Remove Data Architecture Remove Data Quality Remove Data Warehouse
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Data architecture strategy for data quality

IBM Big Data Hub

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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Perform data parity at scale for data modernization programs using AWS Glue Data Quality

AWS Big Data

Today, customers are embarking on data modernization programs by migrating on-premises data warehouses and data lakes to the AWS Cloud to take advantage of the scale and advanced analytical capabilities of the cloud. Some customers build custom in-house data parity frameworks to validate data during migration.

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How HPE Aruba Supply Chain optimized cost and performance by migrating to an AWS modern data architecture

AWS Big Data

This complex process involves suppliers, logistics, quality control, and delivery. This post describes how HPE Aruba automated their Supply Chain management pipeline, and re-architected and deployed their data solution by adopting a modern data architecture on AWS.

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Visualize data quality scores and metrics generated by AWS Glue Data Quality

AWS Big Data

AWS Glue Data Quality allows you to measure and monitor the quality of data in your data repositories. It’s important for business users to be able to see quality scores and metrics to make confident business decisions and debug data quality issues. An AWS Glue crawler crawls the results.

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Breaking State and Local Data Silos with Modern Data Architectures

Cloudera

Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Data quality issues deter trust and hinder accurate analytics. Modern data architectures. Deploying modern data architectures. Forrester ). Forrester ).

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Cloud Data Warehouse Migration 101: Expert Tips

Alation

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

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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.