In this tutorial, we’ll describe data, how data can be transformed into information. Mainly, we’ll discuss their differences with examples.
2. Why Do We Need to Understand Data and Information?
Data and information are two widely used concepts in computer science or computing. While they are closely related concepts, they have different uses in the real sense. Data is raw and unprocessed facts, whereas information is processed data. Understanding these two concepts is vital, as we often use them in computer science.
Data and information are interesting topics in computing because they’re the building blocks in modern technology and useful in several areas including statistics, engineering, data science and computational biology. The amount of data generated in today’s world is in vast quantities and its management and processing have become crucial for accurate decision-making.
Data and information take various forms, such as text, images, structured and unstructured data, video, among many others.
Data refers to raw facts or figures. These facts could be about people, locations, among other things. Data can occur in various forms such as numbers, texts, and many other forms.
Example of data include:
- Numbers: 21, 22, 24, 27, 27
- Text: Giorgia Meloni, Katrín Jakobsdóttir, Irakli Garibashvili, Élisabeth Borne
3.1. Data Collection Source
Data collection is done based on its purpose. It is important to know the source of data before use. We can collect data in two sources:
- Primary sources such as the use of questionnaire, interview, and observation
- Secondary sources such as government statistics, libraries and online sources
Information can simply be said to be processed data that has been given meaning. The data has been assigned with a context to make it meaningful. Given these numbers: 21, 22, 24, 27, 27; if we assign context to these bunch of numbers, then it will make it meaningful:
Information is a result of processing or transforming data into a useful form. We understand information because it’s more organized and has context. Information can be in the form of graphs, tables, or videos.
5. Differences Between Data and Information
Data and information have been used interchangeably but have different meanings. While data is in unorganized form, information is organized:
6. Real Examples on Data and Information
Data becomes information when it is processed and transformed to take actionable form. We use data transformation in real areas including:
- weather forecast
- medical diagnosis
- social media analytics
6.1. Weather Forecast
In weather forecasting, data is collected from sensors, satellites and weather stations. The collected data is processed using computer algorithms to create weather forecasts. We can then communicate this information to the public in easy-to-understand forms, such as graphical representation and tables.
6.2. Medical Diagnosis
Medical tests generate a vast amount of data that can be analyzed to aid in the diagnosis and treatment of diseases. For example, when we collect data on blood tests, it can be processed to help us identify illnesses.
6.3. Social Media Analytics
Social media platforms such as Facebook and Instagram generate massive amounts of data including user likes, comments, followers, and shares. We can analyze and transform this data into useful information to help understand the social media performance of users.
In this article, we describe data and how it can lead to information. While these two concepts may appear to be similar, one is dependent on the other. Data and information are fascinating and important topics in computer science, because they form the core of modern technology.
When data is collected, we need to refine or process the data by assigning context to it. When we put data into context, it becomes meaningful and informative. Both data and information are widely used in several areas or fields due to their significant impact.