MachineMetrics is Honored in Built In...

Boston, MA, January 13, 2020 — MachineMetrics today announced it was included on Built In Boston’s list of Best Places to Work in 2020. "It is such an honor to be recognized as one of Built In
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MachineMetrics named 2020 Smart...

Northampton, MA, January 4th, 2020 – MachineMetrics, a leading data analytics platform for manufacturers, announced today that it has been selected as winner of the 2020 “Smart Manufacturing Company
MachineMetrics / Jan 13, 2020

A New Hope for Manufacturing's Platform...

The Industrial Internet of Things (IoT) space is hot right now, as manufacturing represents perhaps the largest greenfield opportunity left for digitization. Yet, IoT platform implementations have
MachineMetrics / Jan 06, 2020
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    5 Big Data terms and definitions

    Graham Immerman
    Graham Immerman Big Data / July 30, 2017

    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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