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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

SAS Data Quality allows you to tackle your data quality challenges directly where they reside, eliminating the need for data relocation. This approach enables you to operate more swiftly and effectively, all while ensuring that sensitive information remains protected through role-based security measures. Data quality is not a one-time task; it’s an ongoing journey. Our solution supports you throughout each phase, simplifying the processes of profiling, identifying issues, previewing data, and establishing repeatable practices to uphold a high standard of data integrity. With SAS, you gain access to an unparalleled depth and breadth of data quality expertise, built from our extensive experience in the field. We understand that determining data quality often involves scrutinizing seemingly incorrect information to validate its accuracy. Our tools include matching logic, profiling, and deduplication, empowering business users to modify and refine data independently, which alleviates pressure on IT resources. Additionally, our out-of-the-box functionalities eliminate the need for extensive coding, making data quality management more accessible. Ultimately, SAS Data Quality positions you to maintain superior data quality effortlessly and sustainably.

Description

iceDQ, a DataOps platform that allows monitoring and testing, is a DataOps platform. iceDQ is an agile rules engine that automates ETL Testing, Data Migration Testing and Big Data Testing. It increases productivity and reduces project timelines for testing data warehouses and ETL projects. Identify data problems in your Data Warehouse, Big Data, and Data Migration Projects. The iceDQ platform can transform your ETL or Data Warehouse Testing landscape. It automates it from end to end, allowing the user to focus on analyzing the issues and fixing them. The first edition of iceDQ was designed to validate and test any volume of data with our in-memory engine. It can perform complex validation using SQL and Groovy. It is optimized for Data Warehouse Testing. It scales based upon the number of cores on a server and is 5X faster that the standard edition.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Cloudera
Jenkins
SAS Data Loader for Hadoop
SAS MDM

Integrations

Cloudera
Jenkins
SAS Data Loader for Hadoop
SAS MDM

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$1000
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

SAS Institute

Founded

1976

Country

United States

Website

www.sas.com/en_us/software/data-quality.html

Vendor Details

Company Name

Torana

Founded

2008

Country

United States

Website

icedq.com

Product Features

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

Product Features

Automated Testing

Hierarchical View
Move & Copy
Parameterized Testing
Requirements-Based Testing
Security Testing
Supports Parallel Execution
Test Script Reviews
Unicode Compliance

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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