Marketing Personalization · Real-time Analytics
SIDIS needed a data platform that could unify structured and unstructured data from hundreds of sources, support hybrid cloud and on-premises deployments for regulated customers, and keep pace with transaction growth from 1 million daily events across 20 sources to 80 million daily events across more than 500 sources.
Reported impact
SIDIS enabled a major Latin American bank to access 180 data sources, build more than 1,200 indicators, send up to 30 million personalized emails per month, and turn reports that once took days into real-time insight delivered in seconds.
SIDIS uses MongoDB as the core data platform behind a universal data management service that ingests and enriches structured and unstructured enterprise data for banks, retailers, and other large clients. The company runs a hybrid model with MongoDB Atlas for cloud deployments and MongoDB Advanced Enterprise for on-premises environments where regulation requires data to stay in country or inside customer infrastructure. Data from hundreds of sources and legacy banking systems is centralized in MongoDB, where SIDIS cross-references it with statistical models, AI-enhanced metrics, and generative AI explanations before exposing results to dashboards, campaigns, and operational users. MongoDB's flexible document model lets SIDIS adapt schemas for each client without major rework, and elastic scaling handles sharp end-of-month transaction spikes while supporting mixed topologies across SIDIS cloud, customer cloud, and on-prem estates.
Structured and unstructured data from legacy banking systems and hundreds of other sources is centralized in MongoDB, enriched with statistical and AI-generated indicators, and then delivered to reporting, campaign, and decision-support workflows in real time across cloud and on-prem deployments.
"MongoDB enabled us to implement that hybrid structure very quickly while ensuring data security and encryption."
"The bank can now send up to 30 million personalized emails each month to its customer base."
"We were managing around 1 million daily transactions from just 20 sources, compared to 80 million daily transactions from over 500 sources now."
"With SIDIS and MongoDB, the bank can now access and utilize 180 different data sources and has developed more than 1,200 indicators."
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Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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