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Data Profiling: What It Is and How to Perfect It

Alation

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

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How to Deliver Data Quality with Data Governance: Ryan Doupe, CDO of American Fidelity, 9-Step Process

Alation

This starts by determining the critical data elements for the enterprise. These items become in scope for the data quality program. Step 2: Data Definitions. Here each critical data element is described so there are no inconsistencies between users or data stakeholders. Step 4: Data Sources.

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Data Mesh vs. Data Fabric: A Love Story

Alation

But make no mistake: A data catalog addresses many of the underlying needs of this self-serve data platform, including the need to empower users with self-serve discovery and exploration of data products. In this blog series, we’ll offer deep definitions of data fabric and data mesh, and the motivations for each. (We

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Data Catalog First, Master Data Management Second: Here’s Why

Alation

A data catalog communicates the organization’s data quality policies so people at all levels understand what is required for any data element to be mastered. Documenting rule definitions and corrective actions guide domain owners and stewards in addressing quality issues.

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Alation 2022.2: Open Data Quality Initiative and Enhanced Data Governance

Alation

Prime examples of this in the data catalog include: Trust Flags — Allow the data community to endorse, warn, and deprecate data to signal whether data can or can’t be used. Data Profiling — Statistics such as min, max, mean, and null can be applied to certain columns to understand its shape.

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How RallyPoint and AWS are personalizing job recommendations to help military veterans and service providers transition back into civilian life using Amazon Personalize

AWS Machine Learning Blog

The sample set of de-identified, already publicly shared data included thousands of anonymized user profiles, with more than fifty user-metadata points, but many had inconsistent or missing meta-data/profile information. For the definitions of all available offline metrics, refer to Metric definitions.

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Data Hygiene Explained: Best Practices and Key Features

Pickl AI

By maintaining clean and reliable data, businesses can avoid costly mistakes, enhance operational efficiency, and gain a competitive edge in their respective industries. Best Data Hygiene Tools & Software Trifacta Wrangler Pros: User-friendly interface with drag-and-drop functionality. Provides real-time data monitoring and alerts.