• 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.

    • 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.

      • 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.

      • 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.

      • 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. 

    • 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.

    • 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. 

      • 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.

      • 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.

      • 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. 

      • 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.

    • Study Guide: Unit 1

      We recommend reviewing this Study Guide before taking the Unit 1 Assessment.

    • Unit 1 Assessment

      • Receive a grade