Handle With Care: The Data in Data Science
AI and ML applications need unified quality data from multiple silos and diverse formats that multiple workgroups can easily and securely
AI and ML applications need unified quality data from multiple silos and diverse formats that multiple workgroups can easily and securely
Lack of automation and data security challenges are impeding the flow of enterprise information, known as the data supply
The challenges of integrating time-series data into data lakes can be overcome by using the right architecture and providing the appropriate metadata.
With many deployment options, it’s easy to undermine the inherent EDA security benefits by deploying onto a substandard
Managed event services can help companies make faster and more efficient use of events and speed the adoption of event-driven architectures.
We're living in a data-driven world. All the more reason for companies to hire data scientists to work on a variety of
The Open Grid Alliance, a new industry initiative, seeks to bring the resources of grid to bear on edge computing
As we emerge from the pandemic, organizations that examine how they are using information will outperform their industry peers.
With open banking, developers can integrate financial data from multiple institutions within the same application or share financial data between applications …
Today's Neo4j funding announcement is the latest in what has been a banner year for huge industry investments in all things related to real-time