Unit 1: Introduction to Data Management
Data management describes the process of collecting, storing, and analyzing data. Organizations use data management to process business transactions, measure day-to-day operations, and for future decision-making. As a result, decision-makers can rely on data to make choices and take actions that benefit the organization. This unit will cover data management and the overall practice of accessing, collecting, and using data securely, efficiently, and cost-effectively. Data management aims to optimize data use within organizations and other agencies within the bounds of policy and regulation.
Completing this unit should take you approximately 9 hours.
Upon successful completion of this unit, you will be able to:
- identify the value and relative importance of data management to the success of a project;
- explain the need for managing/sharing data and identify relevant public policies;
- use the lifecycle continuum to manage and preserve data; and
- explain what research data is and how it is collected and stored.
1.1: Data Management
Data can reveal essential insights into goals and outcomes. This requires proper management because data insights are useful for decision-making. Data management has become an essential administrative function within an organization. This function includes acquiring, storing, protecting, validating, and processing data. Data management is a valuable resource that develops and improves organizational operations.
It is critical for every organization to have a plan to manage data. This is known as a data management plan (DMP). DMPs are documents that describe how to acquire, manage, analyze, and store data. Imagine how expensive it could be if an organization lost, misplaced, or mishandled acquired data. Therefore, since data is a valuable resource for decision-making, proper data management ensures that data is readily available for operational and strategic planning.
Data is a valuable resource. Therefore, data management has become an important administrative function. An effective data management plan should govern how to acquire, store, and secure organizational data. Remember, reliable data management plans depend on your ability to identify the value added to operational and strategic planning.
Read this chapter. Focus on the differences between data, information, and knowledge; why database technology for data resource management is important; and the role of database management systems. Answer the study questions at the end of the chapter. Why is data management valuable to the success of an organization? What are some common weaknesses in data resource management? How can they be mitigated?
1.1.1: Data Lifecycle Management
Organizations use information systems to acquire, store, and secure data. Management of the data lifecycle is essential for proper data management. A lifecycle is a policy-based approach for how to manage the flow of data stored within information systems. Therefore, data lifecycle management (DLM) is a sequence of stages a unit of data goes through, from initial acquisition to archival or deletion.
There are a few rules to consider before establishing data management lifecycles. (1) Newly acquired data and stored data will be accessed more frequently. This is normally stored in more expensive and faster information systems. (2) Likewise, less critical data is typically stored in less expensive and slower platforms. Apply both rules to establishing and managing data lifecycles.
Read this lesson. Pay attention to the lifecycle (process) of data sets. Answer the questions in this lesson.
Data lifecycle management (DLM) is the policy or process that governs organizational data use. You learned that data management is an administrative function and DLM is a process to manage and preserve that data. Remember, good DLM includes all the phases of the data lifecycle. This is essential to data-driven decisions and actions taken by organizations daily.
1.1.2: Value within Data Management
Data lifecycle management (DLM) is a part of the data management plan (DMP). Therefore, it is important to maintain DLM standards since data is considered a valuable resource to organizations. Can you imagine the loss in revenue or labor hours due to poor DLM? How about the poor decisions made based on unreliable data?
Even with a process and plan in place, an organization's ability to govern data will ensure value and integrity within stored data. Data governance is a continuous process of frameworks to improve data quality and increase confidence in outcomes revealed from the data analysis.
Data is collected, stored, and shared throughout every department within an organization. Data is continuously shared and verified in order to reveal new events and predict outcomes. Data governance provides the framework to improve data management and sharing. This continuous framework evaluates data by establishing a data lifecycle.
Watch this webinar, and pay attention to data governance in relation to a continuous process, improving data quality, and the benefits of governing data. What are potential pitfalls if no one is responsible for governing data? What steps can you apply to ensure data governance is successful? How would you apply data governance with an organizational process model?
1.1.3: Research Data
Information that is collected, observed, or created to validate research findings is called research data. Research data comes in various forms and is gathered using different methodologies. Some people may view data-driven research as only for science. While others think it is just a collection of numbers on a spreadsheet. However, research data is collected and used in multiple forms. For example, videos, diaries, artifacts, and images.
