One example is the science and philosophy of plato. Procedural information – this is a type of information that describes how to make something or how to do something. An example is how to drive a car. Empirical information – this type of information comes from observations and experiments. An example is newton’s theory of gravity. Stimulation information – this is a type of information that comes from reactions. Examples such as information when looking at someone’s gesture and expression. Directive information – this information aims to direct someone to do something. Examples include manuals and sop ( standard operating procedure ). How to process data into information? Illustration of the importance of processing data and information basically, how to process data is quite simple. Starting from collecting data, processing data, retrieving information to storing data. Let’s discuss the stages one by one! 1. Collect data first of all, of course you have to collect data first.

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The data taken can be in the form of qualitative data or quantitative data. You can get the data from two sources: internal and external . Internal data comes from your own business, while external data comes from other sources. Examples include research results or competitor analysis. There are many ways you can collect data. Starting from distributing questionnaires to making observations. Also read: what is data mining? The following is the definition and examples of practice! 2. Preparing data in this process, you need to sort data and delete irrelevant data from other data. This is important, because Lithuania B2B List during the data collection process, sometimes “foreign” data enters the database. Well, data like this can interfere with the process of extracting information in the future. 3. Data input after all the data is well organized, you can enter the data into the data analysis tool .

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 Identify Business Needs

Examples include word processor applications and spreadsheet applications . Later, data processing will be carried out in the data analysis tool. Whatever tool you use, make sure you learn how to use it first. 4. Processing data after entering the data, now all you need to do is process the data . Well, how to do it? It depends, because each data processing tool has a different usage method. For example, if you process data in google sheets, you can process the data using various available Mobile Lead formulas. 5. Retrieving information after the data is processed, you will find an insight or pattern from the data set . For example, suppose you process sales data for quarter x. Based on the results of data processing, it is known that product a is the best-selling product, while product z is the product whose sales volume is unsatisfactory. Now, after you get the information you want, you can present it in the form of graphs, tables or diagrams.


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