Operational Database use cases

You can use the CDP Operational Database service in online transaction processing (OLTP) use cases and other low-latency and high-throughput application use cases.

Customer 360
  • Address the far-reaching effects of the shift in consumer expectations by enabling a holistic view of your business and your customers, from all products, systems, devices, and interaction channels
  • Deliver a consistent, personalized, context specific, and relevant experience
  • Build churn prediction models to identify at-risk customers and proactively target them with retention programs
Content Depot
  • Ensure that all users can access data because of high concurrency and low latency
  • Build data-based applications that distribute custom, easy-to-digest information across your organization
Time-series
Include real-time data and analysis into decision points across your organization
Customer-facing applications
  • Enable serving analytics on mobile and web applications directly to end-customers
  • Use as a key-value store for applications
Operationalize model scoring and serving
  • Build and score models on operational data for prevention, optimization, prescription, and prediction
  • Increase conversion rate of cross-sell and upsell opportunities
  • Predict credit-worthiness and lifetime customer value
Fraud and threat management
Perform fraud model serving and detection
IoT - Operation and monetization
  • Leverage IoT to evolve or change your business model and operations for greater efficiencies
  • Provide an up-to-the-minute picture of the status of the fleet through real-time monitoring, alerting, and diagnosis
  • Deliver economic value by enabling new business models
  • Increase conversion rate of cross-sell and upsell opportunities
Operational excellence
  • Achieve operational excellence by reducing the total cost if ownership (TCO), improving efficiency, and eliminating threats
  • Decrease network downtime using predictive maintenance enabled by active collection and monitoring of network data
  • Optimize equipment performance and costs using real-time IoT analytics