Trending Now

Three teams are working on the same Feature. Team A is a complicated subsystem team, and Teams B and C are stream-aligned teams. During PI Planning, Teams B and C commit to delivering by the end of Iteration Five.
What is one outcome of an integration point?
How is average lead time measured in a Kanban system?
During Iteration planning, the Product Owner introduces multiple new Stories to the team.
Top Governing Bodies Certifications for Change Management Training
Global Talent, Local Impact: Building Capabilities Across Borders
Introductory Guide to Agile Project Management
How to Start Lean Six Sigma Yellow Belt Certification Journey?
12 Project Management Principles for Project Success
An Agile Team decides they want to use pair programming in future Iterations. Where should this be captured?
What is a benefit of an Agile Release Train that has both cadence and synchronization?
What is one way a Scrum Master leads the team's efforts for relentless improvement?
A Beginner's Guide to Site Reliability Engineering
What is one problem with phase-gate Milestones?
What is the purpose of the retrospective held during an Inspect and Adapt event?
What should be the first step a team should take to feed potential problems into the Problem-Solving workshop?
Agile vs. DevOps: Difference and Relation
What is Agile Testing for Projects? - Best Practices & Benefits
What is Agile: History, Definition, and Meaning
The Agile Way of Thinking with Examples
Product Owner Responsibilities and Roles
CSM vs. SSM: Which Scrum Master Certification is Better?
Agile Scrum Product Owner Roles & Responsibilities
Top 7 Project Management Certifications to Level Up Your IT Career
Guide to Scrum Master Career Path in 2024
Scrum Master Certification Exam Preparation Guide
Agile vs SAFe: Comparison Between Both
Agile Scrum Best Practices for Efficient Workflow
Advantages of Certified Scrum Master
How to Get CSPO Certification?
Top 7 Ethical Hacking Tools in 2024
Ethical Hackers Salary Worldwide 2024!
The Complete Ethical Hacking Guide 2024
What is the output of an Inspect and Adapt event?
Lee is a developer on the team. At every daily stand-up Lee reports, "Yesterday, I worked on indexing. Today, I will work on indexing. No impediments." What approach should the Scrum Master suggest to Lee to improve the team's visibility into his work?
How is team performance calculated in SAFe?
What is the purpose of the scrum of scrums meeting during PI Planning?
Which statement is true about batch size, lead time, and utilization?
When is collaboration with System Architects and the Systems Team likely to have the greatest impact on Solution development?
SRE vs DevOps: Key Differences Between Them
Everything about CISSP Certification
How to Pass the CISSP Certification?
What is one way a Scrum Master can gain the confidence of a stakeholder?
The ART stakeholders are concerned. What should be done?
What does a Scrum Master support in order to help the team improve and take responsibility for their actions?
What are two characteristics of teams that fear conflict?
What goes into the Portfolio Backlog?
What are three opportunities for creating collaboration on a team? 
The purpose of Continuous Integration is to deliver what?
Which of the four SAFe Core Values is an enabler of trust?
What is one requirement for achieving Continuous Deployment?
When should centralized decision-making be used?
What is a Product Owner (PO) anti-pattern in Iteration planning?
How are the program risks, that have been identified during PI Planning, categorized?
The work within one state of a team's Kanban board is being completed at varying times, sometimes running faster and sometimes slower than the next state. What could resolve this issue?
What is a good source of guidance when creating an improvement roadmap that improves the teams technical practices?
A team consistently receives defect reports from production even though each Story is thoroughly tested. What is the first step to solve this problem?
What are two benefits of applying cadence? (Choose two.)
Which statement is true about work in process (WIP)?
What are relationships within a highly collaborative team based on?
A Scrum Master is frustrated that her team finds no value during Iteration retrospectives, and the team has asked that she cancel all future ones. Which two specific anti-patterns are most likely present within the team’s retrospectives? (Choose two.)
What are two purposes of the scrum of scrums meeting? (Choose two.)
What is the primary goal of decentralized decision-making?
How can a Scrum Master help the team remain focused on achieving their Iteration goals?
What are the benefits of organizing teams around Features?
If the distance between the arrival and departure curves on a team's cumulative flow diagram is growing apart, what is likely happening?
What is the purpose of the Large Solution Level in SAFe?
Why is the program predictability measure the primary Metric used during the quantitative measurement part of the Inspect and Adapt event?
Inspect and Adapt events occur at which two SAFe levels? (Choose Two)
Which two statements are true about a Feature? (Choose two.)
The Agile Team includes the Scrum Master and which other key role?
What are two actions the Scrum Master can take to help the team achieve the SAFe Core Value of transparency? (Choose two.)
Systems builders and Customers have a high level of responsibility and should take great care to ensure that any investment in new Solutions will deliver what benefit?
Which two Framework elements would a Scrum Master have the strongest connection and most frequent interaction? (Choose two.)
If a team insists that big Stories cannot be split into smaller ones, how would the Scrum Master coach them to do otherwise?
Why are Big Stories considered an anti-pattern?
CISA vs CISM: Which is better for a Cybersecurity Career?
Who is responsible for managing the Portfolio Kanban?
What is the goal of the House of Lean?
Social Media Marketing Strategies for Building Your Brand Presence Online
ITIL 4 Foundation Exam Tips and Study Guide
What is Site Reliability Engineering (SRE)?
How Toyota Entered the Luxury Car Market with Kaizen Principles
What are two ways to describe a cross-functional Agile Team? (Choose two.)
According to SAFe Principle #10, what should the Enterprise do when markets and customers demand change?
AWS Solution Architect Roles, Responsibilities and Salaries
Advantages of Attaining CISA Certification
The Importance of Vulnerability Management
AWS Career for Beginners in 2024
What is AWS Cloud Computing?
Certified Information Systems Auditor Certification
Navigating Project Success: Role of Prince2
ITIL 4: A Journey from Certification to Implementation
Python for Non-Programmers – Unlock New Career Opportunities
What is Service Integration and Management (SIAM)?
SIAM Governance Three Key Layers
What are the core values of the Scaled Agile Framework?
Leading SAFe Certification Exam Preparation
ITIL V4 Major Changes and Updates
ITIL 4 Framework Latest Updates
AI and Power BI: A Powerful Combination for Data Visualization

