Data Quality Framework & Methodologies for Data Citizens

Web Reference: Why Data Management Plans (DMPs) are required. The Belmont Forum and BiodivERsA support international transdisciplinary research with the goal of providing knowledge for understanding, mitigating and adapting to global environmental change. To meet this challenge, the Belmont Forum and BiodivERsA emphasize open sharing of research data to stimulate new approaches to the collection, analysis ... Several actions related to the data lifecycle, such as data discovery, do require an understanding of the data, technology, and information infrastructures that may result from information science education. A full Data and Digital Outputs Management Plan for an awarded Belmont Forum project is a living, actively updated document that describes the data management life cycle for the data and other digital outputs to be collected, reused, processed, and/or generated. As part of making research data open by default, findable, accessible, interoperable, and reusable (FAIR), the Plan should elaborate ...

YouTube Excerpt: This webinar explores managing data quality through governance, strategy, and implementation. Howard Diesel emphasizes assessments, documentation, and the role of data quality in fostering a culture of accuracy and business value. Find our training offerings here: https://modelwaresystemsse.wixsite.com/cdmp-certification Please join our Meetup Group to be notified of upcoming webinars: https://www.meetup.com/DAMA-SA-Data-Management-Meetup/ Connect with us on LinkedIn to avoid missing any upcoming events! Howard Diesel LinkedIn: https://www.linkedin.com/in/howarddiesel-cdmp-dmbok-modelwaresystems/ Modelware Systems LinkedIn: https://www.linkedin.com/company/modelware-systems Join our Data management community here: https://the-data-hive.mn.co/share/w_sdmogS6w4tKJo4?utm_source=manual OR Email Debbie: social@modelwaresystems.com 00:00:00 Start Webinar 00:01:44 Data quality management and implementation cycle in a professional setting 00:05:20 Data Governance and Data Quality Strategy 00:07:29 Data Governance and Implementation Framework 00:10:50 Areas to Compare in Data Quality Analysis and Improvement 00:13:30 Notes on Data Driven and Process Driven Approaches 00:17:02 Quality dimensions, frameworks, and information systems 00:20:42 Implementation Cycle and Data Quality Assessment 00:23:26 Importance and Documentation of Data Quality Expectations 00:25:55 Implementing the DM AIC process for risk assessment and remediation 00:29:36 Defining and Analyzing Quality, Validating Measurement, and Control 00:34:58 Quality Control and Process Improvement Techniques 00:38:32 Analysis of Deliverables and Frameworks in Project Evaluation 00:41:31 Howard Diesel discusses data analysis and strategy implementation 00:43:34 Steps in Ensuring Data Quality and Implementation 00:46:06 Data Quality Assessment Process 00:50:51 Root Cause Analysis and Documentation Process 00:53:35 Data Analysis Techniques and Tools 00:55:59 Discussion on Outliers and Data Analysis 00:59:33 Prioritizing Data Management Approaches 01:01:57 Discussion on decision making and decision inventory 01:06:21 The Importance of Well-Defined Outputs, Data Quality, and Cost Metrics in Data Governance 01:10:33 Error Rates and Quality Maintenance in Data Analysis 01:12:29 Achieving 100% Data Accuracy and its Value to Business 01:15:44 Importance of Data Quality in Company Culture African Data Management Community Forum 2023-07-13 #DataQualityManagement

This webinar explores managing data quality through governance, strategy, and implementation. Howard Diesel emphasizes assessments, documentation,...

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