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September 07, 2017
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Top 5 Use Cases of HDF Streaming Analytics Manager

With the explosion of the Internet of Things (IoT), businesses need to reevaluate their existing data strategies and adopt a more modern data architecture.  Building a near-real time streaming application that take advantage of data-in-motion can be a daunting journey to undertake. Most streaming applications require a considerable amount of coding, testing and time to deploy. Scaling, reusability, and achieving operational agility are just some of the common pitfalls associated with existing software architectures.

With the introduction of Streaming Analytics Manager, part of Hortonworks DataFlow, application developers can easily build a streaming application without writing single line of code for event correlation, context enrichment, complex pattern matching, and more. And, alerts or notifications can be created when insights are discovered, so time is never wasted.

I want to highlight top 5 use cases for considering HDF Streaming Analytics Manager.

  1. Anomaly prevention – In many industries, detection of anomaly events and actions taken to correct them can still take a considerable amount of time. With Streaming Analytics Manager, one can easily build an application to detect if a truck driver had occurred multiple driving violations within a period of time to indicate fatigue or speed driving.
  2. Predictive Maintenance – In the case of manufacturers looking to minimize the risk of equipment failure, you need an application to analyze signals from manufacturing machines and IoT devices to help businesses  understand when they should perform maintenance and updates.
  3. Threat Monitoring – There are a few commercial applications in the market that fit into this category. Still, in many cases, companies need a custom built, real time examination of logs and traces from various systems. A real-time threat monitoring application built using Streaming Analytics Manager can ingest multiple sources of info beyond just system logs, perform events correlation and other necessary analysis and detect a possible attack in a matter of minutes.
  4. Recommendation Engines – Almost everyone has used Amazon or Netflix recommendation engines to find the next best services/goods to purchase and next hit shows to watch. Building a real-time recommendation engine with built-in analytics enables companies to provide the marketing team the exact information to deliver the right upsells/cross sells at just the right time.
  5. Real-time customer sentiment analysis – Social media can make corporations either heroic or infamous in a single day. With Streaming Analytics Manager along with the Flow Management functionalities within Hortonworks DataFlow , companies now can easily build an application that effortlessly collects real-time responses to new products and services to mitigate a major PR disaster or to discover major flaws of the products/services quickly.

To learn more about Streaming Analytics Manager, part of  Hortonworks DataFlow,  read our white paper here.

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