Apoyo Económico accelerates its risk analytics processes on Google Cloud
Apoyo Económico, a microloan company with more than 170 branches, ran critical analytical processes every month on large volumes of information in an on-premise relational database limited by licenses and disk. Amarello migrated and re-engineered those processes to BigQuery: the risk portfolio went from several days to a couple of hours, and analysts have a new universe of information.
- Client
- Apoyo Económico
- Sector
- Financial services
- Country
- Mexico
- Project
- Migration and re-engineering of risk analytics processes
- Technologies
- BigQuery · Data Studio · Google Sheets · Google Cloud
In numbers
- Days → hours
the risk portfolio process went from several days to a couple of hours
- Fewer licenses
reduction in database licensing costs
- Real time
dashboards with BigQuery, Data Studio and Google Sheets for the business areas
In short
Apoyo Económico is a financial sector company that provides microloans, with more than 170 branches nationwide. It needed to migrate relational databases based on licensing and optimize on-premise analytical processes to Google Cloud. The main advantages of adopting a cloud model were the reduction in licensing costs and very significant improvements in information processing time.
01 · The problem
Risk processes that took days on a licensed database
- 01
Critical monthly processes
Critical analytical processes that use large volumes of information run every month. Their function is to deliver, in the shortest possible time, the analysis the business requires.
- 02
The risk portfolio
The central requirement was to migrate the analytical process that produces the risk portfolio, which processes a large volume of historical information.
- 03
Limited by licenses and disk
Most of the process ran on an on-premise relational database, limited to licensed CPUs and hard disk space. Risk analysts needed the flexibility to run additional analyses on the entire available volume.
02 · How we solved it
Re-engineering to BigQuery as the enterprise data warehouse
- 1
Migration and re-engineering
Our team of Google Cloud certified data engineers migrated and re-engineered the analytical processes to BigQuery as the enterprise data warehouse, to cut processing time from several days to a couple of hours and give analysts a new universe of available information.
- 2
Real-time dashboards
BigQuery was connected to Data Studio and Google Sheets to generate dashboards efficiently and with real-time data, which made it much easier to deliver reports to the different business areas in a controlled and secure way.
03 · The benefit for the client
From days to hours, with lower costs and more information for the analysts
Time
- Processing went from several days to a couple of hours.
Cost
- Reduction in licensing costs.
Analysts and business areas
- Risk analysts have a new universe of information for additional processes.
- Reports delivered to the business areas in a controlled and secure way, with real-time data.
Related solutions
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