Use Case | Description |
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Fraud detection | Near real-time fraud detection models can be implemented using the Data Streams as a data source. Example: Determining whether a transaction is fraudulent while the transaction is still in progress and not after the fact. |
Personalization | Scoring models (finance), recommendations (e-commerce). Example: Instant recommendations using real-time mobile device data based on end user's location. |
Enterprise reporting/ BI | Data distribution to the the parent company and/ or various organizational stakeholders internally as well as real-time reporting and dashboard implementation. Example: Would like to enrich Mapp Intelligence Raw Data with my organizational data sources (CRM systems, etc.) and push it to my preferred BI solution. |
Spam/ Bot detection | Spam/ bot detection using streaming data. |
A/B Testing | High-frequency, self-service A/B testing. |
ETL Automation/ Reduction of repetitive ETL processes | The streaming raw data could be directly ingested into any internal stream, aggregated and/ or persisted to DWH, merged with other data, etc. without needing to go through batch processing, providing the customer flexibility and more options to work with. |
Streamlined implementations | Implementation and development efforts with less hassle such as hot deployment of data processing bug fixes, data science models, new pipelines, etc. |