Transform Your Career with Expert-Led Data Integration & BI Training

• Hands-on Power BI & Azure Data Factory Training
• Enterprise Data Warehouse Design
• Industry-Recognized Certification
• Expert Instructors with 15+ Years Experience
• 105 CPD Hours Recognition
• Flexible Blended Learning Format

What is Data Integration & Analytics?

Data Integration and Analytics is the practice of combining data from disparate sources into meaningful and valuable information for business decision-making. In today's data-driven world, organizations generate massive amounts of data from various systems, and the ability to integrate, transform, and analyze this data is crucial for competitive advantage.

Business Intelligence (BI) transforms raw data into actionable insights through reports, dashboards, and data visualizations. As companies increasingly rely on data to drive strategic decisions, the demand for skilled data integration and BI professionals continues to surge across all industries.

This comprehensive programme equips you with advanced competencies in data integration architecture, ETL processes, data warehouse design, and business intelligence tools. You'll learn to work with industry-leading platforms including Microsoft Power BI, Azure Data Factory, SQL Server Integration Services (SSIS), and more.

Our Data Integration & Analytics Professional Certification provides hands-on training using real-world scenarios. Through practical projects and assessments, you'll gain the skills needed to design data integration solutions, build compelling BI dashboards, and implement data governance frameworks in enterprise environments.

Key Modules Covered

• Module 1: Enterprise Data Integration Architecture (9 hours) - Data integration patterns and best practices, ETL process design, API integration strategies (REST, SOAP, GraphQL), real-time vs. batch integration approaches, data synchronization and replication techniques.
• Module 2: Business Intelligence Requirements Analysis (8 hours) - BI platform requirements gathering, dashboard and reporting requirements specification, KPI definition and metrics framework design, self-service analytics requirements, BI solution evaluation.
• Module 3: Data Warehouse & Analytics (8 hours) - Data warehouse dimensional modeling (star schema, snowflake), fact and dimension table design, slowly changing dimensions (SCD), data mart design, OLAP cube concepts and MDX querying.
• Module 4: Microsoft Power BI & Analytics Tools (8 hours) - Power BI architecture and components, DAX (Data Analysis Expressions), Power Query for data transformation, dashboard design best practices, row-level security and data governance.
• Module 5: Data Quality & Governance (5 hours) - Data quality dimensions, data profiling and quality assessment, master data management (MDM) principles, data lineage and metadata management, data governance frameworks.
• Module 6: Cloud Data Integration (4 hours) - Azure Data Factory pipeline design, AWS data integration services, cloud-based ETL and ELT patterns, hybrid cloud data integration strategies, cost optimization.

Technologies & Tools Covered

• Microsoft Power BI (Desktop, Service, Gateway)
• Azure Data Factory (ADF)
• SQL Server Integration Services (SSIS)
• Microsoft SQL Server & Azure SQL Database
• DAX (Data Analysis Expressions)
• Power Query M Language
• Tableau & Qlik Sense Concepts
• Python for Data Manipulation