Remove Big Data Remove Business Intelligence Remove Metadata
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A Beginner’s Guide to Data Warehousing

Unite.AI

In this digital economy, data is paramount. Today, all sectors, from private enterprises to public entities, use big data to make critical business decisions. However, the data ecosystem faces numerous challenges regarding large data volume, variety, and velocity. Enter data warehousing!

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How data stores and governance impact your AI initiatives

IBM Journey to AI blog

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Sometimes, these outputs are biased because the data used to train the model was incomplete or inaccurate in some way.

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9 data governance strategies that will unlock the potential of your business data

IBM Journey to AI blog

The steering committee or governance council can establish data governance policies around privacy, retention, access and security while defining data management standards to streamline processes and certify consistency and compliance as new data is introduced.

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A Comprehensive Guide to the main components of Big Data

Pickl AI

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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A Comprehensive Guide to the Main Components of Big Data

Pickl AI

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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Data architecture strategy for data quality

IBM Journey to AI blog

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

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Data integrity vs. data quality: Is there a difference?

IBM Journey to AI blog

The more complete, accurate and consistent a dataset is, the more informed business intelligence and business processes become. To standardize data, business rules are applied to ensure datasets conform to an organization’s standards and needs.