Watch this video on managing research data. Focus on the risks associated with not managing research data, the importance of sharing research data, and the challenges of both sharing and managing research data.
Research data is collected and stored daily in various forms. Because data is a valuable resource, it requires proper management and sharing between organizations. Remember, data management ensures reliable information and protects the integrity of data within your organization. Be sure you have a detailed plan on how to manage research data.
Watch this video on the basics of research data management. Use what you learned about the importance and challenges of sharing and managing data to follow the data lifecycle in the video. Where can you locate relevant standards for managing research data? Why is it important for data to be as available as possible? What are the benefits of dataset licensing?
1.2: Data Management Plans
Data management plans (DMP) are written documents that describe the data an organization expects to acquire during a research or other type of project. The DMP provides the framework for managing, analyzing, and storing the data used in the project. It also includes the mechanisms an organization will use to share and store this data.
Because the process of doing research may require adjustments, DMP is a living document. This means that you may alter the plan as needed throughout the course of the research changes. Remember, anytime a research plan changes, you must review the DMP to ensure it still meets the needs of the research.
Watch this video on DMP. Pay attention to the definition, questions that develop a DMP, and content that make up a DMP. Remember, you will more likely share research data. Therefore, take notes on the advantages of a good data management plan.
Study the Data Management Plans section of the US Geological Survey. Notice the templates and examples that are provided. How would you evaluate these data management plans? How could you apply one of the templates to develop your own DMP for a situation from your professional experience?
Now that you can describe and explain DMP, let's cover a few careers within the data management field.
1.3: Data Management Careers
Organizations use data more than ever to drive decision-making. However, most organizations only capture a fraction of the value hidden within collected data. Because data can be managed and shared, different departments require people with special skill sets to reveal valuable insights from collected data.
Watch this webinar on the evolving role of the data architect. Pay attention to the opportunities that exist for data professionals working for data-driven organizations. Take note of the various organizations that utilize data for improvement and transformation.
1.3.1: Data Consultant
Data consultants work in almost every industry, including computing, industrial, and retail. This list includes any organization that collects, stores, and requires recommendations on how to improve data use.
Read this summary report for data consultants/architects. Familiarize yourself with the knowledge, skills, abilities, and education level organizations look for when seeking to hire a data consultant.
1.3.2: Operations Analyst
Operations analysts develop and implement practices to improve organizational performance. Operation analyst job descriptions may vary by organization. However, operation analysts are all responsible for identifying procedures and creating plans to improve processes or correct shortcomings.
Read this summary report for operations analysts. Familiarize yourself with the knowledge, skills, abilities, and education level organizations look for when seeking to hire operations analysts.
1.3.3: IT Systems Analyst
IT Systems analysts are also known as computer systems analysts. They are responsible for ensuring an organization's technology runs efficiently and effectively. Due to the rise in organizations using technology, computer systems analysts are needed in virtually every industry.
Read this summary report for an IT Systems analyst. Familiarize yourself with the knowledge, skills, abilities, and education level organizations look for when seeking to hire IT systems analysts.
1.3.4: Database Administrator
A database administrator is also known as a DBA. DBAs are data-driven problem solvers. They oversee software and hardware that stores data. The primary responsibility is to ensure that data is housed in easy-to-find, secured, and backed-up systems.
Read this summary report for DBAs. Familiarize yourself with the knowledge, skills, abilities, and education level organizations look for when seeking to hire database administrators.
Remember, proper data management and data lifecycle management add value to any organization. It is becoming easier to share and manage data due to advancements in technology. Therefore, it is important to have data management and data lifecycle management processes. This produces integrity in standards that effectively collect, analyze, and share data.
Study Guide: Unit 1
We recommend reviewing this Study Guide before taking the Unit 1 Assessment.
Unit 1 Assessment
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Take this assessment to see how well you understood this unit.
- This assessment does not count towards your grade. It is just for practice!
- You will see the correct answers when you submit your answers. Use this to help you study for the final exam!
- You can take this assessment as many times as you want, whenever you want.