Data science is a constantly evolving discipline. The number of techniques and methods continues to increase at a rapid pace. Enormous amounts of data requires cutting edge technologies for reliable and secure storage and to enable faster accessibility and processing. Analyses are performed using multiple computers and multiple processing units, so-called high-performance computing environments. Cloud environments facilitate ‘virtual environments’. Virtual environments make it possible to assemble a multitude of different tools and data management structures with sufficient processing power to test their applications.
In a wide variety of data science projects we use big data infrastructures for storage and analysis, for example, supercomputers, Hadoop clusters, and Spark-Streaming, where complex analyses are not tied to the processing or storage capacity of a single work station.
Depending on the privacy sensitivity of the data from a certain project, we provide the required data security by facilitating reliable technical environments for transfer, storage, encryption and decryption, and processing of the data.