Argyle Data vs Netezza Analytics comparison

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Executive Summary

We performed a comparison between Argyle Data and Netezza Analytics based on real PeerSpot user reviews.

Find out what your peers are saying about Cloudera, Apache, Amazon and others in Hadoop.
To learn more, read our detailed Hadoop Report (Updated: March 2024).
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Pricing and Cost Advice
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  • "Expensive to maintain compared to other solutions."
  • "For me, mainly, it reduces my costs. It's not only the appliance cost. There are also support costs and a maintenance costs. It does reduce the costs very drastically."
  • "The annual licensing fees are twenty-two percent of the product cost."
  • More Netezza Analytics Pricing and Cost Advice →

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    Top Answer:Here are some things to consider when migrating from Netezza to AWS Redshift A. Migrating your data from Netezza to Redshift may be done using methods such as: o Use a third-party tool to export… more »
    Ranking
    20th
    out of 22 in Hadoop
    Views
    32
    Comparisons
    13
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    11th
    out of 22 in Hadoop
    Views
    235
    Comparisons
    100
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    Buyer's Guide
    Hadoop
    March 2024
    Find out what your peers are saying about Cloudera, Apache, Amazon and others in Hadoop. Updated: March 2024.
    765,386 professionals have used our research since 2012.
    Comparisons
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    Overview

    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



    IBM Netezza Analytics is an embedded, purpose-built, advanced analytics platform that empowers analytic enterprises to meet and exceed their business demands. As features, it can predict with more accuracy, deliver predictions faster and respond rapidly to changes.
    Sample Customers
    Cloudera, Gigamon, Hortonworks
    A leading online advertising network
    Company Size
    No Data Available
    REVIEWERS
    Small Business25%
    Midsize Enterprise17%
    Large Enterprise58%
    Buyer's Guide
    Hadoop
    March 2024
    Find out what your peers are saying about Cloudera, Apache, Amazon and others in Hadoop. Updated: March 2024.
    765,386 professionals have used our research since 2012.

    Argyle Data is ranked 20th in Hadoop while Netezza Analytics is ranked 11th in Hadoop. Argyle Data is rated 0.0, while Netezza Analytics is rated 7.4. On the other hand, the top reviewer of Netezza Analytics writes "ARULES() function is the fastest implementation of the associations algorithm (a priori or tree) I have worked with". Argyle Data is most compared with , whereas Netezza Analytics is most compared with Spark SQL and HPE Ezmeral Data Fabric.

    See our list of best Hadoop vendors.

    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.