distinct cost columns.

Learn how to create a conditional column in Power BI to generate month numbers from month names, enabling correct month ordering and easier reporting.

Use Power BI's columns from examples to add a new column by entering sample values and letting the tool auto generate the transformation, speeding up conditional logic.

Learn how to use the transpose and unpivot tools in Power BI to reshape year-by-year sales data into a single value column for effective visualization.

Profile data before loading the model with the query editor’s column distribution, column quality, and column profile, and compare distinct versus unique values across the top 1,000 rows.

Learn to diagnose and resolve common data loading errors in Power BI, including query timeouts, broken data sources, and data type conversions, with practical troubleshooting steps.

Connect to a folder using the folder connector in Power BI, verify the same data structure, and append or combine files into a single table that updates with new files.

learn how to connect to relational SQL databases in Power BI, including Azure SQL databases, using server and database parameters, authentication, and import versus direct query.

Explore the three storage modes—import, direct query, and dual—highlighting advantages, limitations, when to use each, and that switching from direct query to import is irreversible.

Connect Power BI to Microsoft Dataverse, a secure no-code data store, using the Dataverse connector with environment domain crm.dynamics.com, and Import or DirectQuery, with maker and read permissions.

Learn to use parameters in Power BI to dynamically load data, creating a year parameter and applying it in M code to update multiple data sources across environments.

Learn how to build a Power BI data model by connecting tables through relationships, enabling cross-table analysis and preparing for star schema concepts in practice.

Explore the star schema, a simple data model with a central fact table and surrounding dimension tables, and learn how primary and foreign keys connect them for Power BI analysis.

We bring in two additional dimension tables, clean and rename columns, and connect them to the sales fact table to form a simple, performant data model.

Edit relationships in Power BI by selecting columns, and understand cardinalities (many-to-one, one-to-many, and many-to-many) and cross-filter implications.

Explore cross filter direction in Power BI relationships, compare single and both for one-to-many relationships, and learn when filtering from the dimension to the fact improves performance.

Explore table and column properties in the data model view of Power BI Desktop, including hiding and viewing hidden tables and configuring synonyms for Q&A.

Explores creating a date dimension as a separate date table in Power BI, using external sources or DAX calendar auto with add columns for month, quarter, weekday, and holidays.

Create a date table in Power BI with Power Query, using the M formula and list dates, then transform the list into a table and rename it date.

Mark the date table in your model by selecting the table and date column, and set it as the date table with a date type and unique values (nulls allowed). This removes built-in date tables and their hierarchies, reducing the data model size for better performance and affecting related hierarchies by removing the date hierarchy.

Mark the date dimension as the date table, see the built-in hierarchy disappear, then create a custom date hierarchy and include year, quarter, month, and date to streamline analysis.

Resolve data granularity issues by creating a YearMonth column in cost and date tables, establish a relationship, and set cross-filter direction to both for monthly analysis.

Use a single date table to manage multiple relationships by creating an inactive relationship for the delivery date and using dax with userelationship to analyze deliveries across months.

Learn how to use DAX to create calculated columns and measures, adjust data types in the query editor, and understand the storage and performance trade-offs of calculated columns.

Learn about measures in Power BI and how they differ from calculated columns. Measures are not stored per row and are computed on demand using aggregations like sum.

Explore how measures differ from calculated columns, use sumx, an iterator function, to compute row-level revenue (sales times price) and then aggregate for better data model performance.

Learn how to use calculate in DAX to override a filter context and fix a measure to 2018 data, using revenue for 2018 as an example.

Learn how the filter function returns a table to alter the filter context, iterating the date table to limit rows to 2018 and enabling complex filtering in the calculate function.

Explore the all function as a table function in calculate that ignores filters to return all rows, enabling year revenue percentages across all years, such as 2018’s share.

Explore time intelligence in DAX by using date-related functions to build year-to-date analysis and compare current year to previous year with CALCULATE, DATESYTD, and DATEADD.

Create a semi-additive measure that returns end-of-period stock values using calculate and lastdate on a date table. This approach preserves end-of-month accuracy across date hierarchies, avoiding incorrect monthly sums.

