home.
From Smart Homes to Smart Data Platforms
Smart homes have evolved from manual controls to increasingly intelligent automation. Data Automation follows a similar path, with distinct design levels ranging from manual implementation to AI-driven automation. Our Automation Design Levels describe the different architectural approaches along this journey.
Automate Your Snowflake Data Warehouse
Snowflake provides the platform. Data Warehouse Automation accelerates and automates data warehouse development. Together they create a metadata-driven data platform that dramatically reduces manual development while improving governance and consistency.
Process Mining
Totally Different From Business Intelligence And Yet So Identical. At first glance, BI and Process Mining could be twins – both thrive on data, both uncover performance insights, and both promise efficiency. And yet, despite their similarities, they approach the challenge from very different angles.
We are looking for data engineers and product owners to join our growing team in The Netherlands.
Senior Data Engineer
Do you believe traditional data warehouses should evolve into automated, scalable, and metadata-driven platforms? Are you passionate about modern data architectures - from cloud data ingestion and lakehouse platforms to data fabric and enterprise data catalogs? Join us in shaping the next generation of automated data platforms, leveraging cloud technologies, modern data architectures, and data automation frameworks.
Is Process Mining the Same as Business Intelligence?
At first glance, Business Intelligence (BI) and Process Mining may look similar. Both are used to analyze data within business management. Both rely on visualizations to simplify data analysis. And yet, despite their similarities, they approach the challenge from very different angles.
Modern Data Architecture
This course, taught by industry expert Mike Ferguson, explores how modern data architectures enable integrated analytics, data engineering, and AI at scale. It covers architectural approaches such as Lakehouse, Data Mesh, and Data Fabric, and provides practical guidance on designing, implementing, and evolving a future-ready data platform.
Core Competencies.
Our services span the key, interconnected disciplines of modern data and analytics.
Data Architecture & Engineering | |
Data Management & Governance | |
Data Analytics & Process Mining |
Free Learning Lab - Data Platform Automation
This complimentary half-day learning lab explores how Data Platform Automation and metadata-driven automation approaches help simplify and accelerate the design, development, modernization, and management of modern data platforms, including data warehouses, lakehouses, data pipelines, and other data platform components.
Data Automation
Traditional data management and warehouse initiatives have long been time-consuming and resource-intensive, burdened by manual processes, fragmented systems, and complex workflows. However, an automation-first approach transforms this landscape by applying advanced automation technologies, AI-driven orchestration, and intelligent process design to every stage of the data lifecycle.
WhereScape
Quest for Knowledge has been at the forefront of innovative data practices for more than two decades, working with thought leaders such as Ralph Kimball to bring proven methodologies to the Benelux and Sweden. Today, our partnership with WhereScape further strengthens our ability to deliver fast, reliable, and scalable data automation solutions.
Using Data Automation to Migrate Your Data Warehouse to the Cloud
Cloud-native data architectures are rapidly becoming the standard, but for many organizations, legacy data warehouses remain the bottleneck. Traditional migration approaches are often slow, brittle, and manually intensive - particularly when porting complex ETL jobs and schema logic. This is where Data Warehouse Automation (DWA) becomes a game-changer. If you're a data engineer tasked with modernizing infrastructure, here’s what you need to know about automating your DW migration.