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What is accel-DS?
Accel-DS is a unique tool that features a no-code, drag-and-drop interface, making it remarkably easy for users to begin their data projects. While building your dataset, you can observe outcomes in real-time in an intuitive spreadsheet-like format, which also serves the purpose of executing data cleansing transformations. This innovative approach disrupts the traditional ETL development cycle, which often requires extensive coding for the processes of extracting, transforming, loading, and verifying results. Tailored specifically for business professionals and end users, it facilitates the smooth integration of data from a variety of sources, such as databases, XML, JSON, WSDL, and streams like Twitter and Sys Log. With no need for coding expertise, users can simply drag and drop their desired data sources. Designed with Big Data in mind, it simplifies the ingestion, cleansing, and transformation of data from any origin into Hadoop or Big Data environments. The system is capable of efficiently transferring gigabytes of data from relational databases and files into Big Data platforms in mere minutes. Additionally, it accommodates both traditional and complex data types, including maps and structures, thereby providing a flexible solution for a wide array of data requirements. This adaptability guarantees that users can tailor the tool to meet their unique needs with minimal effort, enhancing their overall experience.
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 Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
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
Proden Technologies
Company Location
United States
Company Website
prodentechnologies.net/data-integration-tools.php
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
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services
Categories and Features
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management