Remove 2022 Remove Data Architecture Remove Data Integration Remove Visualization
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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions. Andries has over 20 years of experience in the field of data and analytics.

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Load data incrementally from transactional data lakes to data warehouses

AWS Big Data

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure. Various data stores are supported in AWS Glue; for example, AWS Glue 4.0

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Exploring new ETL and ELT capabilities for Amazon Redshift from the AWS Glue Studio visual editor

AWS Big Data

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. AWS Glue provides an extensible architecture that enables users with different data processing use cases, and works well with Amazon Redshift.

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Augmented data management: Data fabric versus data mesh

IBM Big Data Hub

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

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

AWS Big Data

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. In 2022, AWS commissioned a study conducted by the American Productivity and Quality Center (APQC) to quantify the Business Value of Customer 360.