In a few clicks, connect to your data and identify and resolve duplicate, inconsistent company and individual name data.
Read More →Go, Python, Node.js, and Java SDKs are now all available.
Read More →Taking the industry by storm, where do they go from here?
Read More →Our AI models have significantly expanded to better handle the analysis of global data.
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Available via npm, easily leverage Interzoid's AI-powered data matching algorithms on javascript-based platforms and frameworks.
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Leverage emerging Generative AI capabilities to solve these issues
Read More →What issues can inconsistent data like this cause in the strategic use of your data?
Read More →We are turbocharging our data preparation and matching technology by leveraging the transformative capabilities of Generative AI. Step into the future of data management with us.
Read More →Compare two company/organization names programmatically to see how similar they are.
Read More →Run match reports on and across Databricks data tables and datasets using the free Databricks Community Edition.
Read More →Run matching/duplicate data reports, identify inconsistent data, enrich data, and more within Databricks clusters and SQL warehouses.
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While both training data and models are essential to successful AI, the paradigm emphasis is shifting.
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Ensure the overall health, accuracy, reliability, and quality of your data assets.
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APIs, interactive dataset processing, and connecting to Cloud databases for analysis are all available with Interzoid.
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Quickly and easily match data, identify inconsistency, and eliminate redundancy on Snowflake's Cloud Data Platform.
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This capability enables scheduled/ongoing processing, automated workflow, and data pipelines.
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A data element analysis of data columns can help towards improving data consistency.
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Quick walkthrough shows how easy identifying redundant data in the Cloud can be.
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Enables fast and simple name scoring in Python.
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This makes using in Golang incredibly fast and simple.
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The complexities involved in matching individual or company/organization names can be considerably reduced.
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How useful are business intelligence applications if the underlying data is suspect?
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ELT is emerging as a preferred approach in the era of Cloud Databases versus traditional ETL. Here's why.
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Using Machine Learning capabilities, an organization can significantly improve the quality, usability, and value of their important data assets.
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Standardized, consistent data assets provide better analytics and data-driven results.
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Any CSV file on the Web can be used as a data source.
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Connect to various database platforms to quickly and easily run actionable match reports.
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An overview of Cloud Relational Database Management offerings from AWS Amazon, and how Interzoid can help with improving the important data in each.
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Leverage matching, standardization of inconsistent data, validation, appending and other features to improve the value of your strategic data assets within Microsoft's Azure SQL Database Platform - all from the browser.
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Sample Use Cases for Interzoid's Cloud Data Connect offering, for Data Engineering in the Cloud with the top Cloud Data Platforms.
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100% Cloud, browser-based application easily connects to and quickly generates live duplication/redundancy reports from data within major Cloud database platforms such as Snowflake, AWS RDS, and Google Cloud SQL.
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We will use our proprietary cleansing, matching, and enrichment tools to increase the usability and value of your data assets.
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Example Interzoid API integration code is provided in Javascript, Typescript, Node, Python, Go, Java, Ruby, Rust, C#, and PHP repositories.
Read More →All content (c) 2018-2023 Interzoid Incorporated. Questions? Contact support@interzoid.com
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