Data Engineering

Dedimo is a collaboration of five mental healthcare initiatives. In order to continuously enhance the quality of their care, they organize internal processes more efficiently. Therefore, they use perceptions from the data that is internally available. Previously, they acquired the data themselves from different source systems with ad hoc scripts. They requested our help to make this process more robust, efficient and to further professionalise it. They asked us to facilitate the central storage of their data, located in a cloud data warehouse. The goal was to set up the data infrastructure within this environment, since they were already used to working with Google Cloud Platform (GCP).

At Royal HaskoningDHV, the number of requests from customers with Data Engineering issues continue to climb. The new department they have set up for this, is growing. So they asked us to temporarily offer their Data Engineering team more capacity. One of the issues we offered help with involved the Aa en Maas Water Authority.

The Designathon Works foundation organises Design Hackathons (Designathons) for children aged 8 to 12. The target? Teaching children from all over the world skills to become a 'changemaker'. They are challenged to design solutions for a better world, for example to combat climate change. From the Datahub, we helped Designathon Works fine-tune the impact measurements free of charge. We also made a first move towards automating data collection, analysis and visualisation.

FysioHolland is an umbrella organisation for physiotherapists in the Netherlands. A central service team relieves therapists of additional work, so that they can mainly focus on providing the best care. In addition to organic growth, FysioHolland is connecting new practices to the organisation. Each of these has its own systems, work processes and treatment codes. This has made FysioHolland's data management large and complex.

The Neuron provides a programmatic bidding platform to plan, buy and manage digital Out-Of-Home ads in real-time. They asked us to predict the number of expected impressions for digital advertising on billboards in a scalable and efficient way.

The outbreak of the corona pandemic in early 2020 has turned the world upside down. In addition to countless infections, hospitalisations and deaths, we also saw an outbreak of violence in many countries. Citizens took to the streets, sometimes violently, to protest against the measures taken, but domestic violence also increased in many places and fear and frustration played a role in racism.

Mimic is a start-up that wants to help parents achieve the best feeding experience for babies through the Mimic baby bottle. This bottle provides the most natural drinking experience possible. Thanks to the patented cup system, the Mimic bottle ensures a calm drinking pace and reduces the risk of colic.

In times of the coronavirus (COVID-19), a good overview of the patients in the scaled-up intensive care of the Utrecht medical centre is vital. Employees must be able to view patient characteristics, the most current lab readings and the course of patients' vital signs at a glance. In addition, up-to-date insight into the bed occupancy per department and the capacity of the nursing staff is required. We immediately got started to provide the necessary insights for UMC Utrecht. As a way of also contributing in these times of crisis, we offered our hours free of charge.

RNW Media is an NGO that focuses on countries where there is limited freedom of expression. The organisation tries to make an impact through online channels such as social media and websites. To measure that impact, RNW Media drew up a Theory of Change (a kind of KPI framework for NGOs).

Fietsvoordeelshop has seven physical stores and a webshop. It is one of the most successful bike shops at the moment. In the field of data, the bicycle shop mainly worked with Excel. This means that a lot was done manually, every week. Due to the growth of the organisation and the increasing number of processes, the Excel file became increasingly large and unclear. Fietsvoordeelshop asked us to demonstrate with a data pressure cooker of five days that data-driven work could be of added value.

Publisher Malmberg collects a lot of offline and online data. More and more educational institutions are using online licenses in addition to (or instead of) printed teaching materials. To properly make use of this, Malmberg uses monthly reports. The in-house data team compiles these as input for specific departments. Malmberg asked us to strengthen this team and make the internal processes around data more efficient.

A few years ago, the job title didn't even exist: Data Engineer. Nowadays, there is a high demand for Data Engineers. Almost every organisation consciously collects data, and the realisation that this must be done in a structured way is growing. If the data you collect is not well organised and correct, you cannot use it as input for making good decisions. Data Engineers build infrastructures that process data. Therefore, they are indispensable to organisations that want to collect and apply their data in a structured way.

Infrastructure as Code has proven itself as a reliable technique for setting up platforms in the cloud. However, it does require an additional investment of time from the developers involved. In which cases does the extra effort pay off? Find out in this article.

It is now clear to most companies: data-driven decisions by Data Science add concrete value to business operations. Whether your goal is to build better marketing campaigns, perform preventive maintenance on your machines or fight fraud more effectively, there are applications for Data Science in every industry.

For developing modern data applications, a Data Engineer is essential. But what does it actually mean to be a Data Engineer and what exactly do you do? Our colleague Oskar, Data Engineer at Digital Power, explains.

In June 2020, Sander became part of our team. Although he started in the middle of corona time, he soon noticed that he was greatly stimulated to make contact with his new colleagues. This largely came naturally as part of our onboarding program: "This matched perfectly to my needs: I started calling many colleagues myself to get acquainted! "Read how Sander designs his own training as a data engineer."