In today’s digitally driven world, processing streaming data in real-time is a requirement for business success. The introduction of 5G networks will only increase the data volume and speed requirements that are already putting pressure on traditional data architectures.
There is a massive difference between generating the input data needed by a Machine Learning model once (to prove a concept), and doing it continuously, indefinitely, at scale, and within short time periods. Years of experience working with disparate and imperfect data sets lead me to suspect that people trying to move desktop scale ML […]
In my previous blog on big data analytics, we discussed how to apply your big data analytics to real-time applications. The idea is that, if you have built analytics on your data, the next step is to use the analytics directly in the applications to automate your business workflow and remove the manual components. In this […]
The world is speeding up; people expect customized information and services immediately. In these tumultuous times, some companies are clinging to their legacy data infrastructure as a security blanket. However, traditional RDBMSes are just not able to provide the massive scales, edge distribution, and virtual or cloud deployments that are necessary for modern applications. In […]