Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Legislative measures dictate the conditions under which information can be disseminated and the scenarios that justify such sharing. To enhance the efficiency of information exchange among agencies during investigations of particular cases, data matching and discovery techniques are employed. At the core of the Kalinda system lies an advanced machine-learning algorithm designed to correlate individual records across various agencies by analyzing personal traits such as name and date of birth, as well as the characteristics of associated individuals. Thorough investigations frequently necessitate examining connections between individuals or locations, especially when only incomplete data is available. Kalinda is equipped to handle queries involving partial matches related to individuals, locations, and their interrelations. Additionally, it provides sophisticated algorithms that enable the discovery of records that bear resemblance to the matched ones by utilizing probabilistic record matching methods. This capability significantly broadens the scope of potential leads in investigations, making Kalinda an invaluable tool for law enforcement and investigative agencies.
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
No
API Access
Has API
No
Integrations
PostgreSQL
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
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
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Kalinda
Country
Australia
Website
www.factil.io/products/kalinda/
Vendor Details
Company Name
QDeFuZZiner
Website
zmatasoft.wixsite.com/qdefuzziner/qdefuzziner-software-features
Product Features
Government
Budgeting & Forecasting
No
Code Enforcement
No
Compliance Management
No
Fixed Asset Management
No
Inventory Management
No
License Issuance
No
Permit Issuance
No
Purchasing & Receiving
No
Self Service Portal
No
Taxation & Assessment
No
Utility Billing
No
Work Order Management
No