Business Analyst Course in Kuwait
Business Analyst career acceleration in 85 hours
Hands-on training across Excel, SQL, Power BI, Tableau & Microsoft Fabric
AI-powered Business Analysis & Reporting with Automation Sandbox
Enterprise Digital Transformation simulation with stakeholder & KPI analysis
Capstone project with real-world business scenarios & dashboards
Flexible learning modes & easy payment options
4.9/55868 EnrolledEnrolled Learners
4.9/55868 EnrolledEnrolled Learners
Overview
What will you learn from us:
- Develop strong capabilities in modern business analysis and stakeholder engagement
- Enhance your skills in requirements engineering and business process optimisation
- Turn data into useful insights using Excel, SQL, and predictive analysis
- Design interactive Power BI dashboards for KPI tracking and performance reporting
- Use Generative AI to improve documentation, reporting, and insight creation
- Produce clear management reports through dashboard visualisation and data storytelling
- Apply Agile delivery, product ownership, and solution evaluation best practices
- Make smarter business decisions with business intelligence tools and AI-driven analytics
Upcoming sessions
Curriculum
1
Evolution of Data Analytics
2
Modern Analyst vs Traditional Analyst
3
AI-Powered Decision Intelligence
4
Data-Driven Business Culture
5
Understanding Business KPIs
6
Business Problem Solving Frameworks
7
Analytics Lifecycle
8
Introduction to AI in Analytics
9
Responsible AI Fundamentals
10
ChatGPT
11
Copilot
12
Claude
AI Integration
- Analyze business KPIs and performance drivers
- Generate AI-assisted business insights and recommendations
Activities/Case Study
- Business Decision Simulation
1
Excel Interface & Modern Workflows
2
Data Cleaning Techniques
3
Data Validation
4
Advanced Formulas
5
XLOOKUP
6
INDEX-MATCH
7
IF Logic
8
PivotTables & PivotCharts
9
Power Query Basics
10
Dashboard Development
11
Business Reporting Automation
AI Integration
- Copilot for Excel
- AI-Assisted Formula Generation
- AI-Powered Reporting
- Natural Language Data Analysis
Activities/Case Study
- Sales KPI Tracker
1
SQL Fundamentals
2
Filtering & Sorting
3
Joins
4
Aggregations
5
Subqueries
6
Common Table Expressions (CTEs)
7
Window Functions
8
Query Optimization
9
Business Data Extraction
10
Reporting Logic
AI Integration
- Natural Language to SQL
- AI-Assisted Query Writing
- Query Optimization using AI
- AI Debugging Workflows
Activities/Case Study
- Sales Intelligence Reporting
1
Power BI Ecosystem
2
Data Import & Connectivity
3
Power Query
4
Data Transformation
5
Relationship Management
6
Data Modeling Basics
7
Star Schema Foundations
AI Integration
- Analyze data quality and transformation opportunities
- Generate reporting insights from imported datasets
Activities/Case Study
- Data Cleaning Workflow
1
Data Modeling Best Practices
2
Star vs Snowflake Schema
3
Measures vs Calculated Columns
4
DAX Fundamentals
5
Time Intelligence
6
KPI Calculations
7
Context Transition
8
Advanced DAX
9
Performance Optimization
AI Integration
- AI-Assisted DAX Generation
- Copilot for Power BI
- DAX Optimization using AI
Activities/Case Study
- Procurement Intelligence Dashboard
1
Dashboard Design Principles
2
Executive Reporting
3
KPI Storytelling
4
Drillthrough Features
5
Interactive Analytics
6
Mobile Dashboard Optimization
7
Smart Narratives
8
AI Visuals
9
Business Presentation Techniques
AI Integration
- Generate executive dashboard narratives
- Support business storytelling and insight communication
Activities/Case Study
- Country-Level Performance Dashboard
1
Power BI Service
2
Workspaces
3
Publishing Reports
4
Data Refresh
5
Row-Level Security
6
Collaboration Features
7
Governance Basics
8
Deployment Pipelines
AI Integration
- Monitor dashboard usage and reporting performance
- Support governance and deployment decisions
Activities/Case Study
- Secure Dashboard Sharing
1
Microsoft Fabric Overview
2
OneLake Concepts
3
Lakehouse Architecture
4
Fabric Dataflows
5
Semantic Models
6
Real-Time Analytics
7
Fabric + Power BI Integration
8
Enterprise Analytics Architecture
9
Data Governance Fundamentals
10
Azure Analytics Ecosystem
11
Snowflake Overview
12
Databricks Overview
13
BigQuery Overview
14
dbt Awareness
AI Integration
- Analyze enterprise data architecture requirements
- Support modern analytics platform design decisions
Activities/Case Study
- Enterprise Reporting Architecture Design
1
Prepare Data
2
Model Data
