Course Introduction
Microsoft Copilot is transforming business intelligence by introducing generative AI capabilities that help professionals analyze data, develop reports, create visualizations, and communicate business insights more efficiently. When integrated into the Microsoft Power BI environment, Copilot can assist users in exploring datasets, generating report content, creating analytical summaries, and interacting with business information through natural language. This course provides a practical understanding of how Microsoft Copilot can enhance Power BI development and AI-assisted business analytics, enabling organizations to improve reporting productivity, strengthen analytical capabilities, and support faster, evidence-based decision-making.
The programme explores the relationship between Microsoft Copilot, Power BI, Microsoft Fabric, and the wider Microsoft data and analytics ecosystem. Participants will examine the capabilities of generative AI in business intelligence, including natural-language interaction, AI-assisted report creation, automated insights, analytical explanations, and conversational data exploration. Particular attention is given to understanding the requirements for using Copilot effectively, including appropriate licensing, tenant settings, workspace configuration, supported workloads, data preparation, and organizational readiness. Participants will also examine how Copilot complements established Power BI capabilities such as Power Query, DAX, semantic models, dashboards, and interactive reports.
A major focus of the course is applying Copilot to practical business analytics activities. Participants will explore how natural-language prompts can support report development, identify relevant metrics, generate report page descriptions, summarize trends, and assist with analytical questions. They will investigate how AI can support the development and interpretation of DAX expressions, Power Query transformations, and data analysis workflows. The programme also examines how well-structured semantic models, meaningful field names, clear relationships, and appropriate business definitions improve the relevance of AI-generated results. Participants will learn why AI-generated formulas and analytical interpretations require testing and validation before being used in organizational reporting.
The course further examines AI-assisted dashboard development and performance reporting using Power BI. Participants will explore how Copilot can support the creation of report content, summarize key findings, explain performance indicators, and make business intelligence more accessible to different user groups. Attention is given to dashboard design, KPI monitoring, data storytelling, executive reporting, and the communication of analytical insights. The programme also introduces the role of Microsoft Fabric and modern data platforms in supporting integrated analytics, data engineering, real-time intelligence, and scalable AI-enabled reporting environments. Practical applications across finance, sales, human resources, procurement, operations, and strategic performance management are considered.
Successful implementation of AI-assisted analytics requires appropriate governance, security, and professional oversight. The course addresses data access permissions, row-level security, sensitivity labels, data privacy, information protection, responsible AI, and the risks of inaccurate or misleading AI-generated outputs. Participants will examine the importance of validating generated DAX expressions, checking analytical summaries, reviewing data lineage, and maintaining accountability for business decisions. Emerging developments in AI agents, conversational analytics, Microsoft Fabric integration, and automated enterprise reporting are also considered, with emphasis on their practical relevance and implementation challenges.
By the end of the programme, participants will be better equipped to use Microsoft Copilot capabilities within Power BI to improve report development, explore business datasets, generate analytical explanations, and support management decision-making. They will understand how to prepare data models for AI-assisted analytics, formulate effective prompts, evaluate generated outputs, and incorporate Copilot into existing reporting workflows. The course provides a foundation for improving business intelligence efficiency, strengthening self-service analytics, and building responsible AI-enabled reporting capabilities that align with organizational objectives and data governance requirements.
Duration
5 days
Who Should Attend
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Microsoft Power BI developers and report designers.
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Business intelligence managers and business intelligence analysts.
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Data analysts and business analytics professionals.
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Management information systems managers and reporting specialists.
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Data scientists and analytics consultants.
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Microsoft Fabric developers and data professionals.
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Database administrators and data engineers.
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Finance managers and financial reporting analysts.
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Monitoring, evaluation, and performance management specialists.
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Sales and marketing analytics professionals.
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Human resource analytics and workforce planning specialists.
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Operations managers and supply chain analysts.
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Digital transformation managers and technology strategy professionals.
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IT managers and enterprise data governance specialists.
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Department heads and senior executives responsible for data-driven decisions.
Course Objectives
By the end of this course, participants will be able to:
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Explain Microsoft Copilot capabilities, generative AI concepts, and their applications within Power BI and the wider Microsoft business analytics ecosystem.
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Configure and assess the prerequisites for using Copilot in supported Power BI environments, including licensing, workspace settings, tenant configuration, and organizational readiness.
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Prepare and optimize Power BI semantic models, including relationships, measures, naming conventions, and business definitions, to improve AI-assisted analytical results.
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Apply natural-language prompts to support Power BI report development, data exploration, analytical summaries, and the interpretation of business performance indicators.
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Use Copilot-assisted techniques to develop, understand, refine, and validate DAX expressions and Power Query transformations for business analytics.
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Develop AI-enhanced Power BI reports and dashboards that communicate organizational performance, highlight relevant KPIs, and support management reporting requirements.
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Interpret AI-generated insights, summaries, and analytical explanations while assessing their relevance, accuracy, limitations, and suitability for business decisions.
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Integrate Copilot-supported analytics into business workflows involving Microsoft Fabric, enterprise data sources, and existing organizational reporting systems.
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Apply data governance, security, privacy, access control, and responsible AI practices to protect organizational information and maintain trustworthy analytical outputs.
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Develop an implementation roadmap for adopting Microsoft Copilot in Power BI, including priority use cases, stakeholder readiness, performance indicators, and continuous improvement measures.
