MachineMetrics Blog

Top Causes of Machine Failure and How to Prevent Them

Machine failure, once an accepted part of life for manufacturers and OEMs, has met its match with modern technology using IoT devices, the cloud, and edge computing. In order to pre-empt and prevent
MachineMetrics / Jan 14, 2021

Communication Clears Machine Monitoring's Morale Hurdles

Originally published on Modern Machine Shop. When pen-and-paper methods of tracking job efficiency left AccuRounds’ engineers and managers in the dark, the shop switched to MachineMetrics. But
Machine Monitoring / Jan 07, 2021

What is an Edge Device and Why Is It Essential for IoT?

What is an Edge Device? Edge devices are pieces of equipment that serve to transmit data between the local network and the cloud. They are able to translate between the protocols, or languages, used
MachineMetrics / Jan 07, 2021

How OEE Software Improves Production Efficiency

Overall Equipment Effectiveness (OEE) is a methodology that has been around for many years.  It is a straightforward system that measures a machine’s performance and productivity.  By factoring in
MachineMetrics / Dec 30, 2021
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    Graham Immerman
    Graham Immerman Big Data / July 30, 2017

    5 Big Data terms and definitions

    Do you know what dirty data is? How about Hadoop User Experience (Hue)?

    When working with or around big data it helps to know the terms used to describe it. This list has 5 big data terms everyone should know about analytics and software relating to big data.

    Dirty data is, “Dirty data is data that is not clean or in other words inaccurate, duplicated and inconsistent data.” Not good. Hue is an interface for easier use of Apache Hadoop. MachineMetrics knows how to work with these terms and this data, so contact us to learn how it can work for your business.

    Recommended Read5 BIG DATA TERMS EVERYONE SHOULD KNOWSource: http://dataconomy.com

    This article is a continuation of my first article, 25 Big Data terms everyone should know. Since it got such an overwhelmingly positive response, I decided to add an extra 50 terms to the list.  Just to give you a quick recap, I covered the following terms in my first article: Algorithm, Analytics, Descriptive analytics, Prescriptive analytics, Predictive analytics, Batch processing, Cassandra, Cloud computing, Cluster computing, Dark Data, Data Lake, Data mining, Data Scientist, Distributed file system, ETL, Hadoop, In-memory computing, IOT, Machine learning, Mapreduce, NoSQL, R, Spark, Stream processing, Structured Vs. Unstructured Data. Read More
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