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Building Data Warehousing for Machine Learning and Client Scoring

Year: 2024

Type: article

Abstract: In modern business, data is a critical resource that can significantly increase the company's competitiveness. One of the key tasks associated with data is the creation of data warehouses that provide effective storage, processing and analysis of information. In particular, structured data warehouses play a critical role in the development of machine learning and customer scoring systems. In this article, we will look at the stages of building data warehouses, integrating them with machine learning systems, and the importance of structured data for customer scoring. At the end of the article, we will present a mini-project on implementing a data warehouse using SQL and PySpark, as well as an example of machine learning for customer scoring. Keywords: data warehouse, SQL and PySpark, customer scoring, data structuring, structured data warehouses.

Source: ETM Equipment Technologies Materials

DOI: 10.36962/etm23052024-10

Authors: Nazila Ragimova, Irada Seyidova Nazila Ragimova, Irada Seyidova, Jala Jamalova Jala Jamalova

Language: English

Topic: Big Data and Business Intelligence

Subfield: Management Information Systems

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: diamond

OpenAlex ID: W4404305650

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