Compare Amazon EMR vs. Argyle Data

Amazon EMR is ranked 8th in Hadoop while Argyle Data is ranked 19th in Hadoop. Amazon EMR is rated 0, while Argyle Data is rated 0. On the other hand, Amazon EMR is most compared with Hortonworks Data Platform, Cloudera Distribution for Hadoop and Apache Spark, whereas Argyle Data is most compared with .
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Amazon EMR Logo
2,954 views|2,436 comparisons
Argyle Data Logo
60 views|27 comparisons
Ranking
8th
out of 24 in Hadoop
Views
2,954
Comparisons
2,436
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
19th
out of 24 in Hadoop
Views
60
Comparisons
27
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
Find out what your peers are saying about Apache, Cloudera, Hortonworks and others in Hadoop. Updated: November 2019.
378,570 professionals have used our research since 2012.
Top Comparisons
Compared 17% of the time.
Also Known As
Amazon Elastic MapReduce
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Argyle Data
Overview
Amazon Elastic MapReduce (Amazon EMR) is a web service that makes it easy to quickly and cost-effectively process vast amounts of data. Amazon EMR simplifies big data processing, providing a managed Hadoop framework that makes it easy, fast, and cost-effective for you to distribute and process vast amounts of your data across dynamically scalable Amazon EC2 instances.

Argyle Data has had the privilege of working with global leaders and visionaries on their strategies for revenue threat analytics, big data, and machine learning. What consistently comes up is that best-in-class carriers know the revenue threats that they have been attacked with in the past. What they don’t know is how to prepare for future attacks that will likely incorporate new types and methods of revenue threats.

What is critical to understand is that a) criminals are continually innovating; b) each subscriber will have many devices, many channels, and many potential attack points; and c) we need a better way to detect new fraud and protect customers and carriers in this new world – today in 2015, not in 2020.

This requires an effective strategy for the use of big data and machine learning in the areas of:

Fraud Threats

Analytics apps for identifying threats from various types of domestic fraud and roaming fraud

Profit Threats

Analytics apps for identifying threats from arbitrage, negative margin, high usage, and bill shock

SLA Threats

Analytics apps for identifying threats from network vulnerabilities and from roaming partners not meeting their SLA windows

Forensic Threats

Graph analysis application for analyzing 1st to 5th degrees of separation between data assets



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Learn more about Argyle Data
Sample Customers
YelpCloudera, Gigamon, Hortonworks
Find out what your peers are saying about Apache, Cloudera, Hortonworks and others in Hadoop. Updated: November 2019.
378,570 professionals have used our research since 2012.
We monitor all Hadoop reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
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