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AI Implementation: The Roadmap to Leveraging AI in Your Organization

Ascend.io

Visual representation of Conway’s Law ( source ) Read More: The Chief AI Officer: Avoid The Trap of Conway’s Law Process: Ensuring Data Readiness The backbone of successful AI implementation is robust data management processes. AI models are only as good as the data they consume, making continuous data readiness crucial.

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Data Teams and Their Types of Data Journeys

DataKitchen

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. ’ What’s a Data Journey?

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[O’Reilly Book] Chapter 1: Why Data Quality Deserves Attention Now

Monte Carlo

Not long after data warehouses moved to the cloud, so too did data lakes (a place to transform and store unstructured data), giving data teams even greater flexibility when it comes to managing their data assets. As data becomes more and more foundational to business, data teams will only grow.

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

Monte Carlo

The `dbt run` command will compile and execute your models, thus transforming your raw data into analysis-ready tables. Once the models are created and data transformed, `dbt test` should be executed. This command runs all tests defined in your dbt project against the transformed data. Also, remember data governance.

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