AMQP PREDICTIVE ANALYTICS REPORT

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ANALYSIS

What You Need to Know

  • Breakouts in the AMQP predictive analytics are RabbitMQ, MQTT, WSO2. Seriously consider these technologies to gain a strategic advantage.
  • The technologies who are at the peak of their interest are RabbitMQ, MQTT, WSO2.
  • By far most employment needs are found in the Managed services, Red Hat, Open-source software technologies.
  • These 3 fields have the most active practitioners who have the specific skill set or experience: Managed services, Red Hat, Cisco Systems.
  • Red Hat, HCL Technologies, RabbitMQ lead in searches for information online.
  • These three technologies are receiving the highest investments to gain clients: Managed services, Application layer, Digital Signature Services.
  • These three technologies have the most active advertisers: Managed services, Digital Signature Services, Message queuing service.
  • In patents, these three technologies have the most coverage Application layer, Red Hat, Cisco Systems.
  • The most publications are available for Open-source software, Red Hat, Application layer.
  • Instruction and courseware availability is highest in these technologies: Red Hat, Cisco Systems, Open-source software.

The AMQP report evaluates technologies and applications in terms of their business impact, adoption rate and maturity level to help users decide where and when to invest.

The Predictive Analytics Scores below – ordered on Forecasted Future Needs and Demand from High to Low – shows you AMQP’s Predictive Analysis. The link takes you to a corresponding product in The Art of Service’s store to get started.

The Art of Service’s predictive model results enable businesses to discover and apply the most profitable technologies and applications, attracting the most profitable customers, and therefore helping maximize value from their investments. The Predictive Analytics algorithm evaluates and scores technologies and applications.

The platform monitors over ten thousand technologies and applications for months, looking for interest swings in a topic, concept, technology or application, not just a count of mentions. It then makes forecasts about the velocity of the interest over time, with peaks representing it breaking into the mainstream. Data sources include trend data, employment data, employee skills data, and signals like advertising spent, advertisers, search-counts, Instruction and courseware available activity, patents, and books published.

Predictive Analytics Scores:

000441 – RabbitMQ
000250 – MQTT
000171 – WSO2
000148 – ActiveMQ
000111 – Apache Foundation
000075 – Java Message Service
000060 – Open standard
000051 – Apache ActiveMQ
000049 – Application layer
000047 – Managed services
000041 – Apache Qpid
000035 – Message queue
000012 – Erlang (programming language)
000008 – XDI
000008 – HCL Technologies
000008 – Cisco Systems
000004 – Software AG
000003 – Wire protocol
000002 – Progress Software
000000 – XACML
000000 – WS-Security
000000 – Transport Layer Security
000000 – Solace systems
000000 – Security Assertion Markup Language
000000 – Red Hat
000000 – Open-source software
000000 – OASIS TOSCA
000000 – Message queuing service
000000 – JORAM
000000 – Enterprise messaging system
000000 – Digital Signature Services
000000 – Digital object identifier
000000 – Binary protocol
000000 – Advanced Message Queuing Protocol


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