Ratings and Reviews 124 Ratings
Ratings and Reviews 0 Ratings
What is Plauti?
Plauti enhances data integrity within Salesforce and Microsoft Dynamics 365 CE, empowering teams to automate processes, generate reports, and leverage AI on reliable records. By ensuring that no information is sent to external servers, all operations occur within your CRM, allowing administrators to maintain complete control without needing to submit any IT requests. The solution addresses data quality throughout the entire record lifecycle, providing a comprehensive overview of data health for all objects and fields, enabling the entire team to operate with a consistent and accurate understanding. It facilitates the bulk cleaning of duplicates, standardizes data formatting, and verifies the validity of emails, phone numbers, and addresses. Additionally, Plauti proactively prevents poor-quality records from entering the system, whether they originate from manual input, imports, APIs, or AI-driven tools such as Agentforce and Copilot. Clean data can be immediately utilized for routing and downstream distribution, allowing AI to function effectively on dependable records. As Plauti is integrated directly with the infrastructure of Salesforce and Dynamics 365 CE, it seamlessly adopts your current permissions and security protocols, eliminating the need for separate logins, avoiding delays in data synchronization, and ensuring compliance with regulations. This deep integration not only optimizes workflow but also enhances trust in your data management processes.
What is DQ for Excel?
Elevate your customer data management in an accessible setting by effortlessly exporting it to Microsoft Excel and employing our convenient plugin available in the Office Store, which enhances data quality significantly. Our tool allows you to modify data by abbreviating, expanding, omitting, or normalizing it in five languages and across twelve distinct categories of entities. You can analyze the similarities between records using various comparison methods, including Levenshtein and Jaro-Winkler, while also generating phonetic match keys for deduplication, such as DQ Fonetix™, Soundex, and Metaphone. Furthermore, classify your data to identify the nature of each entry—for example, distinguishing Brian or Sven as individuals, while recognizing Road, Strasse, or Rue as parts of an address, and identifying Ltd or LLC as corporate legal designations. You have the capability to extract information like gender from names and sort contact details based on job titles and roles that involve decision-making. DQ for Excel™ integrates seamlessly with Microsoft Excel, ensuring that it is both user-friendly and efficient for managing data effectively. In addition, its robust functionalities guarantee that your customer data stays precise, pertinent, and well-organized. This comprehensive approach not only streamlines your workflow but also significantly enhances the overall quality of your data management practices.
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Plauti
Date Founded
2011
Company Location
Netherlands
Company Website
www.plauti.com
Company Facts
Organization Name
DQ Global
Date Founded
1997
Company Location
United States
Company Website
www.dqglobal.com/products/dq-for-excel/
Categories and Features
Customer Data Platforms (CDP)
Behavioral Analytics
Campaign Management
Customer Profiles
Customer Segmentation
Data Integration
Data Matching
GDPR Compliance
Personalization
Predictive Modeling
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 Management Platforms (DMP)
Ad Network Integration
Analytics / ROI Tracking
Audience Targeting
Behavioral Analytics
CRM
Campaign Management
Competitive Analysis
Customer Journey Mapping
Data Capture / Transfer
Data Classification
Data Visualization
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
Email Verification
Bulk Email Verification
Catch-all Server Detection
Disposable Email Detection
Domain Check
Mail Server Validation
Single Email Verification
Spam Trap Detection
Syntax Check
Lead Management
Activity Tracking
Campaign Management
Lead Capture
Lead Distribution
Lead Nurturing
Lead Scoring
Lead Segmentation
Pipeline Management
Prospecting Tools
Source Tracking
Master Data Management
Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization
Categories and Features
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management