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Data Quality Dimensions: Assuring Your Data Quality with Great Expectations

KDnuggets

This article highlights the significance of ensuring high-quality data and presents six key dimensions for measuring it. These dimensions include Completeness, Consistency, Integrity, Timelessness, Uniqueness, and Validity.

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7 Essential Data Cleaning Best Practices

Monte Carlo

Implement Routine Data Audits Build a data cleaning cadence into your data teams’ schedule. Routine data quality checks will not only help to reduce the risk of discrepancies in your data, but it will also help to fortify a culture of high-quality data throughout your organization.

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Accelerate Business Value from Data Sharing with Databricks Unity Catalog and Tredence UnityGO!

databricks

Enterprise leaders are turning to the Databricks Data Intelligence Platform to create a centralized source of high-quality data that business teams can leverage.

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How Fox Facilitates Data Trust with Governance and Monte Carlo

Monte Carlo

Table of Contents Solve data silos starting at the people-level Keep data governance approachable Oliver Gomes’ data governance best practices Manage and promote the value of high-quality data How will Generative AI impact data quality at Fox? But visibility isn’t just for the data team.

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Webinar Summary: Agile, DataOps, and Data Team Excellence

DataKitchen

DataOps and Its Benefits: The concept of DataOps was introduced, drawing parallels with DevOps in terms of its emphasis on automation, continuous integration, and providing a high-quality data production pipeline. The goal is to reduce errors and operational overhead, allowing data teams to focus on delivering value.

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The Future of Retail: Key Challenges and Opportunities

The Modern Data Company

Get to the Future Faster – Modernize Your Manufacturing Data Architecture Without Ripping and Replacing Implementing customer lifetime value as a mission-critical KPI has many challenges. Companies need consistent, high-quality data and a straightforward way to measure CLV.

Retail 97
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AI / ML Survival Guide: Conquer DataOps and Data Composability Challenges and Transform into a Truly Data-Driven Organization

The Modern Data Company

Get to the Future Faster – Modernize Your Manufacturing Data Architecture Without Ripping and Replacing Implementing customer lifetime value as a mission-critical KPI has many challenges. Companies need consistent, high-quality data and a straightforward way to measure CLV.