Step-by-Step Data Matching in the Cloud Tutorial

Posted on February 25th, 2023

Match Report Type for Data Matching Tutorial

We have published a step-by-step tutorial demonstrating the automated identification of inconsistent company name data in a dataset. It shows our Cloud Data Connect product that connects to various data sources and runs match reports, appends similarity keys, generates SQL, and performs several other functions utilizing Interzoid APIs behind the scenes to identify matches.

The tutorial found here provides a walkthrough of the automated generation of a match report of possible duplicate data for a CSV file that is stored in the Cloud in AWS S3. The product works the same for Cloud databases such as Snowflake, AWS RDS, Google Cloud SQL, Microsoft Azure SQL, Postgres, MySQL, and several others. It also works with other data content types such as individual person data and street address data, data that is typically inconsistently represented within databases.

Database Cloud Connect for Matching Data Tutorial

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AI Interactive Data Client: Request and Receive Structured Data of Any Kind on Any Subject.

Also, turn your structured data requests into an API call to integrate anywhere with different input parameters.
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Generate Match Reports with CSV and TSV Files

Just a few clicks to analyze your local files for data redundancies and inconsistency, including organizations, names, and addresses.
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Github Code Examples

Code examples for multiple scenarios such as easy integration, appending data via files in batch, generating match reports, and much more...
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High-Performance Batch Processing: Call our APIs with Text Files as Input.

Perform bulk data enrichment using CSV or TSV files.
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