Remove Dashboards Remove Data Transformation Remove Optimization
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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications.

Big Data 275
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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. The applications are hosted in dedicated AWS accounts and require a BI dashboard and reporting services based on Tableau.

IoT 105
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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

If you ask an engineer to show how they operate the application in production, they will likely show containers and operational dashboards—not unlike any other software service. However, none of these layers help with modeling and optimization. Model Operations. Model Development.

IT 364
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Accelerate your data workflows with Amazon Redshift Data API persistent sessions

AWS Big Data

Maintaining reusable database sessions to help optimize the use of database connections, preventing the API server from exhausting the available connections and improving overall system scalability. This enables you to integrate web-based applications to access data from Amazon Redshift using an API to run SQL statements.

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BMW Cloud Efficiency Analytics powered by Amazon QuickSight and Amazon Athena

AWS Big Data

BMW Group uses 4,500 AWS Cloud accounts across the entire organization but is faced with the challenge of reducing unnecessary costs, optimizing spend, and having a central place to monitor costs. The CLEA dashboards were built on the foundation of the Well-Architected Lab.

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

He/she assists the organization by providing clarity and insight into advanced data technology solutions. As quality issues are often highlighted with the use of dashboard software , the change manager plays an important role in the visualization of data quality. Here, it all comes down to the data transformation error rate.

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Data Engineers Are Using AI to Verify Data Transformations

Wayne Yaddow

AI is transforming how senior data engineers and data scientists validate data transformations and conversions. Artificial intelligence-based verification approaches aid in the detection of anomalies, the enforcement of data integrity, and the optimization of pipelines for improved efficiency.