Remove Data Governance Remove Data Processing Remove Metrics
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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

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

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7 types of tech debt that could cripple your business

CIO Business Intelligence

For this reason, organizations with significant data debt may find pursuing many gen AI opportunities more challenging and risky. What CIOs can do: Avoid and reduce data debt by incorporating data governance and analytics responsibilities in agile data teams , implementing data observability , and developing data quality metrics.

Risk 140
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The DataOps Vendor Landscape, 2021

DataKitchen

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . A complete DataOps program will have a unified, system-wide view of process metrics using a common data store.

Testing 304
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Cloudera AI Inference Service Enables Easy Integration and Deployment of GenAI Into Your Production Environments

Cloudera

It is a powerful deployment environment that enables you to integrate and deploy generative AI (GenAI) and predictive models into your production environments, incorporating Cloudera’s enterprise-grade security, privacy, and data governance. Teams can analyze the data using any BI tool for model monitoring and governance purposes.

Metrics 73
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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.

IoT 111
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How to Deliver Data Quality with Data Governance: Ryan Doupe, CDO of American Fidelity, 9-Step Process

Alation

In Ryan’s “9-Step Process for Better Data Quality” he discussed the processes for generating data that business leaders consider trustworthy. To be clear, data quality is one of several types of data governance as defined by Gartner and the Data Governance Institute. Step 7: Data Quality Metrics.

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The 10 Essential SaaS Trends You Should Watch Out For In 2020

datapine

Vertical SaaS also provides the following benefits: Customer intelligence: Enables businesses to obtain industry-specific customer data and intelligence, which plays a critical role in gaining customer-focused insights. More software providers will adopt a mobile-first mentality, optimizing their offerings to suit a host of mobile devices.

Software 314