Enterprises increasingly demand analytics that can keep pace with the real-time, rapid-fire nature of an IoT world. The Forrester Wave™: Streaming Analytics, Q3 2017 report cites SAS® Event Stream Processing as a Leader in this space. According to Forrester, “SAS Event Stream Processing is a relatively new offering, but with stellar low-latency analytics capabilities. In addition to the common […]
Enterprises increasingly demand analytics that can keep pace with the real-time, rapid-fire nature of an IoT world. The Forrester Wave™: Streaming Analytics, Q3 2017 report cites SAS® Event Stream Processing as a Leader in this space.
According to Forrester, “SAS Event Stream Processing is a relatively new offering, but with stellar low-latency analytics capabilities. In addition to the common streaming analytics features, SAS Event Stream Processing is integrated with many continuous machine learning algorithms. It is also the real-time backbone of numerous SAS business solutions including SAS Customer Intelligence, SAS Fraud Framework, SAS Decision Management, SAS Risk Management, SAS Asset Performance Analytics and others. SAS can continue to differentiate in streaming analytics by integrating its vast library of advanced analytics in Event Stream Processing.”
SAS Event Stream Processing quickly ingests and analyses millions of data events per second so a user can understand what’s happening while data is still moving. Adapters and connectors read incoming data, and a visual interface makes it easy for users to see patterns and take action.
To gain the most valuable insight, organisations must now regularly deal with a massive flood of fast-moving data” said Peter Pugh-Jones, Head of Technology at SAS UK & Ireland. “With so much data to consider it can be a real challenge to respond quickly once a pattern has been identified, resulting in missed opportunities and lost profit. This is why SAS Event Stream Processing matters. It enables users to analyse and respond to high velocity big data – from right out at the edge of IoT, all the way to scalable cloud platforms, capitalising on data-driven insight when and where it matters most.”
Enterprises increasingly demand analytics that can keep pace with the real-time, rapid-fire nature of an IoT world. The Forrester Wave™: Streaming Analytics, Q3 2017 report cites SAS® Event Stream Processing as a Leader in this space.
According to Forrester, “SAS Event Stream Processing is a relatively new offering, but with stellar low-latency analytics capabilities. In addition to the common streaming analytics features, SAS Event Stream Processing is integrated with many continuous machine learning algorithms. It is also the real-time backbone of numerous SAS business solutions including SAS Customer Intelligence, SAS Fraud Framework, SAS Decision Management, SAS Risk Management, SAS Asset Performance Analytics and others. SAS can continue to differentiate in streaming analytics by integrating its vast library of advanced analytics in Event Stream Processing.”
SAS Event Stream Processing quickly ingests and analyses millions of data events per second so a user can understand what’s happening while data is still moving. Adapters and connectors read incoming data, and a visual interface makes it easy for users to see patterns and take action.
To gain the most valuable insight, organisations must now regularly deal with a massive flood of fast-moving data” said Peter Pugh-Jones, Head of Technology at SAS UK & Ireland. “With so much data to consider it can be a real challenge to respond quickly once a pattern has been identified, resulting in missed opportunities and lost profit. This is why SAS Event Stream Processing matters. It enables users to analyse and respond to high velocity big data – from right out at the edge of IoT, all the way to scalable cloud platforms, capitalising on data-driven insight when and where it matters most.”
