Training Course on Business Intelligence and Data Warehousing for BI Developers

Course Outline

Module 1: Introduction to Business Intelligence and Data Warehousing

ü  What is Business Intelligence (BI)? Definition, components, and benefits

ü  The evolution of data management: from operational systems to analytical systems

ü  What is a Data Warehouse (DW)? Characteristics and purpose

ü  Differences between OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing)

ü  The BI lifecycle and typical roles in a BI project team

ü  Practical Session: Analyzing different business scenarios and identifying where BI solutions would add value.

Module 2: Data Warehousing Architectures and Methodologies

ü  Top-down (Inmon) vs. Bottom-up (Kimball) approaches to data warehousing

ü  The Corporate Information Factory (CIF) and Data Mart Bus Architecture

ü  Data Lakes vs. Data Warehouses: understanding the distinctions

ü  Cloud-based data warehousing solutions (e.g., Snowflake, BigQuery, Redshift)

ü  Hybrid data warehouse architectures

ü  Practical Session: Discussing design considerations for a data warehouse based on different architectural needs.

Module 3: Dimensional Modeling: Star Schema and Snowflake Schema

ü  Introduction to dimensional modeling: facts and dimensions

ü  Designing Star Schemas: fact tables, dimension tables, primary/foreign keys

ü  Designing Snowflake Schemas: normalization of dimensions

ü  Understanding different types of fact tables (transactional, snapshot, accumulating snapshot)

ü  Handling slowly changing dimensions (SCD Type 1, 2, 3)

ü  Practical Session: Designing a dimensional model (star schema) for a hypothetical sales dataset.

Module 4: Extract, Transform, Load (ETL) Processes and Tools

ü  The importance of the ETL process in data warehousing

ü  Key steps in ETL: Extraction, Transformation, Loading

ü  Data staging areas and their role

ü  Common ETL tools and technologies (e.g., SSIS, Informatica, Talend, Azure Data Factory, AWS Glue)

ü  Best practices for designing efficient and robust ETL pipelines

ü  Practical Session: Developing a basic ETL flow to extract data, perform a simple transformation, and load it into a target table using a chosen ETL tool (e.g., SSIS or a simple Python script).

Module 5: Data Quality, Governance, and Master Data Management

ü  The criticality of data quality in BI and DW

ü  Common data quality issues (e.g., inconsistencies, missing values, duplicates)

ü  Data cleansing techniques and tools

ü  Introduction to data governance: policies, roles, and responsibilities

ü  Master Data Management (MDM) concepts and strategies

ü  Practical Session: Identifying data quality issues in a sample dataset and proposing data cleansing rules.

Module 6: Business Intelligence Reporting and Visualization

ü  Principles of effective data visualization and reporting

ü  Types of BI reports: operational, analytical, strategic

ü  Introduction to popular BI reporting tools (e.g., Power BI, Tableau, Qlik Sense)

ü  Designing intuitive and user-friendly report layouts

ü  Incorporating interactive elements and drill-down capabilities

ü  Practical Session: Creating a simple report with charts and tables using a chosen BI tool (e.g., Power BI Desktop).

Module 7: Designing Effective Dashboards and Scorecards

ü  What is a dashboard? Purpose and characteristics

ü  Key considerations for dashboard design: audience, KPIs, simplicity

ü  Different types of dashboards (e.g., operational, strategic, analytical)

ü  Best practices for visual representation of data on dashboards

ü  Storytelling with data through dashboards

ü  Practical Session: Designing a dashboard layout for a business scenario, selecting appropriate visualizations for different KPIs.

Module 8: Introduction to OLAP and Data Mining Concepts

ü  OLAP cubes: concepts, benefits, and common operations (slice, dice, drill down, roll up, pivot)

ü  MOLAP, ROLAP, and HOLAP architectures

ü  Introduction to data mining: purpose and common techniques (e.g., classification, clustering, association)

ü  The relationship between BI, data warehousing, and data science

ü  Ethical considerations in data mining

ü  Practical Session: Exploring an existing OLAP cube (if available in the training environment) and performing basic OLAP operations.

Module 9: Data Warehouse Performance Tuning and Optimization

ü  Common performance bottlenecks in data warehouses

ü  Strategies for optimizing ETL performance (e.g., batch processing, parallel loading)

ü  Database indexing strategies for faster query performance

ü  Partitioning, aggregation, and materializing views

ü  Monitoring and troubleshooting data warehouse performance issues

ü  Practical Session: Analyzing a slow-performing data warehouse query and suggesting optimization techniques.

Module 10: BI Tool Selection, Implementation, and Future Trends

ü  Criteria for evaluating and selecting BI tools (e.g., features, scalability, cost, ease of use)

ü  Planning and managing BI and DW implementation projects

ü  The role of self-service BI and data literacy

ü  Emerging trends in BI: AI-driven insights, augmented analytics, real-time BI

ü  The future of the BI developer role

ü  Practical Session: Discussing the pros and cons of different BI tools based on a hypothetical business requirement.

About Our Trainers

The training will be delivered by a team of highly experienced Business Intelligence Architects, Data Warehouse Developers, and Data Engineers who have successfully designed, built, and optimized complex BI and DW solutions for various industries. Our trainers bring a wealth of practical strategies, hands-on experience with leading tools and technologies, and deep insights into transforming raw data into valuable business intelligence. Their expertise ensures that participants gain cutting-edge knowledge and actionable skills to excel in the field of BI development.

Quality Statement

We are committed to delivering high-quality, practical, and relevant training programs that empower professionals to excel in their roles and contribute significantly to the success of their organizations. Our courses are continually updated to reflect the latest industry trends, regulatory changes, and best practices.

Admission Criteria

ü  Participants should be reasonably proficient in English. 

ü  Applicants must live up to Phoenix Center for Policy, Research and Training admission criteria.

Terms and Conditions

1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free
2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.
3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.
4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.
5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@phoenixtrainingcenter.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.

Or call us on +254720272325 / +254737296202

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

1. Groups of 5 People and Above – Cheque Payments to: Phoenix Center for Policy, Research and Training Limited should be paid in advance, 5 days to the training.
2. Invoice: We can send a bill directly to you or your company.
3. Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.
2. Participants may cancel attendance 14 days or more prior to the training commencement date.
3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Tailor Made Courses

This training course can also be customized for your institution upon request for a minimum of 5 participants. You can have it conducted at our Training Centre or at a convenient location.

For further inquiries, please contact us on Tel: +254720272325 / +254737296202 or Email training@phoenixtrainingcenter.com

Accommodation and Airport Transfer

Accommodation and Airport Transfer is arranged upon request and at extra cost. For reservations contact the Training Officer on Email: training@phoenixtrainingcenter.com or on Tel: +254720272325 / +254737296202