The 5 Key Steps in Data Analytics: From Question to Insights

Data analytics is a term that refers to the science of managing and analyzing data for the purpose of understanding trends, drawing insights, deriving conclusions and ultimately making decisions based on science rather than intuition. The data analytics approach allows you to review and interpret the existing patterns and recent developments, see the common trends, and assess the outliers. But it doesn’t just stop there—it is also a very powerful tool that enables you to tap into future tendencies and forecast upcoming shifts. Nowadays, data is gathered, analyzed and put to good use in every industry and every aspect of our daily lives—from our shopping habits to financial market trends, from dating preferences to election outcomes. We rely on data, we trust data and we want data to back us up in our personal lives and in business. But how does the data analytics process work, exactly? Let’s take a closer look. We will start by sorting through the types of data analytics available.

There are four types of data analytics:

Descriptive analytics 

Descriptive analytics focuses on identifying and presenting common patterns in your past or present performance. It describes what is happening with your key measures right now or what has been happening to them over a period of time in the past. It will provide you with an image of your past and current performance: it will group, summarize, and show the numbers to you, presenting basic facts. What were the sales peaks? How many clicks occurred in the past 2 months? What flavor of ice-cream is the most popular in town? These are the types of  questions that descriptive analytics will help you answer.

Diagnostic analytics 

Diagnostic analytics will look into the data from your past performance and will focus on answering the question “why” by analyzing patterns and identifying the potential reasons behind the data facts. It will examine the events leading up to the existing patterns, evaluate the outliers and interpret their causes, and provide possible explanations for your findings. Using diagnostic analytics will allow you to isolate what led to a spike in sales or a significant decrease in clicks.

Predictive analytics 

Predictive analytics will go one step further and actually look at what is likely to happen in the future. It will review past data, analyze the causes of current trends, and predict the likelihood of the same or similar events occurring based on previous performance. Predictive analytics will give you answers about your future projections and whether or not your sales numbers or website visitors will grow or decline, depending on what actions you take now.

Prescriptive analytics 

Prescriptive analytics focuses on recommending the right course of action that has the highest chance of bringing you the desired result. Prescriptive analysis will not only look at the previous trends and identify possible causes, but it will also advise you on the winning strategies, best approaches, and successful plans enabling you to make well-calculated decisions and proceed with confidence. 

5 Key Steps in Data Analytics Process

Step One: Define Your Question

It all comes down to asking the right question. You are using data analytics to find insights into the right course of action and to base your decisions on science, so your question should stem from your objectives, the business problem you are trying to solve, and the hypothesis you want to test regarding this problem. Framing the right question is crucial to the outcome of your analysis, as it will determine what data needs to be collected, what tools to use, and what forecasts to expect. 

Step Two: Collect Your Data

Your data sources and the amount of data you need, have been determined by your question. Whether it’s the entries from your own customer relationship management (CRM) tool, consumer survey data from an external source, your company’s financial records, or online dating behaviour patterns—you now know what data you need and where to find it.

Step Three: Prepare Your Data

Once you collect the data, it needs to be cleaned and prepared for further analysis. This step ensures that your data is smooth and consistent, no entry points are missing, and all values are in a readable format. Unclean data may dramatically skew your analysis, provide faulty outcomes, or misleading insights, ultimately leading to fatal mistakes in your business.

Step Four: Analyze Your Data 

This is where the real science of data analytics comes in, and the type of actual analysis you will carry out very much depends on the question you pose, the tools you choose, and the data you have gathered. Whether it is a regression analysis, a time series analysis, a Monte Carlo simulation, or another approach, the essence is in establishing relationships between the variables, creating a mathematical model that predicts the behaviour of these variables, and calculating the statistical probability of the likelihood of an outcome. 

Step Five: Gain Your Insights

Finally, the last step in the data analytics process involves reviewing and interpreting your results and presenting them to your stakeholders so they can be turned into actionable insights. A key part at this stage is visualization, which makes it easier for decision-makers to review and understand the results. Dashboards, real-time reports, and other visualization tools make a big difference in how your data analysis is perceived. This stage is the turning point for your business—the conclusions based on the data analysis will become the foundation for the ultimate decisions moving forward.

Summary

Data analytics is an ongoing process—while we gather and analyze one set of data, a fresh one is accumulated and ready to be reviewed. That’s why it is now often referred to as the data analytics cycle. In this blog post, we have covered the basic steps in the process, what they involve, and how they are carried out. Learning more about data analysis will help you understand the power contained in your data and, hopefully, give you insights into what it can do for your business by shaping your decision-making process. Data analytics will hardly give you all the answers in life, but at least the ones it does give you are backed up by data and have a solid foundation of scientific approach to back it up.ack it up.