Ankur Desai is a Sr. Product Marketing Manager at MapR. He leads the go-to-market efforts for MapR Streams. Previously Ankur worked at SAP on product marketing of SAP HANA. Ankur holds an MBA from Dartmouth College, and a Bachelor of Engineering in Information Technology from University of Mumbai.
Oil and gas wells produce a huge amount of information. Sensors monitor things like temperature, pressure, fluid viscosity, the presence of foreign substances, and seismic activity. Sensors must be monitored in real time to optimize both performance and safety. A slight change in pressure underground may indicate a fracture that can jeopardize the whole well.
I was at the annual Hadoop Summit in San Jose last week. As usual, the MapR booth was buzzing with big data enthusiasts and experts alike. We showcased demos that spanned multiple topics including multi-cluster Hadoop monitoring using Grafana and Kibana (as part of our new Spyglass Initiative), IoT stream analysis using MapR Streams and Spark Streaming, and self-service big data analytics using Apache Drill.
This blog post provides an introduction to the components of a typical streaming architecture and options available at each stage. The three major components, Producers, a streaming system, and consumers. The enthusiasm over real-time processing is being met with a host of technologies. Learn about some of them...
What is predictive maintenance? If we can predict a part failure well in advance, we can schedule maintenance/repair work for the part as per our convenience, while continuing to operate the equipment to avoid unexpected downtime. This will help reduce large repair expenses, as the part will be repaired or replaced well before it fails
Can we agree at the outset that modern businesses rely heavily on data to make critical decisions, and the ability to make decisions in real time is very valuable? Good.
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