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Description
Goodlookup is an intelligent function designed specifically for those who use spreadsheets. This innovative tool combines the intuitive capabilities of GPT-3 with the advanced fuzzy matching features to enhance your productivity. You can utilize it similarly to vlookup or index match, significantly accelerating your topic clustering tasks in Google Sheets! A common drawback of conventional fuzzy matching is its inability to account for contextual similarities beyond mere string comparison. Effective topic clustering demands a deeper semantic comprehension. Thankfully, recent breakthroughs in natural language processing have opened up exciting new avenues for analyzing text data. Goodlookup stands out as an advanced function that approaches true semantic understanding, allowing it to identify similarities in text with a human-like perspective. This tool can recognize semantic connections, synonyms, and even cultural nuances in text strings. Rather than replacing traditional fuzzy matching methods, Goodlookup serves as an additional resource in your data operations toolkit, enriching your analysis capabilities even further. With Goodlookup, you can unlock greater potential in your data-driven projects.
Description
In QDeFuZZiner software, the fundamental unit is referred to as a project, which encompasses the definitions of two source datasets for import and analysis, known as the "left dataset" and "right dataset." Each project not only includes these datasets but also a variable number of solutions that detail the methodology for conducting fuzzy match analysis. Upon creation, every project is assigned a distinct project tag, which is subsequently appended to the names of the corresponding input tables during the raw data import process. This tagging system guarantees that the imported tables maintain uniqueness through association with their respective project names. Furthermore, during the import phase and later when generating and executing solutions, QDeFuZZiner establishes various indexes on the PostgreSQL database, thereby enhancing the efficiency of fuzzy data matching procedures. The datasets themselves can be sourced from spreadsheet formats such as .xlsx, .xls, .ods, or from CSV (comma separated values) flat files, which are uploaded to the server database, leading to the creation, indexing, and processing of the associated left and right database tables. This structured approach not only simplifies data management but also streamlines the analysis process, making it easier for users to derive insights from their datasets.
API Access
Has API
API Access
Has API
Pricing Details
$15 per year
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
Goodlookup
Website
www.goodlookup.com
Vendor Details
Company Name
QDeFuZZiner
Website
zmatasoft.wixsite.com/qdefuzziner/qdefuzziner-software-features
Product Features
Spreadsheet
Analytics
Audit Trail
Calculators
Charting
Multi-User Collaboration
Templates