What is Stream Processing & Analytics?
The Stream Processing and Analytics capabilities within Cloudera DataFlow (CDF), powered by Apache Flink, help businesses democratize real-time streaming analytics across the organization. This also improves detection and response to critical events that deliver business outcomes. With the advent of IoT and other streaming sources, unbounded data streams and events are constantly flowing into the enterprise. CDF’s stream-processing capabilities help analyze them in real time, identify key event patterns, and escalate key alerts based on predictive insights and actionable intelligence.
By enabling key stakeholders with access to real-time data, business decisions are made much faster and create the right business impact. Organizations can enable their analysts with such access with just SQL and not depend on developers to accelerate streaming analytics.
Prevent millions of dollars in loss due to financial fraud by detecting it proactively.
Enterprises across retail, financial services, and other sectors struggle to protect customer data and prevent financial fraud from happening. Cloudera DataFlow’s Streaming Processing and Analytics capabilities can process real-time streams of customer transactions, identify patterns, create predictive alerts and actionable intelligence to prevent potential fraud.
Modernize your logging infrastructure to get real-time analytics.
Log data is increasingly valuable to enterprises. But IT organizations are struggling with effective log collection processes, distributing relevant information upstream, and generating key metrics. Cloudera DataFlow's Streaming Processing and Analytics capabilities help scale up log processing, deliver real-time insights across the firm, and significantly reduce operating costs.
Real-time customer analytics improves engagement, retention, and satisfaction.
Every organization needs real-time analytics to improve customer engagement but struggles to implement it due to an excessive volume of data. Cloudera DataFlow’s Stream Processing and Analytics enables customer analytics by processing massive amounts of data with subsecond latencies while detecting customer interactions and recommending better offerings in real time.