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Learn how to design a data governance solution that meets an enterprise’s needs.
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Learn how to design a data governance solution that meets a company’s needs. First, learn about the different types of metadata and how to build a metadata management system, enterprise data model, and enterprise data catalog. Next, dive deep into data profiling, remediation options for data quality, data quality scores, thresholds, dashboards, exception, and data trend reports. Finally, learn the concepts of master data, golden record creation, master data management architectures, and master data governance processes.
Basic SQL, ETL, Relational Database Basics
Understand what data governance is and its importance and learn about the different disciplines of data governance. Understand the different stakeholders involved in data governance projects.
Understand the different types of metadata as well as the components and capabilities of a metadata management system. Create conceptual and logical enterprise data models and create an enterprise data catalog.
Perform data profiling using various techniques using data quality dimensions. Identify remediation options for data quality issues. Measure data quality using data quality scores and thresholds. Monitor data quality using dashboards, exception, and trend reports.
Understand the concepts of master data and golden record. Understand different types of master data management architectures. Create a golden record using various match and merge techniques. Understand data governance processes for authoring, monitoring, and approval of master data.
Implement data governance solutions for an online shoe reseller to better manage their data now and in the future. Create an enterprise data model that provides a holistic view of all the data in their systems. Next document the metadata in an enterprise data catalog and profile the data in their systems to identify data quality issues, suggest remediation strategies for each of these issues, and design a data quality dashboard. Finally, you will sketch out a proposed MDM implementation architecture, define a set of matching rules for the creation of customer and item master data, and define the data governance roles and responsibilities that are necessary to oversee this data governance initiative.
With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.
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Vijaya is the Founder and Principal Data Architect for Great View Data Corp., which provides Data Architecture consulting and implementation services. Vijaya has extensive experience with creating architecture strategy and roadmaps, establishing frameworks and best practices, and Data Management.
Learn how to design a data governance solution that meets an enterprise’s needs.
On average, successful students take 1 month to complete this program.
No. This Course accepts all applicants regardless of experience and specific background.
Successful learners should have intermediate Python skills including: Data structures and data types, Control flow using for, while, and if statements, Jupyter notebooks, pandas and NumPy, Machine learning frameworks, Calculus, and Linear algebra.
This course is comprised of content and curriculum to support one project. We estimate that students can complete the program in one month.
The project will be reviewed by the Udacity reviewer network and platform. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.
Access to this course runs for the length of time specified in the payment card above. If you do not graduate within that time period, you will continue learning with month to month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our programs.
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Learners will need access to the internet and a 64 bit computer. No additional software or hardware is required.