Live Online Applied Data Engineering, Databases & ERP Data Training Course
Live online, instructor-led · next cohort Nov 2, 2026 · from USD 1,700
Analytics, dashboards and automation are only as good as the data pipelines beneath them, and most organisations keep their most valuable records in ERP systems that are difficult to extract, clean and join. Over ten days, participants learn to design, load, move and query data reliably. The first week covers relational modelling, normalisation, entity relationship diagrams, SQL from basic queries to joins, window functions and stored procedures, indexing, transactions and performance tuning. Participants then explore how ERP platforms such as SAP, Oracle, Microsoft Dynamics and Odoo organise finance, procurement, inventory, sales and HR data.
The second week moves into engineering practice: extract, transform and load design, Python and SQL scripting, workflow orchestration, data validation, change data capture, dimensional modelling, star schemas, warehouse loading, ERP data migration and cutover, master data cleansing, API integration and reporting layers. Database administrators, developers, ERP analysts, business intelligence staff, systems auditors and finance or supply chain data owners will gain the most. Labs run on practice databases supplied during the sessions. Classroom delivery is available in 18 cities, plus online and in-house, with a CPD-accredited certificate. You can build a working pipeline from an ERP source to a reporting model.
At a Glance
How Live Online Training Works
Live online training, led by a trainer in real time, for participants anywhere.
More about live online training →- Format
- Live online, instructor-led
- Duration
- Mon - Fri (10 Days)
- Fee
- USD 1,700 (KES 160,000)
- Next start dates
- Nov 2, 2026, Nov 30, 2026, Dec 28, 2026
- Certificate
- Certificate of Completion
- What you need
- A computer with a reliable internet connection, a webcam and a headset
About this course
Enterprise systems generate vast volumes of transactions, but the information inside them is often locked in complicated schemas, duplicated across modules and inconsistent between departments. Meanwhile, businesses want timely reports, analytics and integration with new cloud tools. Professionals who can bridge databases, ERP structures and modern data engineering practice are therefore in steady demand across banks, manufacturers, public bodies and NGOs.
This ten-day programme gives participants a complete, practical route from database fundamentals to production-style pipelines. It begins with relational theory and SQL, since reliable engineering depends on fluent querying and sound design. The course then turns to ERP data: how core tables are organised, how master and transactional data differ, why migrations fail and how to plan extraction, mapping, cleansing and reconciliation. Data engineering practice follows, with ETL and ELT patterns, scripting, scheduling, logging, error handling, quality checks and documentation.
The closing sessions focus on analytical delivery. Participants design dimensional models and warehouses, load them from ERP extracts, expose results through reports, and consider security, backup, governance and monitoring. Each day is organised around lab exercises on supplied datasets, and the programme ends with an integrated project in which each team delivers a small end-to-end data platform.
Training Objectives
By the end of the course, participants will be able to:
- Design normalised relational schemas and document them with entity relationship diagrams.
- Write SQL queries using joins, subqueries, aggregation, window functions and views.
- Tune queries with indexes, execution plans and sound transaction handling.
- Describe how ERP modules store finance, procurement, inventory, sales and HR data.
- Plan and execute an ERP data extraction, mapping, cleansing and reconciliation exercise.
- Build ETL or ELT pipelines using SQL and Python with logging and error handling.
- Create dimensional models and star schemas and load them into a data warehouse.
- Apply data quality checks, security controls and API integration to data platforms.
What you'll learn
Key Takeaways
Participants complete the programme with:
- A normalised database design and a library of tested SQL queries.
- A migration plan and mapping template for moving ERP data.
- A working ETL pipeline with scheduling, logging and validation steps.
- A star schema warehouse loaded from ERP-style source data.
- A data quality checklist and reconciliation approach.
- A completed capstone project they can describe in their own portfolio.