Analyze price ranges in Power BI with DAX measures for minimum, maximum, median, variance, and average of the price column across days. Create measures in the sales table and compare results across days and hierarchies, selecting variance .P for population or a 100-value sample for faster performance.

Learn to use quick measures in Power BI to create running totals from revenue, view the underlying DAX, and explore built-in calculations while building DAX skills.

Optimize model performance in Power BI by reducing cardinality, shrinking model size, and improving DAX measures, using data types wisely, filtering data, and summarizing where possible.

Identify bottlenecks in a Power BI data model with Performance Analyzer, analyze DAX query times and implicit measures, and optimize by reducing visuals and correcting relationship cardinality.

Master creating visualizations in Power BI Desktop with the Visualizations pane, drag revenue and other fields, and use matrix charts to add years and multiple dimensions.

Explore how to use column charts, line charts, and area charts to display revenue by category, fix table relationships, and compare yearly trends.

Explore how combo charts and treemaps visualize revenue and sales across categories, showing correlation and space-saving insights alongside clustered column charts.

Display single numbers and multiple metrics with Power BI visuals, using card, multi-row card, and gauge visuals to show revenue, currency format, price statistics, and targets.

Compare pie, donut, and funnel visuals, explain when to use them, and introduce alternatives like bar, column, and treemaps, plus add cards, multi-row cards, gauges, and forms.

Explore scatter charts to relate revenue and price, use waterfall charts to show profit progression, and map geographic data for location insights.

Customize and format visuals with the Format tab, adjusting titles and backgrounds, and enhance visuals using tooltips, X-axis and Y-axis options, and data colors for clearer insights.

Create advanced graphical tooltips in Power BI by building a dedicated tooltip page. Set the visual to report page tooltips so it appears on hover with category and revenue visuals.

Design a Power BI report layout with the audience in mind, sketch the layout, limit visuals, then adjust page format and background, align visuals, and apply colors and themes.

Apply conditional formatting in Power BI visuals to highlight insights with color scales based on revenue. Configure rules, diverging colors, and color overrides, including center values.

Explore Power BI slicing and filtering with slicer visuals and the filters pane, showing interactive state and store filters, single vs multi-select, and page-wide options.

Learn how to sort Power BI visuals by axis, category, or month, toggle ascending or descending orders, and apply multi-column sorting using the sort by feature and shift key.

Sync slicers across report pages by using the sync slicers pane in the view ribbon, selecting the same state field on each page, and optionally controlling visibility.

Use themes to apply consistent colors and formatting across Power BI visuals and reports. Learn to import JSON themes, customize fonts and corporate colors, and export or revert to default.

Master drillthroughs and drill downs in Power BI to filter to a details page by category, view orders and revenue, and navigate hierarchies from category to subcategory.

Create and use bookmarks and buttons in Power BI Desktop to save and apply specific filter states and visual visibility, enabling show weekends and show all views.

Learn to configure cross-filtering and visual interactions in Power BI using the edit interactions pane, choosing filter, highlight, or none for each visual.

Learn to use Power BI's analyze feature to explain increases and decreases, explore distribution drivers in bar and line visuals, and add insights enabled by artificial intelligence to your report.

Identify outliers using scatter plots to compare revenue and sales, highlight them by category, and label groups to visualize their impact on overall revenue.

Create groups, bins, and clusters in Power BI to categorize weekdays and weekends, and to form price bins and revenue-driven clusters. Edit, rename, and adjust clusters for clearer visuals.

Explore the analytics pane to add lines such as trend, minimum, and average, plus percentile and symmetry shading, and leverage colors to convey insights in line and area charts.

Explore the forecast feature in Power BI line charts to predict revenue with time series, adjust forecast length, ignore last points, set confidence intervals, and use seasonality.

Explore three ai features in the query editor, including text analysis with Azure cognitive service models like sentiment analysis, key phrase extraction, and language detection to derive insights from reviews.

After building a report, choose local use in Power BI Desktop or publish to Power BI Service for browser access, with Free, Pro, or Premium licenses for sharing and collaboration.

Explore pricing models in Power BI Service, including free, pro, and premium capacity, and learn how each enables sharing, collaboration, publish apps, and scalable content distribution.

Learn how to sign up for Power BI service on powerbi.com for free using a work or school email, get started, and preview the interface.

