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Description
Data Ladder is a company focused on enhancing data quality and cleansing, committed to assisting clients in maximizing their data through services like data matching, profiling, deduplication, and enrichment. Our goal is to maintain simplicity and clarity in our product offerings, ensuring exceptional solutions and customer service at a competitive price for our clients. Our products serve a wide range of users, including those in the Fortune 500, and we take pride in our ability to effectively listen to our clients, which enables us to swiftly enhance our offerings. Our intuitive and robust software empowers business professionals across various sectors to manage their data more efficiently and positively impact their financial performance. Our flagship data quality software, DataMatch Enterprise, has demonstrated its capability to identify approximately 12% to 300% more matches compared to leading competitors such as IBM and SAS in 15 separate studies. With over a decade of research and development to our name, we are continuously refining our data quality solutions. This unwavering commitment to innovation has resulted in more than 4000 successful installations globally, showcasing the trust placed in our products. Ultimately, our mission is to provide superior data management tools that drive success for our clients.
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
Integrations
Cloudera
Jenkins
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
Data Ladder
Founded
2006
Country
United States
Website
dataladder.com
Vendor Details
Company Name
iceDQ
Founded
2005
Country
United States
Website
icedq.com
Product Features
Data Cleansing
Address/ZIP Code Cleaning
Charting
Data Consolidation / ETL
Data Mapping
Multi Data Format Support
Phone/Email Validation
Raw Data Ingestion
Sample Testing
Validation / Matching / Reconciliation
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