Many people hear the words “data” and “information”, and think the terms can be used interchangeably. In fact, data and information aren’t the same at all, there is a distinct difference between the two words.
In order to correctly recognize and use either one, it’s important to know the difference between data and information.
Data vs Information
Data is a collection of figures and facts, and is raw, unprocessed, and unorganized. The Latin root of the word “data” means “something given”, which is a good way to look at it. Individuals and organizations can’t do much with unprocessed data because it’s so random. Once data is given structure, organized in a cohesive way, and is able to be interpreted or communicated, it becomes information.
Example of Data
J,Smith,123 King St, London, UK, 0202656788
Information isn’t just data that’s been neatly filed away, it has to be ordered in a way that gives meaning and context. This is what allows people to use data for reasoning, calculations, and other processes. With that said, data’s importance lies in the fact that it’s a building block. Without it, information can’t be created.
Example of Information
123 King Street
London, United Kingdom
To simplify this concept think of it like this:
Data has no meaning until it’s turned into information. In order for people to interpret data or make any use of it, it must be understood. For instance, a company’s sales figure for one month is a piece of data that’s meaningless because it has no context. It tells nothing, and there’s little that anyone can do with it as is. However, if you take a business’s sales figures from three months and average that number, we’d be able to derive many bits of information from that data. When one has incomplete data, it’s highly likely that it will be misinterpreted and lead to the development of misinformation. For example, suppose someone saw that his business’s sales were up by 4%, and he drew the conclusion that his current marketing campaign was working well. However, if he found out that a competitor who sold the same products had a sales increase of 16% during the same time period, he’d start to question just how well his campaign really performed and would want to gather more facts (data) to analyze the situation again.
Data quality refers to whether data is useful to make decisions, calculations, or plans. Basically, good quality data is reliable, accurate, relevant, consistent, and appropriate for a given context. Using a good data quality software tool such as WinPure Clean & Match are designed to ensure that business data is as reliable as possible so that it can provide a solid basis for effective decision-making.