Training Methodology
The programme is lab driven so that every concept is practised on working data:
- Short instructor demonstrations followed by guided hands-on labs
- Practice databases and ERP-style datasets supplied for each exercise
- Pair programming and peer code review during pipeline development
- Troubleshooting sessions built on realistic migration and load failures
- A final team capstone presented to the facilitators
Day 1: Data Platforms and Relational Foundations
- Roles in the data lifecycle: database, ERP, engineering and analytics
- Relational model, keys and integrity constraints
- Installing and navigating a practice database
- Retrieving data with SELECT, filters and sorting
- Data types, nulls and basic functions
- Lab: querying a sample business database
Day 2: Database Design and Normalisation
- Requirements gathering and conceptual modelling
- Entity relationship diagrams
- Normal forms and when to denormalise
- Creating tables, constraints and relationships with DDL
- Inserting, updating and deleting data safely
- Lab: designing a schema for an order-to-cash process
Day 3: Intermediate SQL for Analysis
- Inner, outer and self joins
- Grouping, aggregation and HAVING clauses
- Subqueries and common table expressions
- Views and reusable query logic
- Set operations and handling duplicates
- Lab: answering finance and inventory questions
Day 4: Advanced SQL, Performance and Transactions
- Window functions for ranking, running totals and comparisons
- Stored procedures, functions and triggers
- Indexes and execution plans
- Transactions, locking and isolation levels
- Backup, restore and basic security roles
- Lab: tuning slow queries
Day 5: Inside ERP Systems and Their Data
- ERP architecture and module integration
- Core structures in SAP, Oracle, Dynamics and Odoo
- Master data compared with transactional data
- Chart of accounts, material, vendor and customer records
- Extraction options: tables, reports, APIs and export tools
- Lab: exploring an ERP demonstration dataset
Day 6: ERP Data Migration and Cleansing
- Migration strategy: scope, sequence, trial loads and cutover
- Source-to-target mapping and transformation rules
- Profiling, de-duplication and standardisation of master data
- Reconciliation of balances and record counts
- Common causes of failed migrations and how to avoid them
- Lab: cleansing and loading customer and item data
Day 7: ETL and ELT Pipeline Engineering
- Batch and incremental load patterns
- Python and SQL scripting for extraction and transformation
- Working with files, APIs and databases as sources
- Logging, error handling and restart logic
- Scheduling and orchestration of workflows
- Lab: building a repeatable extraction pipeline
Day 8: Data Warehousing and Dimensional Modelling
- Warehouse architecture, staging and presentation layers
- Facts, dimensions and star schemas
- Slowly changing dimensions
- Change data capture and incremental warehouse loads
- Cloud warehouse and lakehouse options
- Lab: modelling and loading a sales and procurement mart
Day 9: Quality, Security and Integration
- Automated data quality tests and monitoring
- Data lineage, documentation and catalogues
- Access control, masking and protection of personal data
- API-based integration with ERP and external applications
- Supporting reporting tools and self-service analytics
- Lab: adding validation and alerting to a pipeline
Day 10: Capstone Project and Review
- Project brief: build an ERP-to-report data platform
- Team work on design, migration, pipeline and model
- Reconciling results against source reports
- Presentation of architecture and lessons learned
- Operational handover notes and support considerations
- Review and next steps for continued learning
The course is practical in focus and suits those who handle enterprise data, including:
- Database administrators and database developers
- ERP functional consultants and system analysts
- Data engineers and aspiring data engineers
- Business intelligence developers and report writers
- IT officers responsible for ERP support and migration projects
- Systems and IT auditors
- Finance, supply chain and HR data owners who extract ERP data
- Software developers integrating applications with enterprise systems
Participants who attend the ten days and complete the labs and capstone are granted a CPD-accredited Certificate of Completion by Vision Reach Global Consultancy.
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Frequently Asked Questions About Live Online Applied Data Engineering, Databases & ERP Data Training Course
Everything you need to know about this course before you register.
By the end of the Applied Data Engineering, Databases & ERP Data programme, you'll be able to design normalised relational schemas and document them with entity relationship diagrams, write sql queries using joins, subqueries, aggregation, window functions and views, tune queries with indexes, execution plans and sound transaction handling, and describe how erp modules store finance, procurement, inventory, sales and hr data. The full breakdown of topics is covered session by session in the Course Outline tab above.
The course is practical in focus and suits those who handle enterprise data, including: Database administrators and database developers, ERP functional consultants and system analysts, Data engineers and aspiring data engineers, Business intelligence developers and report writers, IT officers responsible for ERP support and migration projects, Systems and IT auditors, Finance, supply chain and HR data owners who extract ERP data, and Software developers integrating applications with enterprise systems.
Applied Data Engineering, Databases & ERP Data Training Course typically runs as 10 Days. It's available as in-person classroom, live virtual, and in-house corporate training — every course can also be delivered on-site for your team on dates that suit you.
Applied Data Engineering, Databases & ERP Data Training Course is scheduled in-classroom in Nairobi, Kenya, Mombasa, Kenya, Naivasha, Kenya, and Kisumu, Kenya, and 14 other locations, plus a live interactive virtual classroom you can join from anywhere. Check the schedule panel above for exact upcoming dates and fees in each location.
The next live virtual cohort of Applied Data Engineering, Databases & ERP Data starts November 2, 2026, with new classroom cohorts also running on a rolling basis. Pick a date and location in the schedule panel above, then click "Register for the Course" — it takes a few minutes and your seat is confirmed once payment or a signed purchase order is received.
Yes — delegates who meet the attendance requirement receive a Certificate of Completion for Applied Data Engineering, Databases & ERP Data Training Course from Vision Reach Global Consultancy, issued in the name you register with, so double-check the spelling at checkout.
Applied Data Engineering, Databases & ERP Data Training Course is pitched at intermediate professionals. If you're unsure whether it's the right fit for your current role or background, message our training advisors before you register and they'll help you confirm.
Fees for Applied Data Engineering, Databases & ERP Data Training Course vary by delivery location and format and are shown in real time in the schedule panel above once you pick a date. Register 3 or more delegates on the same course together and a 5% team discount is applied automatically — larger cohorts can request a custom corporate quote.
Yes — Applied Data Engineering, Databases & ERP Data Training Course can be delivered on-site at your offices (or virtually for distributed teams), with case studies and examples tailored to your industry and the specific challenges your team is working through. Switch to the "In-House" tab in the schedule panel above to request a proposal.
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