AI and Power BI: A Powerful Combination for Data Visualization

Picture of Stella Martin
Stella Martin
Stella brings over a decade of expertise in AWS and CyberSecurity, showcasing a remarkable record of success. Her extensive experience spans various facets of these fields, making her a valuable asset to any team or project requiring specialized knowledge and proficiency.

Artificial Intelligence (AI) significantly influences the Microsoft Power BI dashboard in Data Visualization. A Microsoft Certified Data Analyst is getting thousands of meaningful and powerful ways to extract insights from data using pre-trained Machine Learning models and custom functions. Power BI has a steady update of tools and visuals with AI features, and often, it becomes tough for Data Analysts to keep updated. Microsoft Power BI, one of the most influential leaders in business intelligence and augmented analytics with the integration of AI is, therefore, doing wonders and becoming invisible concerning Data Visualization.

Power BI is More Than a Visualization tool

Microsoft Power BI has three major components, making it a modern enterprise BI platform. 

  • Data Visualization
  • Data Modelling
  • Data Preparation
Using AI in Microsoft Power BI

Source: Using AI in Microsoft Power B

The image above shows the specific regions of the Power BI platform where unique AI features are present. Let’s see the key AI features present in the Microsoft Power BI platform that make it superior to many other BI tools. Data Analysts mainly use the following traits of AI in Power BI.

Decomposition Tree

Data Analysts use Power BI to represent and interpret data easily, and with the three exclusive AI visuals, the entire procedure becomes seamless. The new AI features can be identified as bulb icons, and Data Analysts can utilize those to bake into traditional visuals, such as bar and column charts.

The decomposition tree is one such AI Visualization developed by the Power BI team. Decomposition or breaking down is a characteristic that shows a measure broken down by various attributes across different dimensions. This feature plays a great role during an ad hoc exploratory analysis of the data. Besides, Data Analysts use it for root-cause analysis with the help of the built-in AI feature.

high value and low value of AI visualization decomposition tree in Power BI

There are two values: High Value and Low Value. Choosing any of these options will ask the feature to execute an “AI split,” subsequently identifying the next field to showcase either the highest or lowest value.


Quick Insights is one of the most straightforward AI functionalities present within Power BI. Primarily, all you need to do is click on your dataset and choose “Get quick insights.” Power BI will then employ diverse algorithms to seek out and pinpoint trends in your data. It’s crucial to note that having a well-structured data model enhances the effectiveness of Quick Insights, yielding more valuable results. After Quick Insights completes its algorithms, you can click “View Insights” to assess the visuals and decide whether you want to retain any by pinning them to a dashboard.

AutoML in Power BI

Automated Machine Learning in Power BI is often considered ‘Machine Learning with training wheels’ by both Data Analysts and Business Analysts. It supports Binary Prediction, General Classification, Regression models, Future forecasting, etc., and acts as a hands-on tool for analysts or developers who want to prototype functionality in Power BI.

Automated Machine Learning using AI in Power BI

Source: Automated Machine Learning using AI in Power BI

Prime AI Features of Microsoft Power BI

The figure below organizes the taxonomy in three ways: 

  • Feature type
  • Grouped under a shared label
  • Primary intended role, where tools in blue are for users, grey for developers, and black for data scientists
  • A feature is in preview or generally available, shown by a white or grey fill, respectively
AI features of Microsoft Power BI

Source: AI features of Microsoft Power BI

AI Augmented Visuals

AI-augmented visuals in Power BI

Using these special AI features in Microsoft Power BI started as regular visuals has now become invincible. 

  • The Decomposition Tree uses AI Splits to break down various traits and characteristics into high or low values according to the requirements of Data Analysts or developers.
  • Clustering in Table and Scatter Charts groups similar observations together, saving the results as a new measure. 
  • Using AI-infused “Insights” appears in various visuals like the Clustered Column Chart. It helps explain visual changes or differences in distribution based on different slicers. 
  • Lastly, in the Line Chart, you can add a trend line, forecast a time series, or spot anomalies.

