Low-Code Solutions Using to Automate the Bank of Russia Tabular Data Processing and Visualization

The article discusses the possibilities of using the low-code solutions to automate the Bank of Russia tabular data processing and its visualization characterizing the state of the banking sector and the credit market. The relevance of using the tools that allow to reduce the labour intensity with open statistical data, increase the analytical procedures reproducibility, and reduce the result dependence on manual operations is substantiated. An algorithm for automated data import and its primary processing using Power Query and built-in Excel tools, which includes the stages of loading, converting, aggregating, and visualizing the information is presented. It is shown that the proposed approach makes it possible to form a reproducible analytical outline for regular monitoring of indicators. The quantitative assessment confirmed the applied efficiency of automation: the labour intensity of a typical data processing cycle has been reduced from 45 to 7 minutes, which corresponds to savings of 84%. The conclusion is made about the prospects of the low-code approach as a tool for modern analytical work with official financial statistics.