Business Intelligence in Power BI Desktop 2400-SP-SQL-PBID
The goal of this course is to familiarize students with Power BI and the topic of business intelligence in a business context.
Course topics:
✓ Automating data import and transformation using Power Query
Importing various types of data files (MS Excel workbooks, test files, CSV files) and loading data from folders. Data transformations involving various types of variables (including operations on numbers, text, and dates). Defining custom columns and conditional columns. Automating data import and transformation. Filtering and sorting, replacing values, grouping, transposing, and rearranging data. Merging and joining data.
✓ Creating a data model
Creating a data model using relationships. Understanding the concept of quick measures. Basics of the DAX language—creating custom calculated columns and measures using, among others, the following functions: CALENDAR, RELATED, DATESINPERIOD, DATEADD, CALCULATE, DATESYTD, ALL, SUMX, FILTER.
✓ Data Visualization and Report Creation
Creating interactive reports using various chart types, including line charts, bar charts, scatter plots, waterfall charts, funnel charts, tree maps, gauge charts, key performance indicators (KPIs), dashboards, and heat maps. Visualization of geographic data—creating maps, shape maps, and cartograms. Filtering reports at various levels—visualization, page, and the entire report. Utilizing interactions between visual elements. Exploring detailed view options. Using “what-if” scenarios. Applying various types of conditional formatting.
Course coordinators
Type of course
Mode
Learning outcomes
Learning outcomes Participants gained the ability to perform comprehensive data analysis and create reports using Power BI Desktop. They are able to use the software to automate the data import process, prepare data for reporting, and create data visualizations in line with the latest trends in business intelligence (BI).
Assessment criteria
An independent assessment task to be completed by the participant upon course completion. A minimum score of 50% is required to pass.
Bibliography
Materials prepared by the lecturer and made available to participants on e-learning platform