Datu noliktavas kvalitātes modelis
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Latvijas Universitāte
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lav
Abstract
Datu noliktavām ir plašs pielietojums, taču to galvenais uzdevums ir apkopot datus no vairākiem avotiem un sniegt biznesam noderīgu informāciju. Līdz ar to īpaši svarīga ir datu noliktavās pieejamo datu kvalitāte. Izstrādājot datu noliktavas sistēmas, bieži vien, izstrādātāji neņem vērā datu kvalitātes nozīmīgumu, kā arī nav pietiekami izstudētas labākās metodes, lai nodrošinātu datu kvalitāti. Maģistra darba gaitā tika analizēti dažādi risinājumi, kas ļauj kontrolēt datu kvalitāti datu noliktavās, izvērtēti to trūkumi un priekšrocības. Tiek analizēts jau konkrētā datu noliktavas sistēmā eksistējošs datu kvalitātes modelis. Empīriskajā daļā analizēts datu modeļa ietvars, kas ir elastīgs un viegli mērogojams dažādām datu noliktavas sistēmām. Maģistra darbā veikts ietvara izvērtējums un uzskaitīti galvenie izaicinājumi, ar ko lietotāji saskaras, strādājot ar datu kvalitātes sistēmu ikdienā. Maģistra darba tēma: Datu noliktavas kvalitātes modelis. Atslēgas vārdi: Datu noliktava, datu kvalitātes kontrole, ETL procesu kvalitāte, datu kvalitātes metrikas
Data warehouses have a broad application, but their main task is to collect data from multiple sources and provide useful information for business. The quality of data available in data warehouses is therefore particularly important. In development of data warehouse systems, developers often do not consider the importance of data quality and have not sufficiently researched best practices to ensure the quality of the data. During the master thesis, various solutions to control data quality in data warehouses were analysed to assess their shortcomings and benefits. Author analysed data quality model in already existing data warehouse system. In the empirical part was analysed a particular data quality framework that is flexible and easily scalable for different data warehouse systems. While working on master thesis author assess data quality framework and lists the main challenges faced by users in the day-to-day process of data quality system. Master thesis title: Data warehouse quality model. Keywords: Data warehouse, data quality control, ETL process quality, data quality metrics
Data warehouses have a broad application, but their main task is to collect data from multiple sources and provide useful information for business. The quality of data available in data warehouses is therefore particularly important. In development of data warehouse systems, developers often do not consider the importance of data quality and have not sufficiently researched best practices to ensure the quality of the data. During the master thesis, various solutions to control data quality in data warehouses were analysed to assess their shortcomings and benefits. Author analysed data quality model in already existing data warehouse system. In the empirical part was analysed a particular data quality framework that is flexible and easily scalable for different data warehouse systems. While working on master thesis author assess data quality framework and lists the main challenges faced by users in the day-to-day process of data quality system. Master thesis title: Data warehouse quality model. Keywords: Data warehouse, data quality control, ETL process quality, data quality metrics