Data Analyst Course in Saudi Arabia
12 immersive modules & professional capstone projects
Comprehensive Data Analytics & AI-Enhanced Reporting Program
85 hours of AI integration training
Copilot & Automation Sandbox for work efficiency
Flexible learning modes & easy payment options
4.85/54.85/5Overview
Our training will help professionals in the following ways:
- Covers Excel, SQL, Power BI, Python, and AI-powered analytics tools
- Spans structured modules covering end-to-end data analysis and reporting workflows
- Develops data extraction, transformation, statistical analysis, and predictive analytics skills
- Builds Power BI dashboards using DAX, data modelling, and reporting workflows
- Integrates Microsoft Copilot and Fabric for AI-assisted analytics and automation
- Enables automated reporting, predictive insights, and data-driven business decision-making
Upcoming sessions
Curriculum
Evolution of Data Analytics
Modern Analyst vs Traditional Analyst
AI-Powered Decision Intelligence
Data-Driven Business Culture
Understanding Business KPIs
Business Problem Solving Frameworks
Analytics Lifecycle
Introduction to AI in Analytics
Responsible AI Fundamentals
AI Integration
- Analyze business KPIs and performance drivers.
- Generate AI-assisted business insights and decision support.
Activities/Case Study
- Business Decision Simulation
Excel Interface & Modern Workflows
Data Cleaning Techniques
Data Validation
Advanced Formulas
XLOOKUP
INDEX-MATCH
IF Logic
PivotTables & PivotCharts
Power Query Basics
Dashboard Development
Business Reporting Automation
Generate formulas and reporting logic using AI.
Automate spreadsheet analysis and dashboard insights.
AI Integration
- Generate formulas and reporting logic using AI
- Automate spreadsheet analysis and dashboard insights
Activities/Case Study
- Business Decision Simulation
SQL Fundamentals
Filtering & Sorting
Joins
Aggregations
Subqueries
Common Table Expressions (CTEs)
Window Functions
Query Optimization
Business Data Extraction
Reporting Logic
AI Integration
- Convert business questions into SQL queries
- Optimize SQL performance and debugging workflows
Activities/Case Study
- Sales Intelligence Reporting
Power BI Ecosystem
Data Import & Connectivity
Power Query
Data Transformation
Relationship Management
Data Modeling Basics
Star Schema Foundations
AI Integration
- Analyze data quality and transformation opportunities
- Generate reporting insights from imported datasets
Activities/Case Study
- Data Cleaning Workflow
Data Modeling Best Practices
Star vs Snowflake Schema
Measures vs Calculated Columns
DAX Fundamentals
Time Intelligence
KPI Calculations
Context Transition
Advanced DAX
Performance Optimization
AI Integration
- Generate DAX measures and calculations
- Optimize data models and reporting performance
Activities/Case Study
- HR KPI Dashboard
Dashboard Design Principles
Executive Reporting
KPI Storytelling
Drillthrough Features
Interactive Analytics
Mobile Dashboard Optimization
Smart Narratives
AI Visuals
Business Presentation Techniques
AI Integration
- Generate executive narratives from dashboards
- Support storytelling and insight communication
Activities/Case Study
- Country-Level Performance Dashboard
Power BI Service
Workspaces
Publishing Reports
Data Refresh
Row-Level Security
Collaboration Features
Governance Basics
Deployment Pipelines
AI Integration
- Monitor dashboard usage and performance
- Support governance and deployment decisions
Activities/Case Study
- Secure Dashboard Sharing
Microsoft Fabric Overview
OneLake Concepts
Lakehouse Architecture
Fabric Dataflows
Semantic Models
Real-Time Analytics
Fabric + Power BI Integration
Enterprise Analytics Architecture
Data Governance Fundamentals
Azure Analytics Ecosystem
Snowflake Overview
Databricks Overview
BigQuery Overview
dbt Awareness
AI Integration
- Analyze enterprise data architecture requirements
- Support modern analytics platform design decisions
Activities/Case Study
- Enterprise Reporting Architecture Design
Prepare Data
Model Data
Visualize Data
Analyze Data
Deploy & Maintain Assets
AI Integration
- Analyze certification readiness and knowledge gaps
- Support DAX optimization and dashboard best practices
Activities/Case Study
- Enterprise Reporting Scenario
Python Fundamentals
Variables & Functions
Jupyter Notebooks
NumPy
Pandas
Data Wrangling
Data Cleaning
Exploratory Data Analysis (EDA)
Aggregation Techniques
Automation Scripts
Reporting Automation
AI Integration
- Generate Python scripts and automation workflows
- Support debugging and code optimization
Activities/Case Study
- Data Cleaning Pipeline
Descriptive Analytics
Diagnostic Analytics
Forecasting Concepts
Correlation Analysis
Business Statistics
Probability Concepts
Hypothesis Testing
A/B Testing
Predictive Analytics Foundations
Generate forecasts and predictive insights.
Interpret statistical results and business outcomes.
