Remove Business Objectives Remove Data Governance Remove Data Lake Remove Metadata
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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities. A data hub contains data at multiple levels of granularity and is often not integrated. Let’s look at the components of the architecture in more detail.

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Data architecture strategy for data quality

IBM Big Data Hub

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

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

AWS Big Data

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. Then, you transform this data into a concise format. Let’s find out what role each of these components play in the context of C360.

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Data Mesh 101: How Data Mesh Helps Organizations Be Data-Driven and Achieve Velocity

Ontotext

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. However, data mesh is not about introducing new technologies. by building data products with domain owners.