AI-integrated Visuals

AI-integrated visuals in Power BI

Smart Narrative, Key Influencers, and Q&A are the main visuals that are strongly AI-powered. 

  • Smart Narrative enables changing text descriptions for visuals
  • Q&A lets users explore data and supports developers to generate visuals using text input. 
  • The Key Influencers visual identifies important influencers and top segments for a target outcome by performing a statistical and machine learning analysis in a user-friendly way.

Data Exploration and Editing

Data Exploration and Editing in Power BI

Create Report:

  • Automatically generates a report on Power BI Service.
  • Based on pasted data for quick report creation.

Quick Insights:

  • Rapidly generates interesting visuals from data.
  • Enables swift exploration of data.

Power Query Editor:

  • Transforms data before loading into Power BI.
  • Notable AI features include: Column generation helps to add new columns from examples. HTML extraction where analysts mine web data from examples. Fuzzy matching boosts merging nearly similar columns.

Data Extraction in Power Query:

  • Extracts data from Text or CSV files using examples.
  • Automatically detects tables from Excel or JSON files.

Target Audience:

  • Primarily designed for Power BI developers.
  • Data scientists can also benefit from the powerful tools within Power Query Editor.

Data Enrichment

Data Enrichment in Power BI

These features can be found in the “AI Insights” section of Power Query. They are designed for Developers, Data Scientists, Data Analysts, etc., and they augment data using Azure Cognitive Services within Power BI. Another key feature is Text Analytics which can input text data and output the detected language, key phrases, and sentiment. Computer Vision being a very special member of the Data Enrichment department can input images and output tags for common objects identified within those images.

AI Add-ons

AI Add-ons in Power BI

While presented here as a unified feature, AI Add-ons serve as an entry point to an extensive array of publicly generated visuals tailored for diverse user groups. Numerous visuals within this collection integrate AI functionalities; however, providing documentation for each falls beyond the scope of this blog post.

Data Science Tools

Data Science Tools in Power BI

This is the treasure for Data Scientists that includes R Integration and Python Integration that can be used to:

  • Collect Power BI data while using custom Data Science models like built-in R or Python, 
  • Conduct advanced text manipulations and calculations during the ingestion process, exceeding the capabilities of native Power BI functionality
  • Craft personalized visualizations in Power BI

Case Studies where brands have integrated AI with Power BI service

AI-integrated Power BI service is a combination of these two technologies, which allows users to leverage AI capabilities within Power BI to enhance their data analysis and decision-making. Some of the latest case studies where companies have used AI-integrated Power BI services for data representation are:

Generative AI and Power BI

This case study by Infopulse, a global IT service provider, showcases how generative AI models can be used in Power BI to create original outputs, such as texts, visuals, audio, or code, based on the data provided. The case study also demonstrates how generative AI models can help with data querying, analysis, and visualization, as well as make data analytics more accessible and efficient.

Infopulse using AI-infused Power BI for analyzing data

Source: Generative AI Use Cases in Data Analytics and BI (

Artificial Intelligence sample for Power BI

This case study by Microsoft provides a sample report for a fictitious company named Contoso, which uses various AI visuals in Power BI to understand their products and regions’ key contributors for revenue won/loss, identify the highest or lowest breakdown of revenue, and detect anomalies in their data. The case study also explains how to use the Key influencers, Decomposition tree, and Anomaly detection visuals in Power BI, and how they can help users discover new insights and inform their decision-making.

AI visuals in Power BI in a fictitious company called Contoso by Microsoft

Source: Artificial Intelligence sample for Power BI: Take a tour – Power BI | Microsoft Learn

AI-powered Data Analytics & Insights

This case study by Bigint Solutions, a data analytics and AI consulting firm, presents a data analytics report for employee attrition analysis, using R programming and Power BI. The case study follows a methodical framework to understand the data, visualize it, and analyze the factors influencing attrition. The case study also uses AI techniques, such as clustering, decision trees, and random forests, to identify the patterns and trends in the data, and provide recommendations to reduce attrition.

employee attrition analysis by Bigint Solution using AI-integrated Microsoft Power BI

Source: Case Study | AI-powered Data Analytics; Insights | Business Data Insights (


AI-integrated Power BI service is a powerful tool that can help users create interactive and engaging reports and dashboards with superior Data Visualization and insights. Using AI in Microsoft Power BI, data professionals can utilize this feature to gather data and analyze it, followed by proper decision-making. Many case studies demonstrate how several companies and industries have used AI-integrated Power BI services for data representation and achieved their business goals. At Spoclear, we deliver Microsoft Power BI Data Analyst training for professionals and aspiring Data Analysts to gain a complete understanding of the Power BI tool and how it can be used with AI to get the best results

Leave a Reply

Your email address will not be published. Required fields are marked *

Popular Courses

Follow us









Subscribe us