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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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Implement data warehousing solution using dbt on Amazon Redshift

AWS Big Data

Snapshots – These implements type-2 slowly changing dimensions (SCDs) over mutable source tables. Seeds – These are CSV files in your dbt project (typically in your seeds directory), which dbt can load into your data warehouse using the dbt seed command. The table refresh can be full or incremental based on the configuration.

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Unleash the power of Snapshot Management to take automated snapshots using Amazon OpenSearch Service

AWS Big Data

in Amazon OpenSearch Service , we introduced Snapshot Management , which automates the process of taking snapshots of your domain. Snapshot Management helps you create point-in-time backups of your domain using OpenSearch Dashboards, including both data and configuration settings (for visualizations and dashboards).

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End-to-end development lifecycle for data engineers to build a data integration pipeline using AWS Glue

AWS Big Data

Solution overview Typically, you have multiple accounts to manage and provision resources for your data pipeline. About the author Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. rename_field('id', 'org_id').rename_field('name', He works based in Tokyo, Japan.

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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

An in-place migration can be performed in either of two ways: Using add_files : This procedure adds existing data files to an existing Iceberg table with a new snapshot that includes the files. Unlike migrate or snapshot, add_files can import files from a specific partition or partitions and doesn’t create a new Iceberg table.

Data Lake 102
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Power enterprise-grade Data Vaults with Amazon Redshift – Part 2

AWS Big Data

Automated backup Amazon Redshift automatically takes incremental snapshots that track changes to the data warehouse since the previous automated snapshot. Automated snapshots retain all of the data required to restore a data warehouse from a snapshot.

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Break data silos and stream your CDC data with Amazon Redshift streaming and Amazon MSK

AWS Big Data

This solution uses Amazon Aurora MySQL hosting the example database salesdb. Valid values for OP field are: c = create u = update d = delete r = read (applies to only snapshots) The following diagram illustrates the solution architecture: The solution workflow consists of the following steps: Amazon Aurora MySQL has a binary log (i.e.,