The data kitchen of the RIVM: from testlocation to Covid-19 dashboard [Dutch spoken]

Martijn van Rooijen and Jeroen Alblas give a peek into the data kitchen of the RIVM. After the introduction of the SARS-CoV-2 virus in The Netherlands, the healthcare chain faced major challenges. For the development of the Covid-19 dashboard, it was important to extract data streams with high-quality data from the care chain. Data virtualisation played an important role in this.

Guidelines for Migrating Your Data Warehouse to the Cloud

Migrating a data warehouse to the cloud can be a daunting task because of its lifespan. De-risk a data warehouse migration project before you migrate anything is important according to Mike Ferguson. He looks at what is involved in migrating a data warehouse to a cloud environment and how a migration can cause changes to the data architecture.

Cloud Database Systems in-depth: how do they work and how do they compare? (Dutch spoken)

There are several well know vendors that offer cloud database systems, such as Amazon, Microsoft and Google. In recent year however we have seen some new entries by companies that specialize in cloud services, such as Snowflake and Databricks. Peter Boncz offers an in-depth technical review and comparison of the existing and new generation cloud database systems.

Customer insights from EWALS and AEGON and how they continuously innovate with data

At Qlik, we have made it our mission to help organizations accelerate business value through data. To lead in the digital age, where real-time decisions are critical, you need robust data pipelines to effectively access and analyse the latest and most accurate data. Qlik offers a data integration and analytics platform that continuously ingests all your data changes, automates data warehouses, manages data lakes to provide true data insight across your organization with world-class analytics.

Ten practical guidelines for modern data architectures (Dutch spoken)

Often, existing data architectures can no longer keep up with the current “speed of business change”. As a result, many organizations have decided that it is time for a new, future-proof data architecture. However, this is easier said than done. In this session, ten essential guidelines for designing modern data architectures are discussed. These guidelines are based on hands-on experiences with designing and implementing many new data architectures.