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

See our Snowflake Native Application. Achieve Data Quality built-in to SQL statements.

Identify inconsistent and duplicate data quickly and easily in data tables and files.
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Connect Directly to Cloud SQL Databases and Perform Data Quality Analysis

Achieve better, more consistent, more usable data.
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Try our Pay-as-you-Go Option

Start increasing the usability and value of your data - start small and grow with success.
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Launch Our Entire Data Quality Matching System on an AWS EC2 Instance

Deploy to the instance type of your choice in any AWS data center globally. Start analyzing data and identifying matches across many databases and file types in minutes.
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