Remove Data Governance Remove Data Strategy Remove Metadata Remove Unstructured Data
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Data governance in the age of generative AI

AWS Big Data

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

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What Is Data Modeling? Data Modeling Best Practices for Data-Driven Organizations

erwin

Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise. Variations of A Theme.

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What is a data architect? Skills, salaries, and how to become a data framework master

CIO Business Intelligence

Application data architect: The application data architect designs and implements data models for specific software applications. Information/data governance architect: These individuals establish and enforce data governance policies and procedures.

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Data architecture strategy for data quality

IBM Big Data Hub

Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads. Efficiently adopt data platforms and new technologies for effective data management. Apply metadata to contextualize existing and new data to make it searchable and discoverable.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

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5 Types of Costly Data Waste and How to Avoid Them

CIO Business Intelligence

. • You have data but don’t use it. Why does valuable data so often go unused? Lack of annotation with the right metadata is a contributing factor. An even larger issue is that people may not know how to see value in data. Recognizing what data can tell you is an acquired skill for people beyond just data scientists.

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A Guide to Data Analytics in the Travel Industry

Alation

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? What are common data challenges for the travel industry?