Data management is a rather complex process that requires a lot of experience. Professional data analysts must constantly update algorithms to meet the job.
Are you looking for a quality data management course at a reasonable price? Don’t know how to start from SQL, Python, or SAS?
I will present to you the top ten data management courses. These courses are free with helpful information to help you succeed in this challenging field.
I have taken some introductory and intermediate-level data management courses. Here are the courses I appreciate the most because of their easy-to-understand knowledge transfer and effective practice integration.
1. Database Management Essentials
Specifications:
- Difficulty: Intermediate.
- Duration: 106 hours to complete.
- Price: Free.
- Provider: University of Colorado.
Course’s Highlights
Database Management Essentials provides the basic knowledge. It is suitable for those working in the data storage and business intelligence industries.
After about two months, I’ve learned about creating a relational database, writing a PRO statement, or creating an ERD.
This knowledge is pretty basic and easy to understand, but it helps me practice with Oracle, MySQL, and PostgreSQL.
In particular, I was impressed with the last lesson: the query formula extends to SQL. This lesson helped me expand my problem-solving skills. It also taught me how to use the UNION operator and write SQL modification statements.
This course can provide an easy-to-understand foundation for many learners.
However, it requires you to complete concept tests before starting. So, for those who do not have too much experience, this one can be a challenge.
Enroll Here: https://www.coursera.org/learn/database-management
Pros
- Easy to understand.
- Provide basic background knowledge
- Suitable for many different objects.
- Expand your problem-solving skills.
- Expertise in extensive query formulas with SQL.
Cons
- You must do concept tests before starting.
2. Research Data Management and Sharing
Specifications:
- Difficulty: Beginner.
- Duration: 14 hours to complete.
- Price: Free.
- Provider: The University of Edinburgh.
Course’s Highlights
This course will focus on introducing data management and sharing in research.
After completing the course, I’ve understood data diversity and the importance of research data management. The knowledge brought by the course helped me to plan good data management.
I also learned many ways to organize, store, and secure data. Efficient data management helps optimize research results and create a reliable repository.
Research Data Management and Sharing is the course that researchers should take. It helps understand research data, plan data management, and store data.
Enroll Here: https://www.coursera.org/learn/data-management
Pros
- Help to understand research data.
- Support planning data management.
- Support the process of optimizing research results.
- Suitable for managing and sharing, and storing data.
- Explain the principles of data organization, storage, and security.
Cons
- Not suitable for beginners
3. Data Management Is the Foundation of Digital Transformation
Specifications:
- Difficulty: Intermediate.
- Duration: 43mins.
- Price: $29 per month after a 10-day trial.
- Provider: Big Data LDN.
Course’s Highlights
In digital transformation, data governance and management play a leading role in business. And Data Management Is the Foundation of Digital Transformation is one of those practical courses that any business professional should consider.
I appreciate its regular updates. The latest trends affecting business, and data, such as Customer 360, Big Data, and ABM, are all mentioned in the lectures.
Although the course duration is relatively short, it still details the three primary stages of digital transformation. It also includes fascinating insights into master data, governance linkages, and the future of business.
This course focuses on providing theoretical knowledge. So, it does not include questions to reinforce knowledge or practice questions. It is also an unfortunate drawback for such a knowledge-rich course.
Enroll Here: Currently Unavailable
Pros
- Highly up-to-date.
- The duration is short.
- Provide easy-to-understand theory
- Focus on data application for business.
- Refers to 3 stages of digital transformation
Cons
- Only focus on theoretical knowledge
4. Big Data Specialization
Specifications:
- Difficulty: Beginner.
- Duration: Approximately 8 months to complete.
- Price: University of California San Diego.
- Provider: Free.
Course’s Highlights
Big data is now impacting every sector and industry. If you are interested in this field, enroll in the Big Data Specialization course.
The impressive point is that it provides pretty detailed knowledge. It gave me easy-to-understand big data’s benefits and related tools.
It not only provides knowledge but also includes a lot of practice exercises. These exercises vary in difficulty, but most require no programming experience.
I was incredibly impressed with the Capstone project at the end of the course. It needed to analyze the simulation dataset and build the big data ecosystem with the earlier tools.
Big Data Specialization is an introductory course for anyone interested in data management with no prior programming knowledge.
The only downside is the extended learning time. Sometimes beginners are only interested in the fastest courses that provide the straightforward command.
Enroll Here: https://www.coursera.org/specializations/big-data
Pros
- Lots of practice exercises.
- An introduction to many valuable tools.
- Provide all knowledge related to big data
- Train your ability to analyze simulated data sets.
- The final project builds a big data ecosystem.
Cons
- Long study time
5. Learn SQL
Specifications:
- Difficulty: Beginner.
- Duration: 8 hours to complete.
- Price: Free.
- Provider: Codecademy.
Course’s Highlights
SQL is one of the ideal tools for data analysis. And go to Learn SQL; you will learn how to master this tool.
This course teaches me how to manage large data sets and analyze actual data. I applied the skills I learned to work more effectively with data, even though the major didn’t have much to do with technology.
This course consists of four lessons, which take about eight hours. During this time, I simultaneously completed four questions and five projects.
This workload is not overwhelming for me. Yet, for a beginner, I think it can be a challenge that is not easy to overcome.
Enroll Here: https://www.codecademy.com/learn/learn-sql
Pros
- Streamlined study time
- Learn to master SQL.
- Many exciting projects.
- Teach how to manage large data sets.
- Support working more efficiently with data.
Cons
- Many projects and assignments in a short time.
6. Digital Transformation and Data Management Masterclass
Specifications:
- Difficulty: Beginner.
- Duration: 1h 34m.
- Price: Free.
- Provider: SkillShare.
