Data today is too distributed and too large to move it to where the processing is performed. Now, businesses must find ways to move the processing close to the data—and the closer, the better.

The offering runs on the distributed systems organizations have already deployed (or plan to) and schedules data processing jobs against the data right where it’s generated, be it on the cloud ...

The startup said today it has closed on the $20 million Series A funding round led by Astasia Myers from Felicis, with ...

When the COVID-19 pandemic accelerated in early 2020, people all over the globe were affected. In this disruption, organizations also scrambled for ways to monitor employee health, maintain compliance ...

Sujit Kumar, these innovative patterns, such as event sourcing, CDC, IMDGs, and advanced caching strategies, are essential ...

Existing distributed computing frameworks are failing to keep a lid on the growing computational, memory and even energy costs resulting from the constantly expanding volume Big Data for anything ...

Data Replication: HDFS, Hadoop’s distributed file system, automatically replicates data blocks across multiple nodes. This redundancy ensures that even if one or more nodes fail, the data ...

The course covers principles of distributed processing systems for big data, including distributed file systems (such as Hadoop); distributed computation models (such as MapReduce); resilient ...