Gartner Continuous Intelligence

Gartner Identifies Continuous Intelligence as a Top 10 Data and Analytics Technology Trend for 2019



Recently, Gartner identified Continuous Intelligence as one of the top 10 technology trends for data and analytics for 2019. The goal in publishing this list was to encourage data leaders to take a close look at the impact that these trends might have on their business, so they might consider adjusting their course of action and review operational initiatives in order to ensure that they are able to maintain a competitive edge.Gartner Continuous Intelligence diagram

Gartner defined “continuous intelligence” as “…a design pattern in which real-time analytics are integrated within a business operation, processing current and historical data to prescribe actions in response to events. It provides decision automation or decision support. Continuous intelligence leverages multiple technologies such as augmented analytics, event stream processing, optimization, business rule management and ML.”

Continuous intelligence enables companies to deliver better outcomes from a broad range of operational decisions since it involves more relevant, real-time data in decision-making algorithms. Individuals are able to make sense of extreme volumes of data in milliseconds, evaluating more alternatives in greater detail than humanly possible without access to real-time data and processing.

In fact, Gartner estimates that, within 3 years, more than 50% of all business initiatives will require continuous intelligence, leveraging streaming data to enhance real-time decision-making.

What makes continuous intelligence difficult is feeding a business’s analytics systems with high volumes of real-time streaming data in a way that is robust, secure, and yet highly consumable. The ability to combine “always-on,” streaming data ingestion and integration with real-time complex event processing, enrichment with rules and optimization logic, and streaming analytics is key to enabling continuous intelligence.Gartner Continuous Intelligence

The Striim Platform solves both sides of the continuous intelligence challenge. Striim enables continuous streaming data ingestion with linear scalability, in an enterprise-grade fashion. This includes ingestion from transactional databases via change data capture (CDC). While data is streaming, Striim enables stream processing, complex event processing, and enrichment of streaming data with reference data, rules, algorithms, and even machine learning models in milliseconds.

As a push-based continuous intelligence solution, Striim is able to deliver processed data to real-time custom dashboards, feeding real-time alerts, automated triggers, and reporting, while simultaneously loading data to a wide variety of cloud, storage, and messaging targets. Striim real-time data can further help enable prescriptive decision support.

To learn more about how Striim can support your continuous intelligence initiatives, please view our recent Striim Overview and Demo video, or schedule a demo tailored to your project with one of our lead technologists.

Read more from Gartner:

Striim Recognized in Gartner’s 2017 Market Guide for In-Memory Computing Technologies

Striim is honored to have been recognized in Gartner’s 2017 Market Guide for In-Memory Computing Technologies as providing solutions in the following areas:

  • Stream Analytics Platforms
  • High-Performance Message Infrastructure
  • In-Memory Data Grid
  • In-Memory Analytics and Real-Time Visualization

According to the report, the In-Memory Computing (IMC) market is projected to reach almost $15 billion by 2021, a dramatic increase from $6.8 billion in 2016. This growth is largely attributed to the many benefits enabled by IMC technologies including speed of processing, scalability, real-time insight, price performance for large volumes of data, and architectural simplification.

One of the key takeaways from the report is that,

“Gartner believes that the current separation between IMDG, IMDBMS, stream analytics and possibly other IMC technologies will increasingly blur during the next three to five years to give birth to a unified IMC platform, which will absorb most of the capabilities of these technologies.”

Striim combines multiple in-memory computing components in a single, converged in-memory computing architecture. In fact, Striim is listed in the report as providing solutions in four out of the five main categories of in-memory computing, enabling companies to immediately migrate toward a unified IMC arechitecture.

Stream Analytics Platforms
Striim is inherently an end-to-end Stream Analytics Platform that performs Distributed Stream Processing incorporating built-in message infrastructures and IMDGs. Striim can ingest, process, analyze, deliver, alert on and visualize high-speed streaming data. Striim performs all processing through SQL-based in-memory continuous queries capable of filtering, transforming, aggregating and enriching data, as well as complex event processing

High Performance Message Infrastructure
Striim includes both a network speed in-memory message infrastructure for streaming data between nodes, and a persistent message infrastructure backed by Kafka for reliable, rewindable messaging.

In-Memory Data Grid
Striim provides a Distributed In-Memory Data Grid for loading cached reference data from databases, files and other sources into memory for high-speed enrichment purposes. Striim utilizes a secondary IMDG for clustering, and distributing applications and run-time code around the cluster.

In-Memory Analytics and Real-Time Visualization
Striim enables back-end and front-end analytics through real-time query processing and interactive visualizations utilizing a distributed indexed results store and server-push technology.

The IMC market is poised for incredible growth, and Striim is looking forward to further integrating its in-memory capabilities to deliver on Gartner’s prediction of the rise of a unified IMC platform.

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