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4.1: Introduction to Data and Databases

  • Page ID
    9766
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    Introduction

    You have already been introduced to the first two components of information systems: hardware and software. However, those two components by themselves do not make a computer useful. Imagine if you turned on a computer, started typing a document, but could not save a document. Imagine if you opened your music app, but there was no music to play. Imagine opening a web browser, but there were no web pages. Without data, hardware and software are not very useful! Data is the third component of an information system.

    Data, Information, Knowledge, and Wisdom

    Behaviorism_1.gif
    Figure \(\PageIndex{1}\): Data to Wisdom. Image by David T. Bourgeois is licensed under CC BY-SA 2.0

    Data is raw bits and pieces of information with no context, for example, your driver's license or your first name. The information system helps organize this information in a designed systematic manner to be useful to the user. The users can be individuals or businesses. This organized collection of interrelated data is called a database. The two highest levels of data are quantitative or qualitative. To know which to use depends on the question to be answered and the available resources. Quantitative data is numeric, the result of a measurement, count, or some other mathematical calculation. A quantitative example would be how many 5th graders attended music camp this summer. Qualitative data consist of words, descriptions, and narratives. A qualitative example would be a camper wearing a red tee-shirt. A number can be considered qualitative as well. If I tell you my favorite number is 5, that is qualitative data because it is descriptive, not the result of a measurement or mathematical calculation.

    When using qualitative data and quantitative data, we need to understand the context of its use. There are advantages and disadvantages to each. This table encapsulates the advantages and disadvantages when gathering data.

    Qualitative Data

    Advantages

    Disadvantages

    Quantitative Data

    Advantages

    Disadvantages

    By itself, data is a collection of components waiting to be analyzed. To be useful, it needs to be given context. Users and designers create meaning as they collect, reference, and organize the data. Information typically involves manipulating raw data to obtain an indication of magnitude, trends, and patterns in the data for a purpose. Returning to the example above, if I told you that “15, 23, 14, and 85″ are the numbers of students that had registered for an upcoming camp, that would be information. By adding the context – that the numbers represent the count of students registering for specific classes – I have added context to data which now is information. Information is data that has been analyzed, processed, structured, and avails itself to be useful.

    Once we collect and understand the data, we put it into context, aggregate it, and analyze it. We then have information, and we can use it to make decisions for the individual and our organization. We can say that this consumption of information produces knowledge. . Knowledge can be viewed as information that facilitates action. This knowledge can be used to make decisions, set policies, and even spark innovation.

    The final step up the information ladder is the step from knowledge (knowing a lot about a topic) to wisdom.

    Wisdom is experience coupled with understanding and insight. We can say that someone has wisdom when combining their knowledge and experience to produce a deeper understanding of a topic. It often takes many years to develop wisdom on a particular topic and requires patience and expertise.

    Behaviorism_1.gif
    Figure \(\PageIndex{2}\): Data Shown on Monitors. Image by Gerd Altmann from Pixabay is licensed under CC-BY-SA 2.0