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Monitor data pipelines in a serverless data lake

AWS Big Data

The combination of a data lake in a serverless paradigm brings significant cost and performance benefits. By monitoring application logs, you can gain insights into job execution, troubleshoot issues promptly to ensure the overall health and reliability of data pipelines.

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Reference guide to build inventory management and forecasting solutions on AWS

AWS Big Data

Inventory management is a critical function for any business that deals with physical products. The primary challenge businesses face with inventory management is balancing the cost of holding inventory with the need to ensure that products are available when customers demand them.

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Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

In collaboration with AWS, BMS identified a business need to migrate and modernize their custom extract, transform, and load (ETL) platform to a native AWS solution to reduce complexities, resources, and investment to upgrade when new Spark, Python, or AWS Glue versions are released.

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Enforce fine-grained access control on Open Table Formats via Amazon EMR integrated with AWS Lake Formation

AWS Big Data

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

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How to use foundation models and trusted governance to manage AI workflow risk

IBM Big Data Hub

AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. It can be used with both on-premise and multi-cloud environments.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America.

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How the BMW Group analyses semiconductor demand with AWS Glue

AWS Big Data

Additionally, this forecasting system needs to provide data enrichment steps including byproducts, serve as the master data around the semiconductor management, and enable further use cases at the BMW Group. To enable this use case, we used the BMW Group’s cloud-native data platform called the Cloud Data Hub.