Remove Data Warehouse Remove Metadata Remove ROI
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Four Use Cases Proving the Benefits of Metadata-Driven Automation

erwin

Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. As such, traditional – and mostly manual – processes associated with data management and data governance have broken down.

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When is data too clean to be useful for enterprise AI?

CIO Business Intelligence

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

More generally, low-quality data can impact productivity, bottom line, and overall ROI. We’ll get into some of the consequences of poor-quality data in a moment. However, let’s make sure not to get caught in the “quality trap,” because the ultimate goal of DQM is not to create subjective notions of what “high-quality” data is.

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SAP Datasphere review: turning data from a technical problem to a business data product.

Jen Stirrup

It can give business-oriented data strategy for business leaders to help drive better business decisions and ROI. It can also increase productivity by enabling the business to find the data they need when the business teams need it. It helps users to work with the data more effectively and reduces the need for technical support.

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Biggest Trends in Data Visualization Taking Shape in 2022

Smart Data Collective

Some solutions provide read and write access to any type of source and information, advanced integration, security capabilities and metadata management that help achieve virtual and high-performance Data Services in real-time, cache or batch mode. How does Data Virtualization complement Data Warehousing and SOA Architectures?

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Using DataOps to Drive Agility and Business Value

DataKitchen

Previously we would have a very laborious data warehouse or data mart initiative and it may take a very long time and have a large price tag. Bergh added, “ DataOps is part of the data fabric. You should use DataOps principles to build and iterate and continuously improve your Data Fabric. Design for measurability.

Metrics 211
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How ActionIQ built a truly composable customer data platform using Amazon Redshift

AWS Big Data

ActionIQ is a leading composable customer data (CDP) platform designed for enterprise brands to grow faster and deliver meaningful experiences for their customers. This post will demonstrate how ActionIQ built a connector for Amazon Redshift to tap directly into your data warehouse and deliver a secure, zero-copy CDP.