
Assess your reporting landscape by listing all reports and classifying them as descriptive, diagnostic, prescriptive, or predictive to guide BI toward diagnostic, prescriptive, and predictive analytics with AutoML.
Download Power BI Desktop for 64-bit or 32-bit systems and publish dashboards to the free service; upgrade to Pro or Premium for advanced analytics, including logistic regression and classification models.
Learn how to build visuals in Power BI using visualization options, filter reports by product or country, and create and format a text box banner for dashboards.
Create a treemap to compare units sold by product. Format borders and data labels, adjust font sizes, and center the title to build a clear Power BI dashboard.
Create a dual axis chart in Power BI using a line for units sold and a stacked column for profit by segment, then format with borders, shadows, and axis options.
Create a map visualization that displays profit, sales, and discounts by country, using circle size to reflect profit and tooltips to show detailed metrics.
Create a final Power BI chart to compare country performance by profit and output, grouping United States and India, and adjust color and font size for clarity.
Explore six dax function types: date and time, lookup value, logical, math, percentile, and text, and learn where to write them—measure, new column, quick measure, and conditional column—in Power BI.
Create a conditional column in Power BI using DAX and Power Query Editor to classify profit or loss, with nested if and switch alternatives and basic debugging tips.
Create a max value measure with max and maxx across tables, then format date columns using format to display month and year.
Explore how to establish one to many relationships across tables using common keys like customer ID and product ID, enabling computations for different visualizations in Power BI.
Publish your Power BI desktop visuals to the web service, sign in, and publish to a workspace. Share, export, embed, manage permissions, and track who opens the report.
Learn to build an aging analysis dashboard in Power BI by creating age and age-group columns, grouping delays into 30-day intervals, and visualizing revenue and aging counts with interactive slicers.
Recent Updates:
June 2023: Added a video lecture on Clustering and Segmentation
Nov 2022: Updated the course with using DAX functions like Calculate and Lookup
June 2022: Added a case study on using Python (programming language) in PowerBI environment
May 2022: Added a case study on Benford Law (Benford law is used to detect fraud)
April 2022: Added a case study on Ageing Analysis
Course Description:
In the last 50 years, the world of reporting, analytics and business intelligence (BI) has seen many of evolutions. The notable ones are the rise of self service BI and augmented analytics. Businesses are no longer content with descriptive or diagnostic analytics. The expectation for prescriptive and predictive analytics has become the new normal.
Machine learning and Artificial Intelligence technology has also evolved significantly in the last decade and the notable evolution is the rise of Auto ML - the no code machine learning approaches. Auto ML has significantly democratized predictive analytics. End users can predict the future outcomes of businesses in a few (mouse) clicks.
Power BI epitomizes the recent trends in business intelligence (BI) and augmented analytics for interactive, easy to use and self-serve dashboards & auto ML capabilities.
This is a comprehensive course on Power BI covering the following:
Data Transformation
DAX
Data Models
Simple & complex visuals
AI enabled visuals
Auto ML: Concepts and no code approaches to forecast future
There are no pre-requisites for this course, although knowledge of excel would be advantageous.
There are actually 2 courses (Power BI and AI - ML) in this course and both are covered in great detail. Whether your objective is to learn power bi or machine learning or both, this course will deliver the goods for you.