Enhanced ELT data pipeline for marketing analytics
Mettovaara, Jani (2026)
2026
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202604207050
https://urn.fi/URN:NBN:fi:amk-202604207050
Tiivistelmä
The increasing demand for reliable and customizable reporting on marketing data was the driving factor for this work. Clear and understandable reports are the visible product of the ELT-oriented data pipeline, and an efficient, automated pipeline frees up resources for data utilization.
The implemented and evaluated source scope in this thesis is LianaMailer data on GCP, while LianaAutomation, LianaPress, LianaMonitor, and Google website analytics and marketing data sources are treated as future integration extensions outside the evaluated implementation scope.
The legacy data flow, using Google Sheets and Google Apps Script, was found to be slow, unreliable and limited in scalability. This system faced challenges as data volumes increased. As the organization already operated within the Google ecosystem, moving the pipeline to Google Cloud Platform (GCP) was identified as the logical next step.
The initial research was conducted to compare the advantages of the existing implementation with the possibilities offered by GCP. The main objective was to determine if the pipeline could be built and maintained in GCP with reasonable resources, followed by the design and implementation of the solution. The specific benefits targeted were improved performance, reliability, ease of maintainability and enhanced scalability.
The implemented and evaluated source scope in this thesis is LianaMailer data on GCP, while LianaAutomation, LianaPress, LianaMonitor, and Google website analytics and marketing data sources are treated as future integration extensions outside the evaluated implementation scope.
The legacy data flow, using Google Sheets and Google Apps Script, was found to be slow, unreliable and limited in scalability. This system faced challenges as data volumes increased. As the organization already operated within the Google ecosystem, moving the pipeline to Google Cloud Platform (GCP) was identified as the logical next step.
The initial research was conducted to compare the advantages of the existing implementation with the possibilities offered by GCP. The main objective was to determine if the pipeline could be built and maintained in GCP with reasonable resources, followed by the design and implementation of the solution. The specific benefits targeted were improved performance, reliability, ease of maintainability and enhanced scalability.