Argyle Data vs Cask comparison

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Argyle Data Logo
33 views|13 comparisons
Cask Logo
83 views|74 comparisons
Executive Summary

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

Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop.
To learn more, read our detailed Hadoop Report (Updated: April 2024).
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Ranking
20th
out of 22 in Hadoop
Views
33
Comparisons
13
Reviews
0
Average Words per Review
0
Rating
N/A
14th
out of 22 in Hadoop
Views
83
Comparisons
74
Reviews
0
Average Words per Review
0
Rating
N/A
Buyer's Guide
Hadoop
April 2024
Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop. Updated: April 2024.
768,740 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



Cask Data Application Platform (CDAP) is the first Unified Platform for Big Data. It provides standardization and deep integrations with diverse Hadoop technologies allowing companies to focus on application logic and insights, rather than infrastructure and integration. The platform is 100% open-source, highly extensible, and delivers enterprise-class features to help accelerate time to build, deploy, and manage data-centric applications & data lakes on Hadoop and Spark.

There are 3 extensions packaged with CDAP: Cask Hydrator, Cask Wrangler and Cask Tracker. CDAP Extensions are self-service, purpose-built applications on CDAP designed to solve common and critical big data challenges. Cask Hydrator for data pipelines, Cask Wrangler for data wrangling and Cask Tracker for data discovery and metadata.

CDAP removes barriers to innovation as an extensible and future-proof platform that provides consistency across environments and easily integrates with existing MDM, BI, and security solutions.

Sample Customers
Cloudera, Gigamon, Hortonworks
AT&T, Salesforce, Cloudera, Hortonworks, Lotame, MAPR, Pet360, Ignition, Safeguard, Cloudwick, Kogentix
Buyer's Guide
Hadoop
April 2024
Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop. Updated: April 2024.
768,740 professionals have used our research since 2012.

Argyle Data is ranked 20th in Hadoop while Cask is ranked 14th in Hadoop. Argyle Data is rated 0.0, while Cask is rated 0.0. On the other hand, Argyle Data is most compared with , whereas Cask is most compared with .

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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.