Data Preparation Techniques And Platforms In The Context Of Machine Learning

As data is becoming crucial for the efficient functioning of any organization, properly preparing it for processing is also getting increasingly important. This article presents an outline of different data preparation techniques, which can be defined in the context of machine learning. Overview of the techniques in combination of algorithms and their specific requirements for the data they can work with can server as basis of the interesting research task of finding automated solutions that not only enable the use of software solutions, but also build complete solutions that support the detection of the potential of the data and application of these techniques that can be automatically identified. Automating data preparation might be one of the steps which ensures that the machine learning process becomes quicker and more accessible. Using data preparation tools is a way to ensure more reliable and accurate data. This article aims to create an overview of existing data preparation tools and platforms. Different aspects of these platforms are considered, including data source compatibility, the data preparation techniques it includes, possibilities for integration, data security etc.