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Average Ratings 0 Ratings
Description
Enhance the integrity of your data both during transit and when stored by implementing superior monitoring, visualization, remediation, and reconciliation techniques. Ensuring data quality should be ingrained in the core values of your organization. Go beyond standard data quality assessments to gain a comprehensive understanding of your data as it traverses through your organization, regardless of its location. Continuous monitoring of quality and meticulous point-to-point reconciliation are essential for fostering trust in data and providing reliable insights. Data360 DQ+ streamlines the process of data quality evaluation throughout the entire data supply chain, commencing from the moment information enters your organization to oversee data in transit. Examples of operational data quality include validating counts and amounts across various sources, monitoring timeliness to comply with internal or external service level agreements (SLAs), and conducting checks to ensure that totals remain within predefined thresholds. By embracing these practices, organizations can significantly improve decision-making processes and enhance overall performance.
Description
Ensure the accuracy and reliability of your address information by cross-referencing it with official Postal Authority databases. This will enhance delivery success rates, reduce the incidence of returned mail, and help you take advantage of postal discounts. Integrate address data sources with our robust cleansing transformations, allowing you to prepare your address data for validation and verification effectively. By identifying individual components within your address records, you can separate them into distinct elements. Address common typographical errors and format your data to adhere to industry standards, which will lead to improved mail delivery outcomes. Additionally, verify the legitimacy of addresses through the official USPS address database, determining if they are residential or commercial and confirming their deliverability with USPS Delivery Point Validation (DPV). Once validated, you can seamlessly merge this data back into various disparate data sources or create tailored output files that align with your organization’s operational processes. Ultimately, this comprehensive approach will significantly enhance the integrity of your address data and streamline your mailing operations.
API Access
Has API
No
API Access
Has API
No
Integrations
Safyr
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Precisely
Founded
1968
Country
United States
Website
www.precisely.com/product/precisely-data360/data360-dq
Vendor Details
Company Name
Firstlogic
Country
United States
Website
firstlogic.com/products/data-quality-suite
Product Features
Data Quality
Address Validation
No
Data Deduplication
No
Data Discovery
No
Data Profililng
No
Master Data Management
No
Match & Merge
No
Metadata Management
No
Product Features
Address Verification
Address Validation
No
Autocomplete
No
Automatic Formatting
No
Data Cleansing
No
Data Discovery
No
Data Quality Control
No
Data Verification
No
Geographic Maps
No
Geolocation
No
Metadata Management
No
Reporting / Analytics
No
Search / Filter
No
Data Quality
Address Validation
No
Data Deduplication
No
Data Discovery
No
Data Profililng
No
Master Data Management
No
Match & Merge
No
Metadata Management
No