Data Platform Automation
description.
Building and modernizing data platforms is a complex and continuously evolving challenge. Organizations must coordinate many interconnected activities, from source discovery, data modeling, ingestion, and transformation to pipeline development, testing, deployment, governance, documentation, and ongoing change management. As platforms grow and requirements evolve, traditional development approaches can become increasingly difficult to scale and maintain.
This learning lab explores how Data Platform Automation can simplify and accelerate the development, modernization, and management of modern data platforms. It examines different automation approaches and technologies, from developer-assisted and metadata-driven development to rule-driven and AI-enabled automation, and shows how they can be applied across the data platform.
To bring these concepts to life, the learning lab includes two practical demonstrations:
- dbt — demonstrating a code-centric approach to transformation automation, reusable components, testing, lineage, documentation, and CI/CD-driven development
- WhereScape — demonstrating model- and metadata-driven automation for designing, generating, deploying, and managing data warehouses, Data Vaults, lakehouses, and data products across modern data platforms
Through practical examples and demonstrations, participants will learn how different automation approaches can reduce repetitive engineering effort, accelerate development and delivery, improve consistency and quality, simplify change and modernization, and enable more scalable and efficient development and management of modern data platforms.
Why attend
Attendees will learn:
- The core concepts, principles, and benefits of Data Automation
- How data automation is evolving from traditional Data Warehouse Automation (DWA) towards broader automation of modern data platforms
- What can be automated across data modeling, data movement, transformation and pipelines, testing and data quality, and platform management
- How different automation approaches work, from developer-assisted and metadata-driven development to rule-driven and AI-enabled automation
- How automation can support the development and modernization of data warehouses, Data Vaults, lakehouses, and data products
- Different ways to implement automation using cloud-native capabilities, component-based frameworks, and dedicated Data Warehouse Automation platforms
- How technologies such as dbt and WhereScape automate different aspects of data platform development and management
- How automation can reduce repetitive engineering effort, accelerate delivery, improve consistency and quality, and simplify ongoing change
- Key considerations and best practices for selecting and adopting the right automation approach for your data platform
Who should attend
This learning lab is exclusively intended for data and analytics professionals working at end-user organizations. It is designed for:
- BI and analytics program and project managers
- Data warehouse and data platform architects
- Data integration architects, designers, and developers
- Data engineers and ETL/ELT developers
- Data warehouse operations, maintenance, and support personnel
- Cloud data platform teams and modernization leaders
- Enterprise and technology architects involved in data strategy and governance
Prerequisites
A basic understanding of data management, metadata, data warehousing, data cleansing, and data integration concepts is recommended.
instructor.
Frank Martens
dates & price.
Course
Delivery Method
Dates
Location
Price
Gravinninen van Nassauboulevard 81
4811 BN Breda, Netherlands
Gravinninen van Nassauboulevard 81
4811 BN Breda, Netherlands
pricing.
This learning lab is offered free of charge and is exclusively available to professionals working at end-user organizations in the previously listed roles. As the number of seats is limited, registration is restricted to a maximum of two attendees per company. All registrations will be reviewed and verified before confirmation is provided.
If attendance is no longer possible, cancellation is requested at least 48 hours in advance. A no-show fee of EUR 50 (excluding VAT) will apply to confirmed participants who do not attend and do not cancel in time. The proceeds will be donated to a charitable organization. This policy helps ensure that available seats can be offered to other interested participants.