3
Visualize Data
4
Analyze Data
5
Deploy & Maintain Assets
Activities/Case Study
- Enterprise Reporting Scenarios
1
Business Analysis Foundations
2
Introduction to Business Analysis
3
Understanding the Business Analyst Role
4
Business Analyst Career Path
5
Core Competencies of a Business Analyst
6
Business Functions
7
Business Models & Revenue Streams
8
Customer Value
9
KPIs and Business Objectives
10
Analytical Thinking & Problem Solving
11
Problem Identification
12
Root Cause Analysis
13
Decision-Making Frameworks
14
Business Case Analysis
15
Stakeholder Management & Communication
16
Stakeholder Identification
17
Stakeholder Mapping
18
Business Communication Techniques
19
Business Meetings & Workshops
20
Conflict Resolution Strategies
AI Integration
- Analyze stakeholder needs and business challenges
- Generate stakeholder communication plans and business analysis insights
Activities/Case Study
- Business Transformation Stakeholder Alignment Project
1
Requirements Engineering
2
Requirement Types
3
Requirement Elicitation Techniques
4
Requirement Validation
5
Requirement Challenges
6
Documentation Fundamentals
7
BRD Structure
8
Functional Specifications
9
User Stories
10
Acceptance Criteria
11
Business Process Analysis
12
Business Process Mapping
13
As-Is Analysis
14
To-Be Analysis
15
Gap Analysis
16
Process Improvement Opportunities
AI Integration
- Generate requirements documentation and user stories
- Analyze process gaps and recommend improvement opportunities
Activities/Case Study
- Enterprise Process Optimization Initiative
1
Agile Business Analysis & Product Ownership
2
Agile Fundamentals
3
Scrum Framework
4
Agile BA Role
5
Story Mapping
6
Backlog Management
7
Product Vision
8
Product Roadmaps
9
Prioritization Techniques
10
Data-Driven Business Analysis
11
Data-Driven Decision Making
12
KPI Analysis
13
Business Reporting & Dashboards
14
Solution Evaluation
15
Business Outcomes
16
User Acceptance Testing
17
Continuous Improvement
18
Jira
19
Lucidchart
20
Business Analysis Frameworks
21
Industry Best Practices
AI Integration
- Generate product backlog items and Agile documentation
- Support solution evaluation and KPI-driven business decision-making
Activities/Case Study
- Digital Transformation Discovery Project
1
Descriptive Analytics
2
Diagnostic Analytics
3
Forecasting Concepts
4
Correlation Analysis
5
Business Statistics
6
Probability Concepts
7
Hypothesis Testing
8
A/B Testing
9
Predictive Analytics Foundations
AI Integration
- AI-Powered Forecasting
- Automated Statistical Interpretation
- AI-Assisted Business Insights
Activities/Case Study
- Customer Trend Analysis
1
Introduction to LLMs
2
Prompt Engineering for Analysts
3
AI Research Workflows
4
AI-Powered Reporting
5
AI Dashboard Narratives
6
Chat-with-Data Systems
7
AI Agents Basics
8
Workflow Automation
9
Responsible AI
10
AI Hallucination Validation
11
ChatGPT
12
Claude
13
Copilot
AI Integration
- Build AI-powered business analysis assistants
- Automate reporting, documentation, and insight generation
Activities/Case Study
- AI-Powered Business Analytics Workflow
1
Conduct stakeholder and business needs analysis
2
Gather and validate business requirements
3
Create process maps and gap analyses
4
Develop user stories and product backlogs
5
Analyze business data and KPI performance
6
Build executive dashboards and reports
7
Support UAT and solution evaluation activities
8
Present business recommendations and transformation roadmaps
1
Participants operate within a simulated enterprise business analysis environment where multiple departments generate large volumes of operational, financial, customer, and performance data requiring continuous monitoring and decision support.
2
Working as Business Analysts, participants design automated reporting workflows using Excel, SQL, Power BI, Microsoft Fabric, and AI-enabled business analysis tools to streamline data collection, dashboard generation, KPI tracking, requirements documentation, and management reporting processes.
3
The sandbox environment enables participants to evaluate how automation can improve reporting accuracy, stakeholder visibility, and business decisionmaking effectiveness.
4
Participants leverage Generative AI, reporting automation techniques, analytics platforms, and business intelligence frameworks to automate requirement analysis, dashboard narratives, executive reporting, KPI interpretation, forecasting insights, and business documentation workflows.
