Streaming Analytics: Operationalizing Business Insights

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Streaming Analytics: Operationalizing Business Insights

Get value from streaming analytics by operationalizing and acting on them.

· Big Data Zone ·
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I had the opportunity hear Stephen Archut, Senior Product Marketing Manager, Analytics, and  Lou Bajuk, Sr. Director, Product Management, Advanced Analytics at TIBCO during TIBCO NOW in Chicago provide an introduction to TIBCO Streaming, the real-time streaming analytics platform for applying mathematical and relational processing to real-time data streams. They shared how algorithm-driven businesses are finding insights, operationalizing, and acting on them to maximize their impact on revenue. 

Forrester found that 74% of businesses want to be data-driven; however, only 29% are good at connecting analytics to action.

Gartner found that more than 60% of models are developed with the intention of operationalizing them were never operationalized.

Algorithm-driven businesses are the new leaders. They're experiencing 30% year-to-year growth, outpacing global GDP by 8X, and took more than $1.8 trillion in revenue from others in 2018.

Augment traditional analytics with more data, faster ingestion, and analysis, new expectations, while reducing costs. Do this with real-time analytics on streaming data from apps, social media, sensors, devices, websites, and more. The growth is being driven by the desire for digital transformation and industrial IoT.

Benefits include:

  • Data is analyzed and processed in real-time.
  • Decisions are based on fresh data.
  • Decision latency is eliminated.

This results in:

  • Superior CX.

  • Operational excellence.

  • Instant awareness and timely decisions.

  • Ability to take advantage of insights.

TIBCO Streaming enables customers to build streaming analytics apps with ease and speed, injecting predictive models in the stream of data, automating decisions, actions, and alerts

Time to market is significantly reduced. Open source/custom coding takes months or years if you ever get to market. TIBCO Streaming with Studio takes days or weeks, while TIBCO Spotfire Data Streams provides self-service solutions in seconds.

Connectivity is achieved with Kafka, MQTT, EMS, and JMS. Access via Continuous Query architecture writes SQL-like queries to access data. Achieve real-time visualizations within the Spotfire environment by looking at real-time and historical data.

Operationalize insights in TIBCO Spotfire and TIBCO Data Science. Apply insights in streaming data, automatically and see if you are trending in the right direction with yield analysis.

The platform is up 24x7x365 with continuous availability, on-demand scalability, cloud-ready, and rolling upgrades for speed, performance, and scalability. It's built for ultra-low latency to coincide with the necessary use case: algorithmic trading <1ms, fraud detection 0ms, upsell cross-sell in e-commerce 50ms, and predictive maintenance in 5 seconds.

Strategic direction for the next 6 to 18 months includes streaming applications on TIBCO Cloud, domain-specific TIBCO Connected Intelligence Solutions, expansion anywhere, everywhere, cloud-native authoring for citizen developers, accelerators for high-value applications to empower customers and partners (e.g., connected vehicles, financial trading, high-tech manufacturing, Apache Spark, insurance pricing, financial fraud detection, business activity monitoring, and risk management). As well as an active and engaged community.

The platform empowers several different user personas:

  • Developers – build complex, real-time solutions.
  • Data Science Teams – operationalize insights.
  • IT and Cloud-Ops – designed for global, elastic deployment, DevOps.
  • Business analysts – build analytic dashboards on (live) data, set alerts.
  • Data Engineer – provides access to real-time data.
  • Citizen Developer is a new focus enabling them to visually compose streaming applications by composing high-level rules.

TIBCO has numerous use cases across several verticals

  • Capital markets – algorithmic trading.
  • Government – smart cities.
  • Energy – predictive maintenance.
  • Healthcare – patient flow monitoring.
  • Retail – omnichannel execution.
  • Manufacturing – asset-based monitoring.
  • Logistics - production optimization.
  • Telecommunications – customer experience.


  • Tailored UX – designed to empower diverse analytics users to contribute and collaborate.
  • Best-in-class interoperable – tight integration allows assembly into solutions that fit needs now and in the future.
  • Open and independent.

Key takeaways:

  • Leverage streaming analytics to connect business insights to actions/decisions.
  • It’s not as hard as you think.
big data ,data streaming ,real-time analytics ,real-time streaming ,streaming analytics

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