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Data Teams and Their Types of Data Journeys

DataKitchen

This lack of control is exacerbated by many people and/or automated data ingestion processes introducing changes to the data. This creates a chaotic data landscape where accountability is elusive and data integrity is compromised. The Hub Data Journey provides the raw data and adds value through a ‘contract.

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The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure

DataKitchen

The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure. While working in Azure with our customers, we have noticed several standard Azure tools people use to develop data pipelines and ETL or ELT processes. We counted ten ‘standard’ ways to transform and set up batch data pipelines in Microsoft Azure.

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Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability

DataKitchen

Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors. There are multiple locations where problems can happen in a data and analytic system. What is Data in Use?

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What is dbt Testing? Definition, Best Practices, and More

Monte Carlo

Run the test again to validate that the initial problem is solved and that your data meets your quality and accuracy standards. Schedule and automate Just like schema tests, custom data tests in dbt are typically not run just once but are incorporated into your regular data pipeline to ensure ongoing data quality.

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