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Data Quality Testing: A Shared Resource for Modern Data Teams

DataKitchen

Data Quality Testing: A Shared Resource for Modern Data Teams In today’s AI-driven landscape, where data is king, every role in the modern data and analytics ecosystem shares one fundamental responsibility: ensuring that incorrect data never reaches business customers. That must change.

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Generative AI: A Self-Study Roadmap

KDnuggets

Instead of optimizing for accuracy metrics, you evaluate creativity, coherence, and usefulness. Concepts like overfitting, generalization, and evaluation metrics translate directly to generative AI, though the specific metrics differ. Design iteratively—test variations and measure results systematically.

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MLFlow Mastery: A Complete Guide to Experiment Tracking and Model Management

KDnuggets

It logs parameters, metrics, and files created during tests. This gives a clear record of what was tested. You can see how each test performed. It saves exact settings used for each test. Metrics : Performance metrics such as accuracy, precision, recall, or loss values. Key Components of MLFlow 1.

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Forget Streamlit: Create an Interactive Data Science Dashboard in Excel in Minutes

KDnuggets

By Shamima Sultana on June 19, 2025 in Data Science Image by Editor | Midjourney While Python-based tools like Streamlit are popular for creating data dashboards, Excel remains one of the most accessible and powerful platforms for building interactive data visualizations. Place KPI metrics at the top.

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How DeNA Co., Ltd. accelerated anonymized data quality tests up to 100 times faster using Amazon Redshift Serverless and dbt

AWS Big Data

Conduct data quality tests on anonymized data in compliance with data policies Conduct data quality tests to quickly identify and address data quality issues, maintaining high-quality data at all times. The challenge Data quality tests require performing 1,300 tests on 10 TB of data monthly.

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Automate Data Quality Reports with n8n: From CSV to Professional Analysis

KDnuggets

While most people associate workflow automation with business processes like email marketing or customer support, n8n can also assist with automating data science tasks that traditionally require custom scripting. Advanced quality metrics like data consistency, outlier detection, or schema validation could be added to future versions.

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6 data risks CIOs should be paranoid about

CIO Business Intelligence

To address this gap and ensure the data supply chain receives enough top-level attention, CIOs have hired or partnered with chief data officers, entrusting them to address the data debt , automate data pipelines , and transform to a proactive data governance model focusing on health metrics, data quality , and data model interoperability. [