Comprehensive Course Outline
Module 1: Foundations of Microsoft Copilot and AI-Assisted Business Analytics
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Understanding generative AI, large language models, natural-language processing, and their relevance to modern business intelligence and data analytics.
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Examining Microsoft Copilot capabilities across the Microsoft ecosystem and its relationship with Power BI, Microsoft Fabric, and enterprise data platforms.
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Exploring the evolution from traditional report development to AI-assisted analytics, conversational business intelligence, and intelligent management reporting.
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Identifying business applications of Copilot in financial analysis, operational performance monitoring, customer intelligence, and strategic decision support.
Module 2: Microsoft Copilot for Power BI: Environment and Configuration
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Understanding the requirements for accessing Copilot in supported Power BI environments, including applicable licensing, capacity, and subscription considerations.
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Examining tenant settings, workspace configurations, administrator permissions, and other organizational prerequisites for enabling Copilot capabilities.
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Exploring the Power BI service, Microsoft Fabric environment, supported workloads, and the relationship between Copilot features and workspace architecture.
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Assessing organizational readiness, user access requirements, regional availability considerations, and implementation dependencies for AI-assisted Power BI adoption.
Module 3: Data Preparation and Semantic Model Optimization for Copilot
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Preparing business datasets through Power Query, including data profiling, cleaning, transformation, standardization, and validation for analytical use.
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Designing effective Power BI semantic models with meaningful table names, field descriptions, relationships, hierarchies, and clearly defined business measures.
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Understanding the role of DAX measures, calculation logic, synonyms, and business terminology in improving the quality of natural-language analytical interactions.
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Evaluating data quality, model documentation, metadata, and semantic model structure to improve AI-generated responses and analytical reliability.
Module 4: Prompt Engineering and Natural-Language Data Exploration
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Understanding prompt engineering principles and developing effective natural-language instructions for business analytics and Power BI reporting activities.
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Using Copilot to explore business datasets, identify relevant metrics, investigate performance trends, and formulate analytical questions.
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Applying contextual prompts to generate report descriptions, summarize findings, compare performance indicators, and explain changes in business results.
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Refining prompts through iterative interaction, clear business terminology, defined analytical parameters, and verification of generated responses.
Module 5: AI-Assisted DAX, Power Query and Analytical Development
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Exploring how Copilot can assist with developing, understanding, and refining DAX expressions for calculations, aggregations, and business performance indicators.
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Applying AI assistance to Power Query transformations, data preparation instructions, and the development of repeatable data processing workflows.
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Using Copilot to explain existing formulas, identify potential calculation issues, and support troubleshooting of analytical expressions.
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Validating generated DAX and transformation logic through testing, comparison with expected results, performance assessment, and professional review.
Module 6: Copilot-Assisted Power BI Report and Dashboard Development
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Using Copilot capabilities in supported Power BI workflows to assist with report creation, report page planning, and the development of relevant analytical content.
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Applying AI-assisted approaches to select appropriate visualizations, organize report layouts, and communicate important business performance indicators.
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Developing interactive dashboards and reports for financial monitoring, sales analysis, operational efficiency, and executive performance management.
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Improving dashboard usability through effective visual hierarchy, KPI organization, contextual explanations, data storytelling, and stakeholder-focused design.
Module 7: AI-Enhanced Business Intelligence Reporting and Performance Analysis
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Generating AI-assisted summaries of business performance, highlighting significant changes, emerging trends, and areas requiring management attention.
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Applying Copilot-supported analysis to revenue performance, budget variances, expenditure monitoring, customer behaviour, and operational indicators.
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Using natural-language interactions to investigate business questions and translate analytical findings into understandable management information.
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Evaluating the relevance and reliability of AI-generated insights through data verification, contextual interpretation, and comparison with established reporting results.
Module 8: Microsoft Fabric Integration and Advanced AI Analytics
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Understanding Microsoft Fabric architecture and its relationship with Power BI, OneLake, data engineering, data warehousing, and integrated analytics.
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Exploring how AI-assisted analytics can complement modern data platforms, enterprise data pipelines, and centralized business intelligence environments.
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Examining real-time intelligence, advanced analytics, data science integration, and emerging AI agent capabilities within the Microsoft analytics ecosystem.
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Evaluating integration opportunities, data connectivity, scalability, and performance considerations for enterprise AI-enabled business intelligence solutions.
Module 9: Security, Governance and Responsible Use of Copilot
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Understanding Power BI security architecture, workspace permissions, row-level security, object-level security, and their relevance to AI-assisted data access.
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Applying data governance principles, sensitivity labels, information protection, privacy controls, and secure handling of confidential business information.
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Assessing risks associated with inaccurate AI-generated summaries, misleading interpretations, incomplete context, and unverified analytical recommendations.
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Establishing validation procedures, human oversight, auditability, accountability, and responsible AI practices for organizational reporting and decision support.
Module 10: Practical Implementation, Emerging Trends and Organizational Adoption
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Developing practical use cases for Microsoft Copilot in Power BI reporting, analytical exploration, dashboard development, and management decision support.
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Assessing implementation requirements, licensing implications, capacity planning, staff capabilities, change management, and expected business value.
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Exploring emerging developments in conversational analytics, AI agents, automated report generation, and intelligent enterprise business intelligence workflows.
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Preparing an organizational adoption roadmap with priority applications, governance requirements, measurable success indicators, and continuous improvement strategies.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
