Information: Describing Data and Statistics and Their Role in Organizational Decision-Making
Overview
This paper explores the relationship between data, statistics, and information, arguing that information is the meaningful output that results from processing and analyzing raw data. The author uses Big Data as a contemporary example to demonstrate how raw data becomes practically useful once computationally analyzed to reveal patterns and trends that inform organizational decision-making.
What this coursework covers
- Introduction defining information as the key concept in understanding data and statistics
- Explanation of how data and statistics lack meaning unless converted into understandable patterns and trends
- Big Data example demonstrating the transformation of raw data into actionable information for business and government
Preview
Information: Describing Data and Statistics
Your Name
Department of ABC, University – Whitewater
ABC 101: Course Name
Professor (or Dr.) Firstname Lastname
Date
Information: Describing Data and Statistics
Information is the first word that comes to mind when I think about data and statistics. For many people, data and statistics are just boring figures and numbers that make no sense or hold no meaning. Data and statistics do not make sense to critical stakeholders, even in established organizations, unless they are converted into a language, patterns, or trends that can be understood. Information is what results once data and statistics have been processed and analyzed. In other words, the end goal of collecting, processing, analyzing, and presenting data or statistics is to provide practical and digestible information that shapes or informs critical decisions.
A good example is the rise of Big Data in the modern era. According to Faveretto et al. (2020), Big Data refers to extensive data sets analyzed computationally to reveal trends, patterns, relationships, and associations among or between variables concerning human behavior or interactions. Since this data is in extreme proportions and various types, they are almost useless in their raw form. However, they provide ample information that shapes key decisions within business organizations and government agencies once processed and analyzed. When a business invests in Big Data analytics, it invests in information.
Data and statistics are, therefore, the raw materials that can be transformed into information. Computers and software processing and analyzing data are like machines that convert raw material into information.