Efficient data import - You will learn how to load data from Excel and CSV files, Access and SQL Server databases, and Excel data models, so you can build reports faster from multiple sources.
Better data preparation - You will master query transformations, custom columns, data sorting, and table merges, which will help you prepare a clean and consistent dataset for further analysis.
Clearer visual reports - You will learn how to combine advanced visuals in Power BI to present results more clearly, making your reports easier to understand and more useful for decision-making.
Reliable data model - You will understand how to design a data model, organize tables, and use active and inactive relationships, helping you avoid errors and inconsistent analytical results.
Confident DAX work - You will learn to create and modify calculated columns and measures, understand when to use each one, and write DAX formulas that give you better control over calculations.
Useful DAX functions - You will practice aggregate, text, logical, statistical, date and time, and filtering functions, so you can build measures that answer real business questions.
More control with tables - You will work with parameter tables, calculated tables, filters, and hierarchies, allowing you to create more flexible reports and a smoother analysis experience for users.
Time-based analysis - You will learn to prepare a calendar table and use Time Intelligence functions to compare periods, calculate running totals, and track changes over time in your reports.
At the outset, participants prepare the environment and place Power BI within the context of business analysis. The section includes installation of the application and a practical orientation to the interface, showing how the tool supports analytical work from the first steps.
Importing data from different sources is the first operational step in building a Power BI solution. The section covers loading .xlsx and .csv files, connecting to MS Access and SQL Server databases, and using data models previously created in MS Excel.
Before analysis starts, data usually needs reshaping to fit the model and reporting logic. This section covers query transformation, creating custom columns, sorting data in Power BI, and combining datasets to prepare consistent structures for later calculations and visualizations.
Power BI is used here as the reporting layer where processed data is turned into readable analytical output. The focus is on methods of using transformed datasets and on combining advanced visualizations so that multiple views work together within one coherent report.
A well-structured data model is the starting point for effective work with DAX and pivot-style analysis. This section explains core concepts, typical applications, rules for organizing data, and the relationships between tables that determine how calculations and summaries behave.
Building formulas in DAX requires understanding how the data model, data types, relationships and filtering affect results. This part explains active and inactive relationships, operators, calculated columns, calculated measures, their differences, and the role of queries when creating or modifying expressions.
DAX function groups are presented in the context of everyday analytical work rather than as isolated syntax elements. Participants use aggregating, text, statistical, logical, date and time, and filtering functions, including CALCULATE, FILTER, RELATED and RANKX, to build practical expressions.
Working with dedicated tables extends model flexibility beyond source data and supports more controlled calculations. The section includes parameter tables, calculation tables, and the use of filter functions to shape context and influence how measures respond in analysis.
Hierarchies help organize dimensions into levels that support clearer navigation and more precise analysis in reports. The section covers automatic hierarchies, creating custom structures, filtering data within hierarchy paths, and adjusting existing hierarchies to match reporting needs.
Time intelligence in DAX focuses on building a reliable calendar table, including proper sorting and date structure required by time-based calculations. It then applies functions such as SAMEPERIODLASTYEAR, DATEADD, DATESBETWEEN and TOTALYTD, TOTALMTD, TOTALQTD to compare periods and calculate cumulative results.
Excel basics - You should be comfortable working with worksheets, tables, and basic formulas in Excel so you can better understand data sources and the analysis logic covered in training.
Tabular data handling - You should understand how data is arranged in rows and columns, recognize headers, and spot common table issues so you can prepare data efficiently for modeling and reporting.
Business analysis basics - You should understand what indicators, aggregations, and comparisons are used for in reports so you can build DAX measures more easily and interpret Power BI results correctly.
Computer literacy - You should be comfortable installing software, managing files, and navigating Windows applications so you can complete Power BI exercises smoothly during the training.
