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RESEARCH & RESOURCES

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TDWI Checklist Report | Modern Data Integration and Data Quality Practices for Digital Business Requirements: Download

Data integration and data quality are technical disciplines, but there’s more required than technology. DI/DQ must also coordinate with and align to business processes and goals. The assumption is that businesspeople should be involved in defining quality metrics, standards, and process rules. This report will drill down into the modern best practices associated with emerging data sources, data platforms, and business use cases.

File Type: .pdf File Size: 219 KB Duration: 9 pages


 

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TDWI Data Management Maturity Model Assessment Guide

TDWI Data Quality Maturity Model Assessment Guide: Asset

This TDWI Data Management Maturity Model Guide is designed to help you understand the phases of maturity in data management as well as help you interpret your scores.


TDWI Data Management Maturity Model Assessment

TDWI Data Quality Maturity Model Assessment

TDWI created the Data Quality Maturity Model and Assessment to help organizations understand the maturity of their data quality effort and determine what steps they must take to improve and expand their data quality programs.


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Digital Dialogue | Ensuring Excellence in AI: The Critical Role of Data Governance: Asset

This recent webinar covered a range of topics including pillars for AI governance, tools to help, and the importance of automation. Download the recap now.