Industry Solutions

In the era of omni-channel retail, consumers are creating more data than ever before. For a retailer, real-time streaming data across the business can help drive insights into customer behaviors and improve business outcomes.

• Sentiment analysis: Understand customer sentiment in the moment
• Personalized promotions: Up to the moment promotions taking into consideration time, location, context, etc. for the optimal customer experience
• Inventory management: Monitor inventory flows to ensure optimal supply and deliver of product across channels

Related links:

• Walmart: Real-time Messaging at Walmart
• Target: Simplifying Omni-Channel Retail at Scale
• Zalando: Real-Time Document Rankings with Kafka Streams
• Stitch Fix: Managing Data at Scale - The Unreasonable Effectiveness of Events
• Etsy: Streaming Data Applications on Docker
• Shopify: Shopify Flash-Sales and Apache Kafka

Explore real-time data is a must have to financial services firms. With an up to the moment view of all activity they can better meet regulatory constraints, combat fraud, and remain competitive in a rapidly changing landscape.

• Market risk: Aggregate data across sources for real-time view of potential exposures
• Fraud detection: Detect potential laundering, payments fraud and respond in real-time to effectively minimize exposure/impact
• Capital management: Optimize capital planning and allocation leveraging data across multiple disparate sources

Related links:

• Goldman Sachs: Real-Time Analytics Visualized with Kafka + Streamliner + MemSQL + ZoomData
• Goldman Sachs: Kafka in the Enterprise: What if it Fails?
• Funding Circle: Building Stateful Financial Applications with Kafka Streams

Retail banking is as competitive as ever. The ability to be one step ahead of your customer, deliver the products they want, and detect potential bad actors is critical to survival. Real-time streams gives you a complete view of the customer across all channels.

• Personalized promotions: Up to the moment promotions taking into consideration time, location, context, etc. for the optimal customer experience
• Credit risk: Discovery and assess risk profiles, minimize risk exposure across all financial products
• Fraud detection: Anomaly detection to identify potential fraudulent activity and meet regulatory requirements

Related links:

• Capital One: Commander - Decoupled, Immutable REST APIs with Kafka Streams
• Rabobank: Real-time Financial Alerts at Rabobank with Apache Kafka’s Streams API
• WePay: Database Streaming At WePay With Kafka and Debezium

The connected car market is expected to reach $46.69B by 2020. At the same time, a ground swell of data will be generated as more and more connected vehicles hit the road, creating unique opportunities for auto manufacturer if they are able to capitalize on data in real-time.

• Connected car: Stream connected car data into central store for real-time monitoring and/or downstream analytics
• Personalized promotions: Up to the moment promotions taking into consideration time, location, context, etc. for the optimal customer experience

Related links:

• Uber: Stream Processing with Kafka in Uber

By streaming data from an unlimited number of sources, healthcare providers can give patients more choices for care and doctors more insight to better predict patient outcomes.

• Connected health: Support precision medicine initiatives by connecting all parts of the patient experience
• Improved care: Connect data across all touch points for complete view of patient
• Proactive patient care: Move care beyond the physical experience, providing proactive outreach as warranted

Related links:

• Cerner: Ingesting complex healthcare data with Apache Kafka at Cerner

By integrating streaming data into business operations, manufacturers streamline operations, deliver higher quality, more relevant products, and reduce waste. Real-time streaming data enables manufacturers to modernize existing processes and streamline costs.

• Supply optimization/inventory management: Real-time insight into supply chain to meet up to the moment demand requirements
• Streamlined product development/introduction: Monitor ongoing product development processes/cycles, lower shut-downs and maximize asset utilization
• Quality assurance: Detect product quality issues as/before they occur via real-time streams of product data