Class Introduction

The team conducted a Power BI training session focused on data modeling and dashboard creation using the Northwind Trader dataset. The instructor guided participants through adding a date table to their model using a pre-written DAX formula and establishing relationships between order dates, required dates, and ship dates with the new date table. The session then progressed to building a dashboard, starting with creating a company logo, heading, and implementing multiple slicers for filtering data by category, country, employee, product, month, and company name. Participants learned to format slicers as drop-down lists and add a line chart showing date-wise sales data. The instructor demonstrated how to format shapes, align slicers, and customize visual elements using Power BI's formatting tools. The class concluded with an assignment for participants to create a similar dashboard using the hospital dataset they had been working with, incorporating the same elements learned during the session.

Northwind Trader Date Table Implementation
The team discussed adding a date table to their Northwind Trader data model in Power BI. They followed instructions to create a new table and implement a pre-written DAX formula to generate the date table with columns for years, months, dates, and weekends. The team then established relationships between the date table and existing tables by linking columns like order date and required date to the date table.

Related Offerings

Power BI Date Table Linking
Gagan and the team discussed how to properly link date columns in a Power BI data model. The team explained that a date table is needed to filter dashboard views by different dates, such as year or quarter-wise sales. They guided Gagan through the process of creating and linking the date table, addressing issues with the relationship type and suggesting a fresh start by deleting and recreating the date table.

Dashboard Training Session Overview
Gagan led a training session on creating dashboards in a reporting tool, guiding the team through basic functionality including switching from model view to report view, using the canvas area for building charts, and accessing various chart types through the insert tab. The team practiced creating a pie chart showing category-wise net sales data and explored theme customization options. Gagan provided an overview of standard dashboard layout elements including company logo, title, and date filters, and demonstrated how to apply different data filters to dashboards before concluding with instructions on using the snippet tab for shapes.

Dashboard Formatting Demonstration
Gagan demonstrated how to build a dashboard step by step, starting with formatting a green box as a heading and adding a company logo in the top left corner. The team learned how to insert and format slicers as data filters, with Gagan showing how to change the slicer style from checkboxes to a dropdown format and adjust visual borders. Gagan emphasized that dashboard formatting involves trial and error with various styling options available through the format tools.

Power BI Slicer Formatting Training
The team discussed creating slicers and formatting them in Power BI, with Gagan seeking help to find the format options. The instructor guided the team through creating six different slicers using various data fields including category name, country, employee name, product name, month, and company name. They then learned how to format and align the slicers using the format options in the visualization pane. The session concluded with instructions on creating a line chart using net sales and order date data, and adding a date slicer for filtering the dashboard. The team was assigned to create a similar dashboard using hospital data, incorporating a logo, heading, and simple charts.

Ready to create professional, interactive Power BI dashboards?

👉 Explore the Power BI Data Analytics Training Program and learn data modeling, DAX, slicers, visualizations, and dashboard design through hands-on projects and real-world datasets.