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Description
Data is essential across various departments in a business, including sales, marketing, and finance. To maximize the effectiveness of this data, it is crucial to ensure its upkeep, security, and oversight throughout its lifecycle. At Uniserv, data quality is a fundamental aspect of our company ethos and the solutions we provide. Our tailored offerings transform your customer master data into a pivotal asset for your organization. The Data Quality Service Hub guarantees superior customer data quality at every location within your enterprise, extending even to international operations. We provide services to correct your address information in line with global standards, utilizing top-tier reference data. Additionally, we verify email addresses, phone numbers, and banking details across various levels of scrutiny. Should your data contain duplicate entries, we can efficiently identify them based on your specified business criteria. The duplicates detected can often be merged automatically following established guidelines or organized for manual review, ensuring a streamlined data management process that enhances operational efficiency. This comprehensive approach to data quality not only supports compliance but also fosters trust and reliability in your customer interactions.
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.
API Access
Has API
API Access
Has API
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
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
Uniserv
Founded
1969
Country
Germany
Website
www.uniserv.com/en/business-cases/customer-data-management/data-quality/
Vendor Details
Company Name
Precisely
Founded
1968
Country
United States
Website
www.precisely.com/product/precisely-data360/data360-dq
Product Features
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
Product Features
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management