CashMe Builds Complex Data Analytics with Microsoft Dynamics, Snowflake and PowerBI

CashMe is a fast-growing fintech company in the home equity loans vertical. The company focuses on excellent customer service and technological innovations and has a loan portfolio of a quarter of billion dollars aiming to become a unicorn in the next few years.



Data Integration


Before 2021 the CashMe company did not have a data analytics team, their transactional data was handled in a CSV format. The company’s data environment was quite simple in terms of data volume, but complex in terms of diversity: marketing teams used various platforms for their tasks (Google Analytics, Google Search Console, MoZ, Aha, Facebook, company’s web portal, NPS score platform, etc.) and billing team used Microsoft Dynamics for operating the transactional data (credit analysis, properties, evaluation, legal details, and contracts).

When I first talked with our marketing director, he said "In order to get simple KPIs for the market chain, we spent three days from Monday to Wednesday, just to get data from all those platforms. And another two days, Thursday to create the KPIs and Friday to analyze and repeat over and over every week." So I said, "Okay, give me a month".

Caio Azevedo

Chief Data Officer


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.

Caio Azevedo

Chief Data Officer

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.

Caio Azevedo

Chief Data Officer


As a result, in three weeks CashMe web analysts managed to automate the data collection from numerous platforms:

Everything is automated nowadays, some of the data is updated not once per week, but more than once per day. It's amazing. Thanks to Skyvia!

Caio Azevedo

Chief Data Officer

Skyvia allowed CashMe to finalize the change management process from manual and semi-manual processes to a full and ultimate automation. And now CashMe can take business-driven decisions based on real-time Power BI dashboards and move several times faster.

As a bonus, Skyvia allowed CashMe to save 10 times more money compared to Supermetrics previously used for integrating data from marketing data sources.

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