Remove Data Governance Remove Data Warehouse Remove Structured Data Remove Visualization
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Data governance in the age of generative AI

AWS Big Data

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

Data landscape in EUROGATE and current challenges faced in data governance The EUROGATE Group is a conglomerate of container terminals and service providers, providing container handling, intermodal transports, maintenance and repair, and seaworthy packaging services. Eliminate centralized bottlenecks and complex data pipelines.

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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. You can use the same capabilities to serve financial reporting, measure operational performance, or even monetize data assets.

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Building Robust Data Pipelines: 9 Fundamentals and Best Practices to Follow

Alation

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

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Improve healthcare services through patient 360: A zero-ETL approach to enable near real-time data analytics

AWS Big Data

The solution uses AWS services such as AWS HealthLake , Amazon Redshift , Amazon Kinesis Data Streams , and AWS Lake Formation to build a 360 view of patients. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse. We use on-demand capacity mode.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

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5 Pain Points of Moving Data to the Cloud and Strategies for Success

Alation

We have seen the COVID-19 pandemic accelerate the timetable of cloud data migration , as companies evolve from the traditional data warehouse to a data cloud, which can host a cloud computing environment. Accompanying this acceleration is the increasing complexity of data. Complex data management is on the rise.