Top Challenges of Using Real-Time Data
Given the unique challenges of working with real-time data, organizations need to consider which tools will help them deploy and manage AI and ML models in the …
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.
Report: 80% of Real-Time Data Businesses See Revenue Jump
The report also claims there’s a potential to squeeze out an additional $2.6 trillion in revenue if more companies made the switch to
Real-time Analytics News for Week Ending June 18
In this week's real-time analytics news: Snowflake's conference proved to be a gold mine for new products and services from the company, its partners, and …
Real-time Data and Database Design: Why You Should Sweat the Small Stuff
Picking the right database when there are so many available should not just be a case of using whatever was easy for your last project.
Optimizing Video Compression Becomes a Reality
As internet traffic continues to grow, a suitable method for ensuring videos do not choke the network will be a requirement. Deepmind’s computer program …
Why Integration Is Essential for Modern, Real-time Applications
Integration is the only way to ensure that your real-time data is being used at the right time, in the right context, to help people make better
How to Use the AsyncAPI Standard for Real-Time APIs
Adopting AsyncAPI or other real-time API standards will be highly valuable to ensure apps can handle real-world events and drive digital
Parallel Processing 2.0: Round Two, Ready Fight!
Vectorized CPUs have been gestating for decades. Now they are emerging as the innovator’s choice as they use parallel CPU instructions when working on a …
ScaleOut Brings Real-Time Capabilities to Azure Digital Twins
Adding real-time analytics unlocks new use cases for Azure Digital Twins that go beyond modeling infrastructures to enable tracking live, mission-critical …
