Data analytics helps many businesses and institutions to simplify their work, predict trends and make successful decisions. However, it is very important to choose the right type of data analysis for different situations to ensure that the results are appropriate. The kinds of insights you get from your data depend on the type of analysis you perform. There are four types of data analysis: descriptive, diagnostic, predictive, and prescriptive. In this post, we will discuss each of these approaches.
Descriptive data analysis is the simplest and most common use of data in business today. This method is designed to analyse what has happened in the past. It will not give you an idea of exactly why something happened, but it will give you a good idea of the sequence of events. For example, with this type of analysis, you can find out how many people visited your website at a certain time or how many people opened your mailings. You can also find out what age or gender people are who have purchased your products. So, this method allows you to see a clear and understandable picture of everything that has happened up to this point in time from large amounts of data.
After asking the question of “what happened”, the next step is to ask why did it happen? The main purpose of this type of data analytics is to find and identify the causes of various discrepancies or problems. For example, if your sales dropped dramatically last month, this method will help you to find the cause. By analysing the data in this way, it is possible to detect where customers stopped when they were interested in your page. Perhaps something just wasn’t clicking for them? This method can also be used to understand the positives. In other words, if sales are up, understanding what caused it will allow you to use a similar strategy more often.
Predictive analysis attempts to answer the question “what is likely to happen in the future.”Predictive analysis identifies trends that can be used to forecast what might happen in the future. For example, if your sales normally fall in the summer, you might want to run more promotions at this time. Machine learning also relies on this type of analysis, as artificial intelligence also correlates with certain recurring patterns. So, while this method cannot guarantee that things will be this way or that way, it is quite accurate in identifying trends and makes it easier to plan your future actions based on these trends.
Prescriptive Analysis allows you to find out what happened, why it happened, and what might happen. In other words, it allows you to plan your actions to avoid mistakes and build on positive experiences. This approach is the most complex, as it uses both algorithms, machine learning, and statistics. For example, this approach is often used to develop navigation applications that not only show the nearest and fastest route but also help to avoid various obstacles. Similarly, this method helps to “navigate” a company’s operations to keep things running smoothly and avoid disruptions.
By choosing the correct type of data analysis method for a given situation, each company can take action based on the results obtained, which will make it easier to solve problems, generate good ideas and lead the company to success. In other words, having a good knowledge of data analytics or having a good data analyst makes your company much more viable.
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