Data Science and the Cloud

Cloud technologies provide data scientists with ideal environments in which to explore data processing and develop new machine-learning models.

We therefore help our customers to plan and subsequently onboard cloud projects, as well as to implement and operate data science projects in the cloud.
A cloud setup can streamline many otherwise lengthy processes. In order to apply data science to real-world conditions, models which have, in many cases, been created “under lab conditions” must be transferred to productive systems. Consistent use of the Infrastructure as Code (IaC) paradigm, however, allows reproducible system landscapes to be created. This enables data scientists working in test environments to design new models which are real-world-ready and easier to implement, right from the very outset.
Platform-as-a-service offerings from cloud providers enable faster development of new algorithms. They provide not only the necessary means of implementation, but also sufficient computing resources. Customised models, on the other hand, can be tailored even more accurately to the requirements of each case and are usually better than standard offerings.

Data science in the cloud

While there are many options available for implementing data science in the cloud, few of them are truly sustainable. We help our customers to find solutions for the long haul.
When an organisation decides to enter the cloud and the project begins, some customers still need to be made "cloud-ready". The effort and tasks involved in this can vary considerably, depending on how the company is structured and its aspirations. We are therefore happy to advise on the organisation and structuring of cloud systems from the very beginning and to carry out customised cloud onboarding. This approach facilitates the creation of sustainable products, makes subsequent development steps transparent in the long term, and enables continuous integration/deployment (CI/CD).

We support data scientists

Many companies already have their own data science expertise. To make working in the cloud as easy as possible for these companies, we take over the implementation of the cloud setup and work with them to develop a data science self-service kit. Having a jointly developed framework ensures that they can focus on their work without having to actively engage with the code.

Customised solutions

Each solution brings its own challenges. We offer cloud-based data science solutions tailored to the needs and goals of our customers.

Major vendors such as Google, Amazon, and Microsoft Azure offer products which provide easy setup and encourage faster results. These benefits, however, often come with a critical limitation: vendor lock-ins prevent smooth transitions from one system to another.

We can create cloud infrastructures which function independently of individual cloud providers. We would be delighted to help you find the best solution for your needs.

Development of Big Data and Data Science Solutions for ProSiebenSat.1

Development of Big Data and Data Science Solutions for ProSiebenSat.1

ProSiebenSat.1 is greatly interested in the specific contributions made by TV ads to the added value of the e-commerce company advertised. Exactly how many visitors visit the e-commerce website because they saw the TV ad? How much revenue is generated by those visitors proven to have come to the website from the TV ad? The challenge was that standard solutions for analysing web traffic cannot explain the correlation between TV ads broadcast (events outside the online world) and the online behaviours they trigger. For this reason, ProSiebenSat.1 decided to develop a customised big data solution to answer these questions. inovex implemented a data science project based on a Hadoop cluster for ProSiebenSat.1.

Read the 'Data Science for ProSiebenSat.1' Case Study

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Stefan Igel

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Stefan Igel

Leadership Team Data Management & Analytics