Fivetran and BigQuery for automated fraud detection
Fivetran, a cloud-based automated data movement platform, lets organizations easily extract, load, and transform data from many sources and destinations.
To ingest and store the training data, pipelines across multiple, disparate sources (file systems, databases, third-party APIs) are established
Creating training sets from stored data and applying machine learning models to it in order to create predictive models that can distinguish between authentic and fraudulent transactions
Implementing and utilizing fraud detection solutions can take a lot longer when a data science team is assembled to build machine learning models and data pipelines
The company’s capacity to supply downstream data products with the most recent and accurate data was severely impeded by this delay
The data must be of the highest caliber, credible, transparent, and reliable, and it must also be unique to their use case
The company selected Fivetran primarily because of its ability to handle schema drift and evolution from multiple sources to their new cloud data platform in an automated and dependable manner
Beyond DB2, Fivetran showed that it could handle a broad range of data sources, including other databases and a number of SaaS applications