Live from #GartnerIO | Turning Data Streams Into Business Value at the Edge with Paul DeBeasi, Gartner Distinguished VP Analyst. Follow along for key #GartnerInsights ⬇️
Real-time edge stream analytics is the key to situational awareness and improved decision quality. #GartnerIO #IO
What are some common edge stream analytics use cases? 3 examples 🔽 #GartnerIO #IO
"Stream processing is not appropriate for every analytics problem. Work with key stakeholders to determine which use cases can benefit from real-time streaming data." #GartnerIO #IO
How does stream analytics differ from conventional analytics? #GartnerIO #IO
Conventional systems analyze data after it is stored; whereas Event Stream Processing (ESP) platforms analyze data-in-motion as it arrives, operating at the edge. #GartnerIO #IO
ESP platforms are appropriate for high-volume, low-latency event-drive applications. #GartnerIO #IO
"One size does not fit all. Use different streaming architectures and ESP technologies for different business problems." #GartnerIO
3⃣ ways to derive business value from stream analytics. First, connect tech KPIs to stakeholder value. #GartnerIO #IO
Next: Apply product management principles. #GartnerIO #IO
Finally: Empower user to compose analytics solutions. #GartnerIO #IO
Key Takeaway: "Push beyond technology KPIs. You must align with stakeholder value by applying product management principles and empowering the user." #GartnerIO #IO
I&O Technical Professionals: Use this action plan to turn data streams into business value at the edge. #GartnerIO #IO
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