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Scale knowledge management use cases with generative AI

IBM Big Data Hub

With data stored across clouds and on-premises environments, it becomes difficult to access it while managing governance and controlling costs. Further complicating matters, the uses of data have become more varied, and companies are faced with managing complex or poor-quality data.

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Enhance data security and governance for Amazon Redshift Spectrum with VPC endpoints

AWS Big Data

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3).

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How FanDuel adopted a modern Amazon Redshift architecture to serve critical business workloads

AWS Big Data

More and more of FanDuel’s community of analysts and business users looked for comprehensive data solutions that centralized the data across the various arms of their business. Their individual, product-specific, and often on-premises data warehouses soon became obsolete.

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What is Business Intelligence Consulting

BizAcuity

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization.

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What is Business Intelligence Consulting

BizAcuity

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization.

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Data architecture strategy for data quality

IBM Big Data Hub

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. Reduce data duplication and fragmentation.

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Data Mesh 101: How Data Mesh Helps Organizations Be Data-Driven and Achieve Velocity

Ontotext

This promotes data autonomy and enables decision-making about data domains without centralized gatekeepers. It also breaks down the code and data monolith and distributes it across the domain teams, which results in better management and scalability. What does data mesh do that other approaches can’t?