Confident Power BI start - You will quickly get comfortable in Power BI and understand how to use it for business analysis, so you can work with more confidence and make better use of the tool from day one.
Data import from many sources - You will learn how to load data from Excel and CSV files, Access and SQL Server databases, and Excel data models, making it easier to bring scattered data into one report.
Better data preparation - You will master query transformations, custom columns, sorting, and merging data, so you can prepare a consistent dataset that is ready for reliable analysis and reporting.
Clearer visual reporting - You will learn how to choose and combine Power BI visuals to present results in a clear, useful way, helping business users and decision-makers understand the numbers faster.
Smarter DAX work - You will understand the difference between calculated columns and measures, and work with relationships and filters, so you can build formulas that truly match the analysis goal.
Useful DAX functions - You will use aggregation, text, logical, statistical, and filtering functions in DAX, so you can calculate rankings, business rules, and key metrics without manual data handling.
Stronger data model - You will learn how to build parameter tables, calculated tables, hierarchies, and table relationships, which will help you create more flexible, scalable, and well-structured reports.
Time-based analysis - You will master DAX Time Intelligence, build a calendar table, and use functions such as YTD, MTD, and year-over-year comparisons to analyse trends and changes over time.
The training opens with the Power BI environment itself, starting from installation and the main elements of the application. It also sets the business analysis context, so participants understand where reporting, modeling and later DAX work fit within the tool.
External sources enter the workflow through different connection paths and file types. This section covers importing data from .xlsx and .csv files, MS Access and SQL Server databases, as well as reusing data models prepared earlier in MS Excel.
Preparing data in Power BI involves reshaping queries before calculations and reporting begin. Participants work with query transformations, custom columns, sorting and data combination, learning how to align datasets so they can be used consistently in later modeling steps.
Power BI is used here as the reporting layer for data that has already been prepared and modeled. The section looks at ways processed data can be presented and how advanced visualizations can be combined to build coherent analytical views rather than isolated charts.
Before writing formulas, it is necessary to understand how the data model is organized and why that structure matters. This section covers core DAX concepts, model capabilities, table relationships, pivot tables and practical rules for arranging data in a consistent analytical layout.
Working with DAX starts from the model context in which formulas are evaluated. The section explains data types, active and inactive relationships, filtering, calculated columns and measures, including their differences, modification rules, operators, queries and formula structure.
Useful DAX functions are grouped here by the type of calculation they support in everyday model work. The section combines aggregation, text, statistical, logical, date and filtering functions, including CALCULATE, FILTER, RELATED and RANKX, with attention to where each category fits best.
Building analysis logic often requires dedicated tables beyond the source dataset. This part focuses on parameter tables, calculation tables and the use of filter functions, showing how table structures support scenario handling and controlled filtering in DAX models.
Hierarchies help organize dimensions for navigation and analysis across multiple levels of detail. Participants create and modify automatic and custom hierarchies, then use them to filter data correctly and control how users drill through related categories in reports.
DAX time intelligence relies on a properly prepared calendar table, including correct sorting and date structure. The section works through functions for period comparison, shifting and accumulation, such as SAMEPERIODLASTYEAR, DATEADD, DATESBETWEEN and TOTALYTD, TOTALMTD, TOTALQTD.
Excel skills - You should be comfortable using Excel tables, filters, and basic formulas, because this will make it much easier for you to understand data models and report workflows.
Data analysis basics - You should understand rows, columns, data types, and simple aggregations, so you can build a data model more easily and interpret calculation results correctly.
Source data handling - You should have experience working with CSV or XLSX files and understand tabular data structures, because the course includes importing and transforming such data.
Reporting logic - You should be able to define which metrics and data views are needed in an analysis, so you can translate business needs into measures, filters, and visuals more easily.