Course’s Highlights
I was interested in the chief data office but couldn’t find these novel knowledge update courses. It was only when I enrolled in the Digital Transformation and Data Management Masterclass that I gained relevant knowledge.
After the course, I also learned how to do end-to-end data analysis. More specifically, learning is no longer too difficult for me when taking some other courses related to Blockchain analysis or robot automation.
My only complaint is that it is presented as requiring no entry. In practice, however, I only encourage students with a technical background to sign up for this course. If you’re just interested in how the head data office structure works, you might want to consider the easier-to-understand ones.
Enroll Here: Currently Unavailable
Pros
- Fast learning time.
- End-to-end data analysis.
- New and interesting lectures
- Provide knowledge of chief data
- Support knowledge about Blockchain and automation.
Cons
- Not too suitable for beginners.
7. Data Management for Clinical Research
Specifications:
- Difficulty: Beginner.
- Duration: 17 hours to complete.
- Price: Free.
- Provider: Vanderbilt University.
Course’s Highlights
As the name suggests, this course provides knowledge and practical exercises related to data analysis in clinical research.
Its lessons are pretty stimulating with vital concepts and effective data research methods. This course provides a new understanding of data in the clinical field.
However, it should still update some technical knowledge. Its pace is also quite fast, not too suitable for beginners.
Enroll Here: https://www.coursera.org/learn/clinical-data-management
Pros
- Easy to understand.
- Arousing interest in learning
- It covers many essential concepts
- Specialized in clinical data research.
- Describe in detail the methods of data research.
Cons
- The course pacing is too fast.
8. Data Management and Visualization
Specifications
- Difficulty: Beginner.
- Duration: 12 hours to complete.
- Price: Free.
- Provider: Wesleyan University.
Course’s Highlights
Data is the best method to visualize any report or analysis. Data Management and Visualization is the course to help you manage data in an intuitive way.
Even the first lessons raised quite a few questions related to research work, describing variables and relationships.
The value I get back after the course is also quite remarkable. I can use data analysis tools like SAS and Python fluently.
Operations such as handling missing data and graphs can’t be difficult for me either. I appreciated the course’s lesson on data visualization as graphs.
Yet, while learning, I wish it provided more supplemental material instead of little video tutorials.
Enroll Here: https://www.coursera.org/learn/data-visualization
Pros
- Bring many core values.
- Get familiar with data analysis tools.
- Teaches in detail how to analyze data.
- Ask a variety of research questions.
- Many lectures on data visualization as graphs.
Cons
- Lack of additional documentation.
9. IBM Data Science Professional Certificate
Specifications:
- Difficulty: Beginner.
- Duration: 11 months to complete.
- Price: Free.
- Provider: IBM.
Course’s Highlights
The IBM Data Science Professional Certificate is the most practical course I’ve ever taken. I always encourage those interested in data science and career development in the field to sign up for the course.
Instructors teach knowledge related to open-source tools and libraries, Python and SQL. Its lessons involve hands-on exercises, helping learners master data.
One particular advantage that interests me in this course is that it also provides a digital badge from IBM upon completion. It is an outstanding advantage over conventional methods that only grant certificates of completion.
The IBM Data Science Professional Certificate has a hefty emphasis on practice. In particular, its knowledge volume is almost equivalent to 12 university credits.
Therefore, the journey to conquer the course will be pretty tricky, even for experienced people.
Enroll Here: https://www.coursera.org/professional-certificates/ibm-data-science
Pros
- Suitable for data scientists.
- Granted digital badges from IBM.
- Teaching a lot of knowledge about open source
- Many practical exercises are highly applicable.
Cons
- Practical lectures are hard to follow.
10. Business Analytics Specialization
Specifications:
- Difficulty: Beginner.
- Duration: 6 months to complete.
- Price: Free.
- Provider: University of Pennsylvania.
Course’s Highlights
Business Analytics Specialization is a course for analysts working in business and finance. Its lessons all revolve around the field of analysis. When taking the course, I learned much about customer analysis, operations, and accounting.
At the end of the course, I had to complete the Capstone project, which required synthesizing all the knowledge learned to serve business analysis purposes.
Business Analytics Specialization is quite a valuable course for those working in the business field. It pretty much focused on analysis rather than management.
Enroll Here: https://www.coursera.org/specializations/business-analytics
Pros
- In-depth lectures
- Many interesting projects.
- Useful for large enterprises.
- Easily apply learned knowledge.
- Basic knowledge and easy to understand.
Cons
- Focus on data analysis instead of management.
Learning Guide
Many courses teach data management for you to enroll in. But not every system is functional enough. Here are some tips for you to consider.
- Course Level: If you’ve never studied data management, start with the most basic-level courses. Intermediate or advanced techniques will be suitable only for professionals wishing to develop a career in this field.
- Time to complete the course: Online data management courses have flexible study times. If you don’t have much time, look for short periods that teach in-depth a particular aspect of data management.
FAQs
Here are some frequently asked questions related to data management courses. You can refer to the answers to understand more about these courses.
What do you learn in the data management course?
The most basic knowledge in data governance courses is creating, accessing, and updating data.
Why should I learn data management?
You should learn how to manage data to reduce data setup and usage errors.
With a regularly updated data system, the company will better respond to the changes in the market and customers.
What are the requirements for data management?
The essential requirements for data management are processing large data volumes, automatic data quality assurance, and support for the development of science and technology.
What are data management skills?
Data management is the skill of managing and using information effectively.
What is a data management tool?
Management tools will assist in developing and monitoring an organization’s data analysis and practices.
Conclusion
In my experience, people new to data management need introductory courses like Database Management Essentials. Meanwhile, business professionals should join Business Analytics Specialization to serve their field.
With each different need, you will have your options. Hopefully, the course list I introduced above can meet your work needs.
Thank you for your interest in the article!