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Unlocking the Value of Data: A Comprehensive Guide to Data Profiling

Analysts Corner

As organizations increasingly rely on data to drive their operations, strategy, and innovation, ensuring data integrity and usability has never been more important. This is where data profiling comes into play. It’s akin to conducting a “health check” on your data to assess its quality, integrity, consistency, and usability.

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Information Governance vs. Data Governance: A Comparative Analysis

Astera

Data governance focuses on the technical and operational aspects of managing data, while information governance looks at the wider policies, procedures, and strategies guiding data usage. They are different, yet they complement each other, providing a holistic approach to managing data.

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What is a Data Catalog? Features, Best Practices, and Benefits

Astera

The former offers a comprehensive view of an organization’s data assets. It facilitates data discovery and exploration by enabling users to easily search and explore available data assets. Benefits of a Data Catalog With the components and workings of a data catalog established, how do they benefit an organization?

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Data Catalog vs. Data Dictionary vs. Business Glossary: Key Differences

Astera

This feature is valuable for understanding data dependencies and ensuring data quality across the entire data lifecycle. While data dictionaries offer some lineage information for specific fields within a database, data catalogs provide a more comprehensive lineage view across various data sources.

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Data Governance Framework: What is it? Importance, Pillars and Best Practices

Astera

A data governance framework is a structured way of managing and controlling the use of data in an organization. It helps establish policies, assign roles and responsibilities, and maintain data quality and security in compliance with relevant regulatory standards.

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What Is a Business Glossary? Definition, Components & Benefits

Astera

Understanding the Business Glossary A business glossary is a repository of data-related terms and definitions specific to a company’s industry, processes, and products. It includes industry-specific jargon, acronyms, and business-specific terminologies, all systematically organized for easy reference.

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Data Wrangling and Exploratory Analysis

The BAWorld

The primary purpose of data scientists is to find a suitable data science model for the massive amount of data. A data science model refers to organizing the data elements and extracting meaningful insights from raw, unstructured data. Core Data Wrangling Activities. Discovering. Structuring.