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

AWS Big Data

A CDC-based approach captures the data changes and makes them available in data warehouses for further analytics in real-time. usually a data warehouse) needs to reflect those changes in near real-time. This post showcases how to use streaming ingestion to bring data to Amazon Redshift.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Data processing Raw data is often cluttered with duplicates and irregular formats.

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Fivetran Modern Data Stack Conference 2023: Key Takeaways

Alation

Last week, the Alation team had the privilege of joining IT professionals, business leaders, and data analysts and scientists for the Modern Data Stack Conference in San Francisco. In this blog, I’ll share a quick high-level overview of the event, with an eye to core themes. What did attendees take away from the event?

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How Dafiti made Amazon QuickSight its primary data visualization tool

AWS Big Data

The following factors guided our decision: Tool close to data – It was important to have the data visualization tool as close to the data as possible. At Dafiti, the entire infrastructure is on AWS, and we use Amazon Redshift as our Data Warehouse.

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Migrate your existing SQL-based ETL workload to an AWS serverless ETL infrastructure using AWS Glue

AWS Big Data

Customers often use many SQL scripts to select and transform the data in relational databases hosted either in an on-premises environment or on AWS and use custom workflows to manage their ETL. AWS Glue is a serverless data integration and ETL service with the ability to scale on demand. Choose Submit.

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Join a streaming data source with CDC data for real-time serverless data analytics using AWS Glue, AWS DMS, and Amazon DynamoDB

AWS Big Data

You will also want to apply incremental updates with change data capture (CDC) from the source system to the destination. To make data-driven decisions in a timely manner, you need to account for missed records and backpressure, and maintain event ordering and integrity, especially if the reference data also changes rapidly.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

The longer answer is that in the context of machine learning use cases, strong assumptions about data integrity lead to brittle solutions overall. Most of the data management moved to back-end servers, e.g., databases. So we had three tiers providing a separation of concerns: presentation, logic, data. Upcoming Events.