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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

Flipboard

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis.

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How to Build Effective Data Pipelines in Snowpark

phData

As today’s world keeps progressing towards data-driven decisions, organizations must have quality data created from efficient and effective data pipelines. For customers in Snowflake, Snowpark is a powerful tool for building these effective and scalable data pipelines.

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Shaping the future: OMRON’s data-driven journey with AWS

AWS Machine Learning Blog

When needed, the system can access an ODAP data warehouse to retrieve additional information. Document management Documents are securely stored in Amazon S3, and when new documents are added, a Lambda function processes them into chunks. Emel Mendoza is a Senior Solutions Architect at AWS based in the Netherlands.

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How Dataiku and Snowflake Strengthen the Modern Data Stack

phData

Snowflake’s cloud-agnosticism, separation of storage and compute resources, and ability to handle semi-structured data have exemplified Snowflake as the best-in-class cloud data warehousing solution. Snowflake supports data sharing and collaboration across organizations without the need for complex data pipelines.

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Optimizing Matillion Workflows: A Guide to Visual Design and Best Practices

phData

For those unfamiliar with GIT or GIT practices, please refer Git for Business Users with Matillion DPC What is a Matillion Pipeline? A Matillion pipeline is a collection of jobs that extract, load, and transform (ETL/ELT) data from various sources into a target system, such as a cloud data warehouse like Snowflake.

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What Is Fivetran and How Much Does It Cost?

phData

Fivetran is an automated data integration platform that offers a convenient solution for businesses to consolidate and sync data from disparate data sources. With over 160 data connectors available, Fivetran makes it easy to move data out of, into, and across any cloud data platform in the market.

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Migrating to the cloud? Follow these steps to encourage success

Smart Data Collective

The recommendation is to bring a minimal amount of data, development environments, and automation tools to the initial cloud environment, then introduce users and iterate based on their needs. Failing to make production data accessible in the cloud. Centralise new data and computational resources.