Four magic data analytics questions to make your life easier

‘Data is the new oil’ This sentence describes the importance of data in the 21st century. If oil prices affect every business sector, then data does the same thing. Thus, you do not have to be a data engineer or data scientist

to deal with data. You can be a business strategist, a teacher, or even a high school student. Everyone can benefit from data analysis skills.

So, what is data analytics? It is the science of analyzing raw data to answer questions. Before we talk about SQL or Python, the most crucial point is how to ask the right questions. These four magic questions can help you understand and handle problems in your career.

What happened? (Descriptive analytics)

Understanding the problem is the first step toward every solution. The concept of this question is to identify the trends and relationships of your data. You might already be familiar with this process when using a program like Microsoft Excel. This program does not help you solve problems but facilitates your investigation into it.

In real-life practice, some retail businesses offer free membership to every customer. Customers will get a special promotion if they present their membership card or number with every purchase. With this method, the store will obtain customer information such as age, residence, education, purchase amount, items purchased, etc. Businesses can then use this data to identify trends. For example, certain age groups may be more likely to purchase particular products. We can use newly discovered information for further analysis.

Why did this happen? (Diagnostic analytics)

After identifying a trend, you should investigate its cause to find a solution. Customers in the subscription model industry might complete a survey describing their decision to terminate their membership. They may be dissatisfied with the service or they may have found a similar service at a more affordable price. This data will tell us why the trend (service cancellation) happens.

What might happen in the future? (Predictive analytics)

If you can identify a current trend, you should also be able to predict the future trend. Prediction is crucial to preventing a problem or finding a solution when the same problem occurs again. In weather forecasting, the meteorological department records information about past floods, such as humidity or rainfall amount. If those conditions match, the trend (flooding) will probably occur again in the future.

What should we do next? (Prescriptive analytics)

You may have several ways to deal with one problem. You can decide which choice is the best. In marketing, lead scoring is used to determine who might become a future customer based on their engagement. For example, you have a limited budget to broadcast your advertisement. Instead of wasting time and money sending mail to everyone, you can focus only on those who clicked a link in the latest e-mail and visited the product’s page.

When you begin with the right questions, it can make it easier find the right answers. Although, the process of finding problems and solutions is crucial, don't forget to put your findings into practice!