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Vision Reach Global
Database Management Systems

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.

Upcoming live online sessions

Live Online

Nov 2 – 13, 2026

$1,700

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Live Online

Nov 30 – Dec 11, 2026

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Live Online

Dec 28, 2026 – Jan 8, 2027

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Live Online

Jan 25 – Feb 5, 2027

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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

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.

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
FAQ

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.

Still have questions about Live Online Applied Data Engineering, Databases & ERP Data Training Course? Chat with an advisor·Visit the full FAQ

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What Our Clients Say

VRG brings strategic discipline to complex organizational challenges. Their approach is structured, data-driven, and outcome-focused.

Levis Wabwire

Levis Wabwire

Managing Director

They facilitated our strategy review, we improved departmental KPI alignment by 35% and reduced operational bottlenecks significantly.

David Oketch

David Oketch

Strategy Lead

Employee engagement scores increased following the leadership training program. The difference in accountability culture is evident.

Wendy Albright

Wendy Albright

Program Manager

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