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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Enhance your customer data within a user-friendly environment by easily exporting it into Microsoft Excel and utilizing our plugin, which can be found in the Office Store for improved data quality. With our tool, you can transform data by abbreviating, elaborating, excluding, or normalizing it across five spoken languages and twelve distinct entity categories. You can assess the similarity between records through various comparison techniques, such as Levenshtein and Jaro-Winkler, and generate phonetic match keys for deduplication purposes, including DQ Fonetix™, Soundex, and Metaphone. Additionally, classify your data to determine what each piece represents—for instance, recognizing Brian or Sven as personal names, while identifying Road, Strasse, or Rue as elements of an address, and Ltd or LLC as legal suffixes for companies. You can also derive information such as gender from names and categorize contact information based on job titles and decision-making roles. DQ for Excel™ operates seamlessly within Microsoft Excel, making it both intuitive and straightforward to use, thus streamlining your data management processes effectively. Moreover, with its powerful features, you can ensure that your customer data remains accurate, relevant, and organized.

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 No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Microsoft Excel Yes 
Safyr No 

Integrations

Microsoft Excel No 
Safyr Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version 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 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

DQ Global

Founded

1997

Country

United States

Website

www.dqglobal.com/products/dq-for-excel/

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 No 
Data Deduplication No 
Data Discovery No 
Data Profililng No 
Master Data Management No 
Match & Merge No 
Metadata Management No 

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 

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