Speaker
Description
The talk focuses on the general steps of the data processing cycle and its implementation in a firm that operates in the fintech industry. While statisticians often discuss the actual processing of data - such as making the best possible models and thoroughly verifying that the results satisfy the necessary conditions - this work discusses the various steps that teams in companies have to complete that are essential for the data processing cycle to bear fruit, i.e. so that the client receives their desired outcome. In the first part, 4 basic steps of the cycle are outlined - data collection, preprocessing, processing and output. The second part of the talk focuses on the processing of data in terms of the continuous integration cycle - from the detailed description of the issue on a "ticket" through development and testing all the way to the successful deployment of the fix in production. Examples from firms in the industry are shown to better illustrate the discussed concepts.
