Data Engineering for Business Intelligence Course: Powering Analytics and Strategic Insights

Introduction

Business Intelligence (BI) has become the cornerstone of modern decision-making, enabling organizations to derive actionable insights from complex datasets. However, BI systems are only as powerful as the data pipelines, storage systems, and integration processes that power them. This course focuses on the critical role of data engineering in enabling effective BI solutions, equipping participants with the knowledge and skills to design, build, and manage robust data architectures that drive analytics and strategy.

The course begins by laying a foundation in data engineering principles, covering essential topics such as data modeling, ETL (Extract, Transform, Load) processes, data pipelines, and database optimization. Participants will gain hands-on experience with industry-leading BI-focused data engineering tools, ensuring they can handle real-world scenarios involving complex data sources and large-scale data flows.

As organizations increasingly adopt cloud-based platforms, the program emphasizes integration with cloud-native tools such as AWS Redshift, Google BigQuery, and Microsoft Azure Synapse Analytics. Learners will explore data lakehouses, hybrid environments, and emerging architectural models that support flexible, scalable, and cost-effective BI solutions.

Beyond technology, the course addresses governance, security, and compliance in BI-focused data engineering. This ensures that participants not only build scalable systems but also design environments that are secure, compliant, and aligned with enterprise policies.

By the end of the course, participants will be able to build and optimize enterprise-grade BI data architectures that fuel advanced analytics, dashboards, and data-driven decision-making, positioning themselves as strategic enablers in their organizations.

Who Should Attend

• Data engineers and architects seeking to support BI platforms.
• Business intelligence developers and professionals.
• Database administrators managing BI workloads.
• Data analysts looking to advance into engineering roles.
• IT professionals tasked with building analytics-ready data pipelines.
• Cloud engineers supporting enterprise BI systems.
• Consultants specializing in BI and analytics solutions.
• Project managers overseeing data and analytics projects.
• Business leaders aiming to align data engineering with BI strategy.
• Academic and research professionals building BI-driven systems.

Duration

5 days

Course Objectives

Upon completing this course, participants will be able to:

• Understand the role of data engineering in powering BI systems.
• Design robust data pipelines for analytics and reporting.
• Apply best practices in ETL design and workflow automation.
• Optimize databases for BI performance and scalability.
• Implement cloud-based BI architectures using Redshift, BigQuery, and Synapse.
• Integrate data lakes and warehouses for advanced analytics.
• Secure and govern BI data environments effectively.
• Enable real-time and near-real-time BI insights.
• Leverage BI-focused data engineering to support AI and predictive analytics.
• Stay ahead of trends in BI engineering, including lakehouses and Data Mesh.

Comprehensive Course Outline

Module 1: Introduction to Data Engineering for BI

• The relationship between data engineering and BI.
• Core BI concepts and analytics workflows.
• Key data challenges in BI environments.
• Overview of modern BI platforms and ecosystems.

Module 2: Data Modeling for BI

• Designing star and snowflake schemas.
• Dimensional modeling for analytics.
• Handling slowly changing dimensions.
• Best practices for BI data warehouse design.

Module 3: ETL and ELT Processes

• Fundamentals of ETL and ELT for BI.
• Workflow orchestration tools (Airflow, dbt).
• Data transformation for analytics-readiness.
• Automation and optimization strategies.

Module 4: Data Pipeline Design and Management

• Batch vs. streaming pipelines for BI.
• Pipeline monitoring, testing, and validation.
• Error handling and fault tolerance in pipelines.
• Best practices for pipeline scalability.

Module 5: Cloud-Native BI Architectures

• BI on AWS (Redshift, Glue, QuickSight).
• BI on Azure (Synapse, Data Factory, Power BI).
• BI on Google Cloud (BigQuery, Dataflow, Looker).
• Hybrid and multi-cloud BI integration.

Module 6: Data Warehousing and Lakehouse Approaches

• Data warehouses vs. data lakes vs. lakehouses.
• Designing BI-ready lakehouse architectures.
• BI workloads in Snowflake and Databricks.
• Case studies of enterprise implementations.

Module 7: Real-Time and Near-Real-Time BI

• Real-time streaming data for BI (Kafka, Spark).
• Real-time dashboards and monitoring.
• Incremental data loading strategies.
• Use cases in finance, retail, and operations.

Module 8: Governance, Security, and Compliance

• Data governance frameworks for BI.
• Role-based access control and identity management.
• Data lineage and metadata for BI trust.
• Compliance with GDPR, HIPAA, and other regulations.

Module 9: Enabling AI and Predictive BI

• Integrating BI with machine learning workflows.
• Feature engineering in BI pipelines.
• Predictive dashboards and advanced analytics.
• AI-driven insights for decision-making.

Module 10: Future Trends in BI Data Engineering

• Data Mesh and decentralized BI engineering.
• Serverless architectures for BI pipelines.
• The rise of augmented analytics.
• Preparing BI systems for continuous innovation.

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 requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, 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