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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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CRM’s Have a Big Data Technical Debt Problem: Here’s How to Fix It

Smart Data Collective

Customer relationship management (CRM) platforms are very reliant on big data. As these platforms become more widely used, some of the data resources they depend on become more stretched. CRM providers need to find ways to address the technical debt problem they are facing through new big data initiatives.

Big Data 131
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Comparing DynamoDB and MongoDB for Big Data Management

Smart Data Collective

A growing number of companies are discovering the benefits of investing in big data technology. Companies around the world spent over $160 billion on big data technology last year and that figure is projected to grow 11% a year for the foreseeable future. Unfortunately, big data technology is not without its challenges.

Big Data 111
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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

The AWS Glue crawler generates and updates Iceberg table metadata and stores it in AWS Glue Data Catalog for existing Iceberg tables on an S3 data lake. Snowflake integrates with AWS Glue Data Catalog to retrieve the snapshot location. Andries has over 20 years of experience in the field of data and analytics.

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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. project-dir. -- Run all the snapshot files dbt snapshot --profiles-dir.

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Use AWS Glue ETL to perform merge, partition evolution, and schema evolution on Apache Iceberg

AWS Big Data

Iceberg creates snapshots for the table contents. Each snapshot is a complete set of data files in the table at a point in time. Data files in snapshots are stored in one or more manifest files that contain a row for each data file in the table, its partition data, and its metrics.

Snapshot 108
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Enhance your security posture by storing Amazon Redshift admin credentials without human intervention using AWS Secrets Manager integration

AWS Big Data

Restore a snapshot New warehouses can be launched from both serverless and provisioned snapshots. On the provisioned snapshot dashboard, on the Restore snapshot menu, choose Restore to provisioned cluster or Restore to serverless namespace. Try it out today and leave a comment if you have any questions or suggestions.