How to Simplify Your Data Analysis Process – 2024 Guide

In order to operate in today’s market and still be competitive companies collect a large amount of data in a variety of places (both online, but also in the real world). In other words, market research has to be done continuously. All of this is performed in order to adjust the work methods, and increase customer experiences, and employee experiences for the better. The data collected can significantly add value if it is systematically analyzed to gain insight into how you can improve your products and services.

But the fact that it has to be collected in so many places also means the process of analyzing can be a bit daunting and complicated. If we were writing about this a decade ago, this might be true, but there is a solution today which can contribute to the simplification of the whole process. But first, let’s simplify everything by explaining the term a bit more in detail.

Data analysis: definition of terms


Data analysis is the science of examining a set of data, for example, to draw conclusions from information, to make important business decisions, or simply to expand knowledge in different areas. Daniel Burrus, a business consultant and spokesperson for business and innovation, says of data analytics: “A lot will help people work smarter and faster because we have data for everything that happens.”

In order for the process not to be as daunting as we mentioned, we are giving you a guide on how to simplify a data analysis process.

Invest in a good software

There is no quality data analysis without a good software solution, and if the aim is to simplify the whole process, the first thing you need to do is invest in one. As a result, you’ll get your data analyzed at the highest level possible, rest assured everything is done how it’s supposed to be. With these solutions, you’ll be automating so many processes inside the company that the risk of a human mistake being made will be minimized. Hence, reporting will be conducted a lot easier. However, with so many solutions being offered today, one can easily get confused about which one to buy. Consult the list of the highest-rated software solutions here

Why are these software solutions important?


Over the past few decades, the development of information systems in larger enterprises has been accompanied by the development of management technology in data storage. Initially, the information systems of individual departments were developed independently of each other, so that, for example, the finance department had a separate information system from the human resources department. The so-called “information islands” were created, between which the flow of information was not established.

If a company has offices in multiple states until recently it was the practice for each state to have a separate information system, which was necessary due to differences in legislation, local customs, and the problem of remote customer support. Such systems most often had different data structures. The problem arose with reporting, as there was no easy way to aggregate data from diverse information systems, to get a picture of the state of the entire enterprise. One of the tasks of information engineering is to merge separate information systems into one logical unit, from which unified data can be obtained.

Apply the process in the context of your own business

Such analysis is used in many business areas. It provides those responsible with an important basis for making decisions, for example when a product should be placed on the market or how high the price of a product should be. Below are examples of areas where companies are increasingly using data analytics.

In the field of marketing


In marketing, researchers conduct data analysis to predict consumer behavior and place products and services on the market accordingly. For example, analyzing sales data can help you identify a portfolio of products or services that is less popular or particularly well-accepted in a particular demographic group. Data analysis can also give you a deep insight into the optimization of marketing campaigns to better connect with the target group and respond more precisely to its needs.

In the field of human resources

Companies use data analysis in the field of human resources in order to be able to offer their employees a good working environment and the best working conditions and to ensure a high level of employee satisfaction. Employee surveys or pulse surveys are usually conducted for this purpose.

In the field of user experience management

Data analysis in the field of customer experience management aims primarily to make customer experiences on the customer path positive. Data is usually collected through the analysis of points of contact, i.e. surveys at the interface between customers and companies.

Why is information so important?

The problem of not having the right information in practice is greater than it may seem. Certain types of businesses, especially those that are not profit-oriented, can operate in this way. However, a large company, which sells its main product on the market for a month at the wrong price, due to inaccurate information obtained by the management from a bad information system, will surely find itself in big trouble. The organization’s dependence on quality information from the business system grows with its size and the geographical dislocation of its offices.

In smaller organizations, it is common for “everyone to know everyone” and “everyone to know everything”, so the informal flow of information within the company is also quite effective. In a company like this, it will be difficult for some significant wrong decisions to be made due to wrong data in the software. The larger the organization, and the larger the geographical area, the less or no personal contact among its employees, and important decisions at the top of the hierarchy are largely made based on reports from the information system. The importance of having accurate business information for such companies is a matter of market survival.

About Nina Smith