This AWS instance enables you to quickly and easily identify matches of inconsistent, duplicate/redundant, and otherwise non-normalized data of organization/company names, individual names, and addresses using an AI model built into the application platform.

There are two ways to do this, an API for a single data entity such as an organization name or an individual name, and also the command-line driven CONNECT application for analyzing a text file or database table, generating "match reports", as well as enabling match index tables to be created for more advanced purposes, such as SQL JOINS that overcome data inconsistency issues or matching/appending data between two datasets to get signficantly higher match rates, and also prevent redundant, non-normalized data to enter a database at the point of data collection.

Using the API, a similarity key is generated for the entity in the parameter of the call. Data that is "similar" will generate the same similarity key.

Examples:

GE -> wAR3laPfUVvB784_iH0cw7aQbKhr26sophlZ4z7iqtM General Electric -> wAR3laPfUVvB784_iH0cw7aQbKhr26sophlZ4z7iqtM

AMAZON.COM -> EP88bx0VFDaIh-cOt86c8pOJ6lNkb_TWiKFpmMKXakY Amazon Inc. -> EP88bx0VFDaIh-cOt86c8pOJ6lNkb_TWiKFpmMKXakY

This can be achieved by calling the API that is running on this instance. For example, you can use cURL to make the API call:

$ curl 'http://localhost:8950/getcompanymatchadvanced?company=ibm&algorithm=wide '

Use the generated similarity key, rather than the actual data itself, to match, normalize, and/or sort company name data by similarity. This avoids the problems of data inconsistency, misspellings, and name variations when matching within a single dataset, and can also help matching across datasets or for more advanced searching.

Calling this API enables the capability to be built into an infinite number of applications, processes, pipelines, and more.

For Connect, which supports analysis, processing, and reporting of full datasets, the following data sources are supported.

File Types (requires pathname in the "connection" parameter when calling the API, either locally with full path or at a URL address)

CSV TSV Excel Parquet

Databases (local, on the network, or in the Cloud - requires connection string in the "connection" parameter)

AWS RDS (Postgres & MySQL) AWS Aurora (Postgres & MySQL) Postgres MySQL Azure SQL SQL Server Snowflake Databricks Google Cloud SQL (Postgres & MySQL) SkySQL (MySQL) CockroachDB

All database connections are native connectivity. The source can either be a table within the database or a logical view.

For more documentation, usage, and getting starting info, see the following starting point directory upon launch of the instance: $ /home/ec2-user/interzoid