When I worked at NASA, about a dozen years ago, NASA issued a request for concept papers describing potential new technologies
It doesn’t matter if it’s big data or small data, it’s always BIG for the user. Big data investments mean big expected ROI and big business value. This is why when customers are searching for a big data platform it’s important for them to ask the right questions.
The recent Skytree and MapR webinar ”Predictive Analytics with Machine Learning and Hadoop” proved to be highly interactive and engaging. As promised, Nitin and Jin have provided answers to
In this article we continue our interview with predictive analytics pioneer Colleen McCue.
Fireworks from the July 4th holiday seem like a distant memory, but the virtual fireworks continue to spark (pun intended) within the MapR partner ecosystem.
M.C. Srivas, CTO and Co-Founder of MapR Technologies, spoke recently at Spark Summit 2014 on “Why Spark on Hadoop Matters.” Spark, with an in-memory processing framework, provides a complimentary full stack on Hadoop, and this integration is showing tremendous promise for MapR customers.
The two topics Predictive Analytics and Big Data often appear together in discussions and blogs. This is not surprising when one considers that one of the great differences between traditional data warehousing and the new big data era is the outcome that each one has been tasked to produce. Databases and data warehousing have traditionally been used to provide a report (basically, descriptive analytics) about what has happened or what is happening.
The sign of maturity of most technologies is the appearance of standards. Standards are used to enable, to promote, to measure, and perhaps to govern the use of that technology across a wide spectrum of communities. Standardization increases independent use and comparative evaluations of the technology.