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
What you will learn in this course:
Upcoming sessions
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
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
SQL Fundamentals
Filtering & Sorting
Joins
Aggregations
Subqueries
Common Table Expressions (CTEs)
Window Functions
Query Optimization
Business Data Extraction
Reporting Logic
Power BI Ecosystem
Data Import & Connectivity
Power Query
Data Transformation
Relationship Management
Data Modeling Basics
Star Schema Foundations
Data Modeling Best Practices
Star vs Snowflake Schema
Measures vs Calculated Columns
DAX Fundamentals
Time Intelligence
KPI Calculations
Context Transition
Advanced DAX
Performance Optimization
Dashboard Design Principles
Executive Reporting
KPI Storytelling
Drillthrough Features
Interactive Analytics
Mobile Dashboard Optimization
Smart Narratives
AI Visuals
Business Presentation Techniques
Power BI Service
Workspaces
Publishing Reports
Data Refresh
Row-Level Security
Collaboration Features
Governance Basics
Deployment Pipelines
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
Prepare Data
Model Data
Visualize Data
Analyze Data
Deploy & Maintain Assets
Python Fundamentals
Variables & Functions
Jupyter Notebooks
NumPy
Pandas
Data Wrangling
Data Cleaning
Exploratory Data Analysis (EDA)
Aggregation Techniques
Automation Scripts
Reporting Automation
Descriptive Analytics
Diagnostic Analytics
Forecasting Concepts
Correlation Analysis
Business Statistics
Probability Concepts
Hypothesis Testing
A/B Testing
Predictive Analytics Foundations
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
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.
After completing this program, participants will be able to:
1
Convert raw business data into clear, actionable insights
2
Build executive reports that highlight performance trends and recommendations
3
Assess data quality and improve the efficiency of analytical workflows
4
Streamline recurring reporting tasks to enable faster business decisions
5
Interpret statistical results and use forecasting techniques to assess future business performance
6
Enable enterprise decisions through responsible, AI-driven analytics solutions
Overall ratings by our students
The Data Analyst Course in Oman teaches participants to use Excel, SQL, Power BI, DAX, and Python to address practical business analytics requirements. Participants learn to clean messy datasets, build KPI-driven dashboards, and apply statistical methods to explain what the numbers actually mean for businesses.
Beyond technical tools, this course builds judgment skills such as reading business context, choosing the right analysis method, and presenting findings clearly to decision-makers. Participants also work with Generative AI for reporting support, reflecting how modern analytics teams actually operate in Oman.
Yes. The Data Analyst Training in Oman includes a dedicated Microsoft PL-300 Certification Alignment Track. It is designed to help participants build practical knowledge aligned with the certification’s core areas, including preparing, modelling, visualizing, analysing, deploying, and maintaining data assets.
Participants reinforce this preparation through a PL-300 dashboard lab, an enterprise reporting case study, and a mock certification-readiness assessment. This course also develops supporting capability in Power Query, DAX, data modelling, dashboard design, performance optimisation, and Power BI best practices.
This course builds hands-on skills across the core tools used in modern analytics roles, moving from spreadsheet basics through to enterprise reporting platforms.
Key tools and software covered include:
Yes, data analytics skills are in demand in Oman, particularly as organizations expand digital transformation and data-driven decision-making. According to current Indeed listings, data-related opportunities in Muscat and across Oman include operational, financial, engineering, and reporting roles that can require KPI, Excel, Power BI, analytical, and communication skills.
Demand also extends across finance, healthcare, telecommunications, HR analytics, and other sectors. Participants who develop practical skills in SQL, Power BI, Python, statistics, dashboards, automation, and AI-powered reporting can better align their capabilities with Oman’s evolving analytics requirements.
No, a technical background is not required to enrol in the Data Analytics Course in Oman. The course does not require prior coding experience or an IT degree, allowing professionals from different backgrounds to enrol.
This course introduces participants to analytics progressively through Excel, SQL, Power BI, Python, statistics, Microsoft Fabric, and Generative AI. This broad structure can support professionals from different business functions.
A Data Analyst typically works more on the data itself, cleaning datasets, running queries, and answering specific business questions as they come up. A Business Intelligence Analyst takes a broader view, building the dashboards and reporting systems that let an organization monitor performance continuously, rather than analysing one question at a time.
This course develops both skill sets rather than forcing an early choice. Participants build SQL querying ability for analyst-style work alongside Power BI dashboard design for BI-style reporting, giving them the flexibility to move into either role with confidence.
The Data Analyst Course in Oman comprises 85 hours of structured training delivered through modules that can be completed alongside a full-time role rather than as an intensive full-day program. Each module builds on the last, moving from Excel and SQL through to Power BI and Python, so professionals can apply new skills at work as they progress.
This course is designed for working professionals, and scheduling can typically be discussed based on individual availability.
Learners Point brings over two decades of regional training experience to this course, giving participants in Oman a genuinely practical, structured path into data analytics.
Reasons why Learners Point is chosen for this training:
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