At Mirai, data analytics is our bread-and-butter. Our interdisciplinary team of engineers and consultants combines state-of-the-art techniques and technologies from statistics and computer science to build high-end reactive analytic applications. Our experts employ techniques from classical statistics and advanced analytics such as predictive modeling and machine learning to turn your data into actionable insights.
We use widely adopted software packages for the implementation of analytics such as R, Python, Julia and MATLAB/Octave. To optimize runtime performance our experts will also implement core algorithms in C/C++ or utilize parallel computing and out-of-memory techniques, wherever appropriate. For large-scale distributed processing and big data tasks we further employ technologies such as Apache Spark, Scala/Akka and Hadoop.
In the machine learning domain we work with GPU-enabled frameworks like TensorFlow and PyTorch besides Spark MLlib and others.
Meaningful analytics always require sound data input — our people can help you to get your data into shape where this may not be the case yet. Similarly, actionable insights require clear and concise visualization — we will sit down with you to design reports and provide the degree of support you require to get them implemented.