Remove Data Architecture Remove Data Warehouse Remove Metadata
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Expand data access through Apache Iceberg using Delta Lake UniForm on AWS

AWS Big Data

The landscape of big data management has been transformed by the rising popularity of open table formats such as Apache Iceberg, Apache Hudi, and Linux Foundation Delta Lake. These formats, designed to address the limitations of traditional data storage systems, have become essential in modern data architectures.

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Run Apache XTable in AWS Lambda for background conversion of open table formats

AWS Big Data

This post was co-written with Dipankar Mazumdar, Staff Data Engineering Advocate with AWS Partner OneHouse. Data architecture has evolved significantly to handle growing data volumes and diverse workloads. This allows the existing data to be interpreted as if it were originally written in any of these formats.

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What is a Data Mesh?

DataKitchen

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. The past decades of enterprise data platform architectures can be summarized in 69 words. Introduction to Data Mesh. Source: Thoughtworks.

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Accelerate SQL code migration from Google BigQuery to Amazon Redshift using BladeBridge

AWS Big Data

BladeBridge offers a comprehensive suite of tools that automate much of the complex conversion work, allowing organizations to quickly and reliably transition their data analytics capabilities to the scalable Amazon Redshift data warehouse. times better price performance than other cloud data warehouses.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems. As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant.

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How Metadata Makes Data Meaningful

erwin

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

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Breaking State and Local Data Silos with Modern Data Architectures

Cloudera

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Deploying modern data architectures. Lack of sharing hinders the elimination of fraud, waste, and abuse. Forrester ).