Remove Data Processing Remove Data Transformation Remove Optimization
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CIOs are rethinking how they use public cloud services. Here’s why.

CIO Business Intelligence

Expense optimization and clearly defined workload selection criteria will determine which go to the public cloud and which to private cloud, he says. By moving applications back on premises, or using on-premises or hosted private cloud services, CIOs can avoid multi-tenancy while ensuring data privacy. But should you?

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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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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

AWS Big Data

Together with price-performance, Amazon Redshift offers capabilities such as serverless architecture, machine learning integration within your data warehouse and secure data sharing across the organization. dbt Cloud is a hosted service that helps data teams productionize dbt deployments. Choose Create.

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Amazon Redshift data ingestion options

AWS Big Data

The currently available choices include: The Amazon Redshift COPY command can load data from Amazon Simple Storage Service (Amazon S3), Amazon EMR , Amazon DynamoDB , or remote hosts over SSH. This native feature of Amazon Redshift uses massive parallel processing (MPP) to load objects directly from data sources into Redshift tables.

IoT 109
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Unlock scalable analytics with a secure connectivity pattern in AWS Glue to read from or write to Snowflake

AWS Big Data

In this post, we explore how AWS Glue can serve as the data integration service to bring the data from Snowflake for your data integration strategy, enabling you to harness the power of your data ecosystem and drive meaningful outcomes across various use cases. Store the extracted and transformed data in Amazon S3.

Analytics 112
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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

This means there are no unintended data errors, and it corresponds to its appropriate designation (e.g., Here, it all comes down to the data transformation error rate. In other words, it measures the time between when data is expected and the moment when it is readily available for use. date, month, and year).