When in 2021 a strategic web analytics team was hired, their challenge was to create a data analytics pipeline based upon the data warehouse as a repository, Microsoft Dynamics as a source of operational data, and Power BI to create the dashboards and reports. The dashboards were aimed to depict the internal analytics including operational data and KPIs, and partners’ data for the reporting purposes.
In the long-term perspective, the web analytics team planned to create their own machine learning analytics platform, a data warehouse and a data mart.
At first their data was stored in a PostgreSQL database, which was later synced with Snowflake using Skyvia. CashMe analysts spent some time testing both platforms to make sure the data integration pipelines work smoothly and moved them to Snowflake afterwards.
The Snowflake was chosen because of several reasons. The first one is the market volume.
We believe that property guarantee credit can be ten times bigger than we have nowadays in Brazil, so the CashMe analytics team expects the exponential growth of data.
Second reason was Snowflake’s independence from the “big three” Cloud environments (AWS, Azure and Google). And final reasons were Snowflake’s ease of use, flexibility and low cost compared to the competitors.
The data pipeline needed to be automated, so CashMe analysts started to look for a solution. CashMe analysts compared all major data integration solutions by three criteria: their G2Crowd rating, subscription cost and the compliance with technical requirements. They run a series of tests on Skyvia, Talend, Pentaho, Matillion and decided to go with the first one:
The key point why we chose Skyvia was its native Microsoft Dynamics support as well as Snowflake support, overwhelmingly simple interface, reliability and low cost. It took us three weeks total to set Skyvia’s data pipelines up and running.