Real-Time Data Processing: Five Use Cases You Should Know
Webinar Speaker: Fern Halper, TDWI VP Research, Senior Research Director for Advanced Analytics
Date: Thursday, March 9, 2023
Time: 9:00 a.m. PT, 12:00 p.m. ET
Organizations are leveraging higher volumes of diverse data in order to remain competitive and successful in a complex and ever-evolving environment. This includes real-time data and analytics.
TDWI research indicates real-time and streaming data are becoming more mainstream for numerous use cases. This data is increasingly dominated by machine-generated data, IoT data, or other streaming data types. Real-time data provides businesses with current information, allowing them to make informed decisions quickly to become more competitive. It can be used to drive top-line benefits by better understanding customer behavior and improving the customer experience. It can also help improve operational processes by monitoring systems and quickly identifying bottlenecks, problems, and other inefficiencies. Successful companies are also using machine learning models with real-time data for use cases such as recommendation engines or promotional activities. They are also making use of IoT analytics, e.g., for predicting if a machine part will fail or even orchestrating large groups of devices on a factory floor.
Although some “real-time” use cases can process data in minutes or seconds, others require millisecond range response time. In other words, there are use cases where extreme real-time data response is required. The challenge organizations have in dealing with extreme real-time data is that their architecture simply cannot scale to support high-volume/high-velocity, data-intensive workloads. It is not a matter of throwing hardware and stacks of software at the problem. Modern real-time platforms must be optimized for real-time data processing. This means that the platform is able to handle high-velocity data streams and perform complex analytics on that data in real time, with low latency.
Join this webinar to learn more about extreme real-time use cases and how modern data platforms can help. Topics include:
- Trends in real-time data
- Five categories of real-time data use cases
- Modern real-time data platforms
Head of Product Marketing
Volt Active Data
David Rolfe is Volt Active Data’s head of product marketing. He has 30 years of database industry experience, half of which has been in the telco industry. In prior roles he designed and built charging, policy, and mediation systems; managed a globally distributed team of DBAs; and oversaw the selection of technology to replace legacy RDBMS. David is also credited as the inventor of four separate patents in the area of real-time conflict resolution in distributed databases. David was Oracle’s sixth employee in Ireland and later went on to work at Sun, Pacific Bell, LeapFrog, and Openet/Amdocs.
Fern Halper, Ph.D.