AI Integration
- Generate forecasts and predictive insights
- Interpret statistical results and business outcomes
Activities/Case Study
- Customer Trend Analysis
Introduction to LLMs
Prompt Engineering for Analysts
AI Research Workflows
AI-Powered Reporting
AI Dashboard Narratives
Chat-with-Data Systems
AI Agents Basics
Workflow Automation
Responsible AI
AI Hallucination Validation
AI Integration
- Build AI-powered reporting and analytics assistants
- Automate insight generation and business intelligence workflows
Activities/Case Study
- AI Insight Generator
Participants assume the role of a business analytics team responsible for supporting executive leadership across Finance, Sales, HR, Operations, Procurement, and Customer Experience functions.
Working within a complex enterprise environment, teams are required to collect, clean, transform, model, analyze, visualize, automate, and communicate business data to support strategic decision-making.
Leveraging Power BI, Microsoft Fabric, SQL, Python, Predictive Analytics, and Generative AI technologies, participants develop integrated analytics solutions that provide meaningful business insights, executive reporting capabilities, and decision intelligence across multiple functional areas.
Throughout the simulation, participants define enterprise KPI frameworks, transform large-scale datasets, build analytical models, develop executive dashboards, perform predictive forecasting, and automate reporting processes.
The exercise replicates real-world analytics operations where business leaders depend on accurate insights, forecasting capability, and data-driven recommendations to improve organizational performance, operational efficiency, and long-term strategic planning.
Participants operate within an enterprise analytics automation environment where organizations seek to reduce manual reporting effort, improve analytical efficiency, and accelerate decision-making through intelligent automation.
Using Python, SQL, Power BI, Microsoft Fabric, and Generative AI technologies, participants design and implement automated workflows capable of collecting, transforming, analyzing, and presenting business data while supporting real-time reporting, forecasting, and executive intelligence requirements.
The sandbox environment focuses on building scalable analytics automation ecosystems that integrate AI-assisted insight generation, predictive analytics models, automated dashboard refresh processes, KPI monitoring systems, and intelligent reporting assistants.
Participants develop practical experience in creating end-to-end automation solutions that improve reporting accuracy, enhance business visibility, streamline analytical operations, and support enterprise-wide decision intelligence initiatives.
Meet your Trainer
Our Trainers
Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.
We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.
Learning Outcomes
Successful completion of Data Analyst training will help professionals in Saudi Arabia in the following ways:
1
Apply advanced Excel functions and PivotTables to analyse business datasets
2
Write SQL queries to extract, transform, and manipulate structured business data
3
Build interactive Power BI dashboards using DAX measures and data modelling
4
Use Microsoft Copilot and Fabric for AI-assisted analytics and automated reporting
5
Perform statistical analysis, hypothesis testing, and A/B testing for business decisions
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.
Learners Point Certificate
Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.
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Frequently asked questions
A Data Analyst course is important in Saudi Arabia as organisations increasingly rely on data-driven decision-making, business intelligence, and AI-powered reporting.
With Vision 2030 accelerating digital transformation, companies are investing in analytics tools, structured data systems, and reporting frameworks.
This creates strong demand for professionals who can manage end-to-end data workflows, from data extraction and analysis to dashboard development and insight generation.
This course is designed for junior and mid-level professionals who want to build practical data analytics skills for business decision-making. It is ideal for professionals working in finance, operations, sales, marketing, HR, supply chain, healthcare, retail, and government sectors, as well as graduates and career switchers looking to gain hands-on experience in SQL, Python, Power BI, and AI-powered analytics.
Yes. The course includes AI-powered analytics using Microsoft Copilot and Microsoft Fabric. Participants learn how to automate reporting, generate insights, and enhance dashboards in Power BI using AI-assisted workflows. These capabilities are increasingly important in modern organisations that rely on real-time analytics and intelligent reporting systems.
Yes. Data analytics skills are in high demand across Saudi Arabia, especially in roles such as Data Analyst, Business Intelligence Analyst, and Reporting Analyst. This course prepares professionals with practical, job-ready skills in SQL, Power BI, Python, data modelling, and analytics workflows, which are commonly required by employers across industries.
Learners Point offers a structured, practical, and industry-focused training program. The course includes 60 hours of training, 12 modules, hands-on projects, expert-led sessions, AI integration, and career support, helping participants build job-ready skills for data analytics roles in Saudi Arabia.
No advanced coding knowledge is required. The course is designed to help beginners and working professionals build skills step by step, starting with fundamentals and progressing to tools like SQL and Python in a structured and practical manner.
Participants will gain hands-on experience with:
- Excel for data analysis and reporting
- SQL for data extraction and transformation
- Power BI for dashboards and business intelligence
- Python (Pandas, NumPy) for data analysis and automation
- Microsoft Copilot and Fabric for AI-powered analytics
Yes. The program includes industry-based simulations in every module, where participants work on real business scenarios such as:
- Automating data workflows using Python
- Building dashboards in Power BI
- Performing statistical and A/B analysis
- Generating insights using AI tools
The course concludes with a capstone project that integrates all tools into a complete analytics solution.
This course stands out due to its focus on:
- End-to-end analytics workflow training
- Integration of AI tools like Microsoft Copilot and Fabric
- Strong emphasis on practical business use cases and simulations
- Coverage of both technical tools and analytical thinking
This ensures participants are prepared not just to use tools, but to deliver business insights and data-driven decisions.
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