5
Through practical experimentation and workflow optimization activities, participants build scalable automation solutions that support operational efficiency, data-driven decision-making, stakeholder communication, and enterprise transformation initiatives while maintaining governance, reporting quality, and business alignment
Learning Outcomes
By the end of this course, you will be able to:
1
Apply business analysis best practices to solve organizational challenges and improve business outcomes
2
Gather stakeholder requirements and convert them into clear, precise business specifications
3
Create executive dashboards that highlight KPIs and support performance tracking
4
Evaluate and improve business solutions using Agile methodologies, analytics, and performance metrics
5
Use Generative AI to streamline documentation, reporting, and analysis tasks
6
Support enterprise transformation through process optimisation and data-driven decision-making
Learners Point Certificate
Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.
KHDA Certificate
Earn a KHDA attested Course Certificate. The Knowledge and Human Development Authority (KHDA) is the educational quality assurance and regulatory authority of the Government of Dubai, United Arab Emirates.
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Frequently asked questions
This Business Analyst Course in Kuwait is ideal for participants seeking to develop practical skills in business analysis, stakeholder management, requirements engineering, and data-driven decision-making. It also suits professionals looking to strengthen their ability to support business improvement, reporting, and transformation with confidence.
It is relevant to participants seeking hands-on exposure to Excel, SQL, Power BI, Agile business analysis, and Generative AI. This course is designed for those aiming to apply modern tools and structured thinking in real business environments.
Participants in this course in Kuwait will gain a strong mix of business analysis, data, reporting, and AI-powered skills that help them work more effectively in modern business environments. It is designed to shift participants from core concepts to practical application through hands-on, career-relevant learning.
The following topics and subject areas are covered in this course:
- Modern analyst mindset, KPI thinking, and business problem-solving.
- Excel for data cleaning, formulas, pivot tables, and reporting automation.
- SQL for data extraction, filtering, joins, aggregations, and business reporting logic.
- Power BI for modelling, dashboards, executive analytics, and storytelling.
- Requirements engineering, stakeholder management, and process improvement.
- Agile business analysis, product ownership, predictive analytics, and Generative AI.
Yes, this training in Kuwait includes both SQL and Power BI for participants wanting practical, workplace-ready skills. This course covers SQL for business data extraction, filtering, joins, aggregations, and reporting logic.
It also includes Power BI for data modelling, dashboard development, executive reporting, dashboard storytelling, and enterprise deployment. Together, these tools help participants turn data into clear insights that support better business decisions.
This training helps participants in Kuwait build practical capability in business analysis, stakeholder communication, requirements engineering, and process improvement. It is designed to strengthen the skills needed to analyse business needs, support reporting, and contribute more confidently to day-to-day decision-making.
It also helps participants apply Excel, SQL, Power BI, Agile business analysis, and Generative AI in real work settings. With hands-on learning and applied exercises, the course supports improved performance, stronger business insight, and more effective contribution to transformation initiatives.
Yes, this course includes strong practical learning that helps participants apply concepts in real-world business settings and build confidence through guided, hands-on work. The training is designed to move beyond theory and reinforce skills through labs, simulations, and applied exercises.
The practical learnings included in this training are:
- PL-300 practice labs for hands-on Power BI learning, modelling, and reporting
- Dashboard development projects to build executive and KPI-based reporting skills
- Agile simulations to practice business analysis in delivery-focused scenarios
- Predictive analytics exercises to apply forecasting and data interpretation
- Case studies that reflect real business challenges and decision-making
- Automation sandbox activities to test Excel, SQL, Power BI, Microsoft Fabric, and Generative AI workflows
The Business Analyst Course in Kuwait is designed to support participants at different levels, including those who are building their foundation in business analysis, data analysis, and requirements engineering. This course begins with core concepts and progressively moves into more practical topics, making it accessible and structured.
While prior experience can be helpful, it is not essential for enrolment. Participants who are motivated to learn Excel, SQL, Power BI, Agile business analysis, and generative AI can benefit from this training as they develop job-relevant skills for modern business environments.
Simulations and the Automation Sandbox help participants apply what they learn in a safe and practical environment. They recreate real business situations so that participants can practice business analysis, dashboard development, reporting, and decision-making without the pressure of a live workplace setting.
The Automation sandbox is particularly useful for testing Excel, SQL, Power BI, Microsoft Fabric, and Generative AI workflows. It strengthens confidence, improves accuracy, and helps connect theory with real-world execution in a structured way.
Learners Point stands out as a leading institute because this training is built around practical capability. It focuses on helping participants develop job-relevant skills in a structured way that aligns with modern business needs.
Reasons why you should choose Learners Point for your Business Analyst training:
- Strong focus on business analysis, stakeholder management, and requirements engineering.
- Practical coverage of Excel, SQL, Power BI, Microsoft Fabric, and Generative AI.
- Hands-on learning through PL-300 practice labs, case studies, simulations, and an automation sandbox.
- Training aligned with Agile business analysis, product ownership, and solution evaluation.
- Emphasis on dashboard development, KPI reporting, and data-driven decision-making.
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