Making the Case for a Small Data Observability Strategy
Small data observability can provide the real-time insights that matter, empowering companies to maximize the uptime of complex and growing infrastructure.
Topic: Analytics
How real-time data is used in business analytics, including predictive, descriptive, and prescriptive uses. Edge analytics is also explored.
Why SQL Will Remain the Data Scientist’s Best Friend
A dizzying range of tools and services has grown out of the need to speed up and scale data analytics. However, one skill that has often been overlooked is …
Real-time Analytics News for Week Ending September 3
In this week's real-time analytics news: Teradata announced a complete cloud analytics and data platform, now with next-generation, cloud-native deployment and …
How Hybrid Cloud Can Be Used For Analytics and Machine Learning
A hybrid cloud approach lets businesses essentially pick and choose the various aspects of their analytics and ML workloads that they want to keep on-premises …
Edge Computing Enters the Thin vs. Thick Debate
Despite the growth and variety in edge computing device availability, the path toward thin or thick edge isn’t exactly clear.
Quantum’s Disruptive Promise: Niche to Mainstream
To take quantum computing from its niche existence to the mainstream, we need to learn how to isolate quantum systems better from their environment and learn …
Faster Than Ted Lasso: Deep Real-Time Analysis Comes to European Football
The real-time data "provides a level of understanding commentators and fans could previously only speculate about, like the probability of making an attempted …
Real-time Analytics News for Week Ending August 27
In this week's real-time analytics news: The Linux Foundation and the World Bank released a free, online quantum computing training course to provide an …
Moving to the Cloud for Better Data Analytics and Business Insights
The benefits of moving data analytics to the cloud can disappear if businesses don’t have the necessary expertise to manage the cloud’s complexities. Here …
3 Considerations for Adding Real-Time ML to Applications
Data that is ready for machine learning will be observable, supported by real-time infrastructure, and primarily processed with streaming technologies.