Course Summary
This course is designed to introduce students to the fundamentals of data management, including data modeling, storage, and retrieval.Key Learning Points
- Learn how to design and implement a data model that is efficient and effective for your organization
- Gain a deeper understanding of how to store and retrieve data in a way that is scalable and secure
- Explore techniques for managing and analyzing large datasets, including data warehousing and data mining
Related Topics for further study
Learning Outcomes
- Design and implement a data model that meets the needs of your organization
- Store and retrieve data efficiently and securely
- Analyze large datasets using data warehousing and data mining techniques
Prerequisites or good to have knowledge before taking this course
- Basic understanding of SQL
- Familiarity with data analysis techniques
Course Difficulty Level
IntermediateCourse Format
- Self-paced
- Online
- Video lectures
- Quizzes and assignments
Similar Courses
- Introduction to Big Data
- Data Science Essentials
Related Education Paths
- Data Management and Warehousing Specialization
- Data Science Specialization
- Master of Science in Data Science
Notable People in This Field
- Tim O'Reilly
- Hilary Mason
- Kirk Borne
Related Books
Description
This course will provide learners with an introduction to research data management and sharing. After completing this course, learners will understand the diversity of data and their management needs across the research data lifecycle, be able to identify the components of good data management plans, and be familiar with best practices for working with data including the organization, documentation, and storage and security of data. Learners will also understand the impetus and importance of archiving and sharing data as well as how to assess the trustworthiness of repositories.
Outline
- Understanding Research Data
- Welcome
- Research Data Defined
- Types of Data and Metadata
- Research Data Lifecycle
- Why Manage Data?
- Data Management Stakeholders
- Data Management Across the Research Lifecycle
- "What Are Data?"
- "Why is Data Management Important?"
- Summary & Additional Resources
- Summary & Additional Resources
- Understanding Research Data
- Data Management Planning
- Introduction to Data Management Plans
- Funding Agency Requirements
- Data Management Plan Content
- Data Management Planning Tools
- Summary & Additional Resources
- Data Management Planning
- Working with Data
- Good File Management in Research
- File Naming
- Versioning
- File Formats
- Data Transformations
- Documentation
- Data Citation
- Storage
- Backup
- Data Security
- Encryption
- Interview - Natalia Calanzani
- Interview - Shaun Bevan
- "How does good data management add value to research?"
- "Do you think data sharing helps to reduce waste and increase transparency of research?"
- Summary & Additional Resources
- Summary & Additional Resources
- Summary & Additional Resources
- Summary & Additional Resources
- Organizing Data
- File Formats and Transformations
- Documentation and Data Citation
- Storage and Security
- Working with Data
- Sharing Data
- Benefits of Sharing
- Challenges to Sharing
- Data Citations
- Protecting Confidentiality (Part 1)
- Protecting Confidentiality (Part 2)
- Intellectual Property and Data Ownership
- Access
- "What Are the Benefits of Sharing Data?"
- "What Are the Drawbacks of Sharing Data?"
- Summary & Additional Resources
- Summary & Additional Resources
- Sharing Data
- Archiving Data
- Why Archive Data?
- Authenticity and Integrity
- Metadata
- Demonstrating Trustworthiness
- Data Curation Standards and Best Practices (Part 1)
- Data Curation Standards and Best Practices (Part 2)
- "Why is Archiving Data Important?"
- "Why is Digital Preservation Important?"
- Conclusion
- Summary & Additional Resources
- Summary & Additional Resources
- Archiving Data
Summary of User Reviews
The Data Management course on Coursera has received positive reviews from students. Many users found the course to be comprehensive, informative, and well-structured. The course provides a great foundation for anyone interested in data management.Key Aspect Users Liked About This Course
Comprehensive course materialPros from User Reviews
- Course content is well-structured and easy to follow
- Instructors are knowledgeable and engaging
- Course provides a great foundation for data management
- Assignments and quizzes are challenging but fair
Cons from User Reviews
- Some users found the course to be too basic
- Course may not be suitable for those with advanced knowledge of data management
- Course may require a significant time commitment
- Some users found the course to be too theoretical
Helen Tibbo
4.7 Raiting
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