Navigate the Power BI service interface using left navigation to access apps, data sets, and workspaces, publish reports to cloud, export data, and start a 60-day Power BI Pro trial.

Publish Power BI reports from Power BI Desktop to Power BI service, manage workspaces, and export data from visuals to Excel or csv with Power BI Pro or Premium licensing.

Apply sensitivity labels in Power BI to protect reports, dashboards, and datasets from unauthorized access, requiring organization-wide enablement, edit permission on content, and a pro or premium per user license.

Create a real Power BI workspace with a Pro or Premium Per User license, customize its name, description, image, and contact list, and publish reports for team collaboration.

Explore assigning workspace roles in Power BI, compare admin, member, contributor, and viewer permissions, and learn who can publish, edit reports, and manage users.

Create and publish a workspace app in Power BI by selecting reports, configuring navigation, and granting permissions to individuals or groups with pro licenses or premium capacity.

Update an app in its workspace by adding content, uploading or publishing reports, and editing page visibility. Use workspace as a staging area to test changes before updating the app.

Explore how to create and customize dashboards in Power BI by pinning visuals from reports, arranging tiles, drilling down to reports, and pinning live pages from the workspace.

Discover how the Q&A feature uses natural language to generate visuals, letting you pin them to dashboards, reuse synonyms, and tailor insights in Power BI reports.

Apply and customize dashboard themes in Power BI by uploading JSON themes, selecting presets, adjusting tile colors and opacity, saving, and reusing themes across dashboards, including mobile layouts.

Configure mobile layouts for Power BI reports and dashboards in Power BI Desktop or Power BI Service, adjusting visuals and sizes, and explore auto generate insights from our data.

Learn to use Power BI quick insights to automatically uncover dataset insights with machine learning and pin compelling tiles to your dashboard to enhance storytelling.

Learn how to connect on-premise data to Power BI by installing and configuring a data gateway, resolve credentials, and enable scheduled refresh for datasets.

Set up automated data refresh for your Power BI dataset by configuring the online gateway, credentials, and scheduled times, and monitor the refresh history to catch and fix errors.

Learn to set up and test subscriptions for Power BI dashboards and reports, including recipients, subject, message, frequency, time, and start date. Licensing requires Power BI Pro or Premium capacity.

Set up data alerts on gauge, card, or KPI visuals in Power BI dashboards to receive threshold-based notifications and optional email alerts, with per-user scope under pro or premium.

Endorse Power BI content to guide end users by promoting or certifying reports, datasets, and apps. Set endorsements, feature items on home, and enable discovery and access for trusted content.

Configure row-level security in Power BI by testing roles in Power BI Desktop, assigning California to the security group in the service, and validating through test as role.

Create a single security table to manage one dynamic role in Power BI, linking the security table to stores by state and filtering data using the current user with USERPRINCIPALNAME.

Grant direct access to a dataset by using manage permissions, add users or groups, and assign read, reshare, and build rights while reviewing related content and lineage to track dependencies.

Use paginated reports for a pixel perfect view of tabular data when printing or exporting to PDF, built with Power BI Report Builder on Power BI Premium.

Import custom visuals from AppSource, search and filter visuals in the marketplace, and import them into Power BI Desktop to enhance reports.

Explore how to export Power BI data to Excel using Analyze in Excel from reports and datasets in Power BI Service, connect via OLE, refresh data, and share with others.

Master case studies by analyzing a realistic scenario with requirements, data sources, and user groups, then answer 8–12 questions by skimming text and navigating between information.

Practice the final exam with a 60-question, 100-minute simulation, including a case study, to build familiarity with the exam environment, target a 70% pass, and identify topics to review.

Schedule the PL-300 exam online or at a test center, sign in with a Microsoft account, run a system check with onVUE, and prepare for check-in 30 minutes early.

Prepare by completing lectures, quizzes, and practice test to identify weak topics; run the system test, verify your ID, check in 30 minutes before exam, manage time, and read carefully.

Claim your Microsoft Power BI Data Analyst badge after the exam, then share and showcase it on LinkedIn, your resume, or in your email signature through Credly.

Renew your Power BI certification by completing a Microsoft Learn assessment six months before expiry to renew for another year, connect your profiles, and stay up-to-date without retaking the exam.