Featured Author

Ankur Desai
Sr. Product Marketing Manager, MapR

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.

Author's Posts

Posted on December 15, 2016 by Ankur Desai

In this week’s Whiteboard Walkthrough, Ankur Desai, Senior Product Marketing Manager at MapR, describes how Apache Kafka Connect and a REST API simplify and improve agility in working with streaming data from a variety of data sources including legacy database or data warehouse. He also explains the differences in this architecture when you use MapR Streams versus Kafka for data transport.

Posted on December 9, 2016 by Ankur Desai

In my previous blogpost, I explained the three major components of a streaming architecture. Most streaming architectures have three major components – producers, a streaming system, and consumers. Producers (such as Apache Flume) publish event data into a streaming system after collecting it from the data source, transforming it into the desired format, and optionally filtering, aggregating, and enriching it.

Posted on July 29, 2016 by Ankur Desai

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.

Posted on July 8, 2016 by Ankur Desai

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.

Posted on April 14, 2016 by Ankur Desai

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...

Posted on April 8, 2016 by Ankur Desai

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

Posted on March 28, 2016 by Ankur Desai

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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