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Description

Experience a seamless zero-touch copilot designed to enhance data quality, spending efficiency, performance metrics, and overall usage. Your data team will be promptly informed about any analytics failures or operational bottlenecks, ensuring no critical issues go unnoticed. We swiftly identify anomalies and notify you instantly, allowing you to maintain high data quality and prevent downtime. As performance metrics shift negatively, you will receive immediate alerts, enabling proactive measures. Our solution bridges the gap between data utilization and resource distribution, helping you to minimize costs and allocate resources effectively. We provide a detailed breakdown of your spending across various dimensions such as warehouse, user, and query, ensuring transparency and control. If spending patterns begin to deviate unfavorably, you'll be notified right away. Gain valuable insights into underutilized data and its implications for your business's value. Revel in the benefits of Revefi, which vigilantly monitors for waste and highlights opportunities to optimize usage against resources. With automated monitoring integrated into your data warehouse, manual data checks become a thing of the past. This allows you to identify root causes and resolve issues within minutes, preventing any adverse effects on your downstream users, thus enhancing overall operational efficiency. In this way, you can maintain a competitive edge by ensuring that your data-driven decisions are based on accurate and timely information.

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
Okta

Integrations

Cloudera
Jenkins
Okta

Pricing Details

$299 per month
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

Revefi

Country

United States

Website

www.revefi.com

Vendor Details

Company Name

iceDQ

Founded

2005

Country

United States

Website

icedq.com

Product Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

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

Alternatives

Alternatives

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