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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality.

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Amazon DataZone now integrates with AWS Glue Data Quality and external data quality solutions

AWS Big Data

Today, we are pleased to announce that Amazon DataZone is now able to present data quality information for data assets. Other organizations monitor the quality of their data through third-party solutions. Additionally, Amazon DataZone now offers APIs for importing data quality scores from external systems.

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The next generation of Amazon SageMaker: The center for all your data, analytics, and AI

AWS Big Data

With this launch, you can query data regardless of where it is stored with support for a wide range of use cases, including analytics, ad-hoc querying, data science, machine learning, and generative AI. We’ve simplified data architectures, saving you time and costs on unnecessary data movement, data duplication, and custom solutions.

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How HPE Aruba Supply Chain optimized cost and performance by migrating to an AWS modern data architecture

AWS Big Data

This complex process involves suppliers, logistics, quality control, and delivery. This post describes how HPE Aruba automated their Supply Chain management pipeline, and re-architected and deployed their data solution by adopting a modern data architecture on AWS.

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Automated data governance with AWS Glue Data Quality, sensitive data detection, and AWS Lake Formation

AWS Big Data

Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake. Data confidentiality and data quality are the two essential themes for data governance.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

Need for a data mesh architecture Because entities in the EUROGATE group generate vast amounts of data from various sourcesacross departments, locations, and technologiesthe traditional centralized data architecture struggles to keep up with the demands for real-time insights, agility, and scalability.

IoT 111
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Simplify data integration with AWS Glue and zero-ETL to Amazon SageMaker Lakehouse

AWS Big Data

While traditional extract, transform, and load (ETL) processes have long been a staple of data integration due to its flexibility, for common use cases such as replication and ingestion, they often prove time-consuming, complex, and less adaptable to the fast-changing demands of modern data architectures.