What You Need to Know
- Breakouts in the Cloud Testing predictive analytics are Logikcull, New Relic, Service virtualization. Seriously consider these technologies to gain a strategic advantage.
- The technologies who are at the peak of their interest are Zoom Cloud Meetings, Service virtualization, Email on Acid.
- By far most employment needs are found in the Distributed Systems, Software testing, Functional testing technologies.
- These 3 fields have the most active practitioners who have the specific skill set or experience: Software testing, Distributed Systems, Functional testing.
- Rackspace, New Relic, Software testing lead in searches for information online.
- These three technologies are receiving the highest investments to gain clients: Service virtualization, Load balancer, Load testing.
- These three technologies have the most active advertisers: Software testing, Automated Testing Software, AB Testing Software.
- In patents, these three technologies have the most coverage Distributed Systems, Performance test (assessment), Parallel computing.
- The most publications are available for Distributed Systems, Service Level Agreement, Software testing.
- Instruction and courseware availability is highest in these technologies: Software testing, Microsoft Azure, Stress testing.
The Cloud Testing 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 Cloud Testing’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:
000739 – Logikcull
000679 – New Relic
000410 – Service virtualization
000378 – Microsoft Azure
000282 – SOASTA
000255 – Rackspace
000232 – Email on Acid
000157 – BlazeMeter
000081 – Stress testing
000076 – Functional testing
000075 – Load testing
000075 – HP LoadRunner
000066 – Load Impact
000055 – Visual Website Optimizer
000040 – Software testing
000035 – SOAtest
000031 – Vendor Cloud
000028 – Service Level Agreement
000022 – SOASTA CloudTest
000014 – Cloud CMS
000008 – Parallel computing
000000 – Zoom Cloud Meetings
000000 – VetCloud
000000 – SyncApps
000000 – SupportDesk
000000 – Skillmeter
000000 – Servant Keeper
000000 – retailcloud
000000 – Performance test (assessment)
000000 – Neotys
000000 – Load balancer
000000 – ITRP
000000 – HireSelect
000000 – Firewall (computing)
000000 – Earth Class Mail
000000 – Distributed Systems
000000 – Commerce Sciences
000000 – brainCloud
000000 – Automated Testing Software
000000 – aKite
000000 – AB Testing Software