Despite the amount of data we generate every day, only 0.5% of that data is analyzed and used to discover insights and improvements. While that may not seem like a lot, considering the amount of digital information we have at our fingertips, half a percent is a lot and makes a big difference.
With so much data and so little time, knowing how to collect, curate, organize and make sense of this information that can improve your business can be a difficult task, but there are data analysis techniques to solve this problem.
To help you understand the potential of analytics, its meaning, and how you can use it to qatar number data improve your business practices, we’ve answered several questions for you. We’ll not only explore data analysis techniques and methods, but we’ll also show you various types of data analysis and how to do them in the real world with a 15-step blueprint for success.
What is Data Analysis
What is data analysis ? Data analysis is the process of collecting, modeling, and analyzing data to support decision-making. There are several techniques and methods for performing data analysis depending on the market and the purpose of the analysis.
All these data analysis methods are largely based on two main areas: Quantitative and Qualitative methods.
Read this article until the end to understand the different data analysis techniques, as well as quantitative research methods as well as qualitative insights – all of which will give your information analysis efforts a clearer and more defined direction.
Why is data analysis important?
Before we start talking about the categories of data analysis along with their methods and techniques, you first need to understand the potential that data analysis can bring to your company.
Let’s start with customers, arguably the most important element of any business. If you use data analytics to get a 360º view of every aspect of your customer, you’ll understand which channels they use to communicate with you, their demographics, interests, habits, purchasing behaviors, and more.
In the long run, it will bring success to your marketing and digital marketing strategies , will allow you to identify potential customers and will prevent you from wasting resources on the wrong audience. You can also measure your customer satisfaction by analyzing your customer reviews or the performance of your customer service department.
From a management perspective, you can also benefit from analyzing your data because it will allow you to make decisions based on data rather than just intuition. For example, you can know where to invest your capital, spot growth opportunities, predict your returns, or address unusual situations before they become problems.
7 Essential Data Analysis Methods
Before we talk about the 7 methods, it would be important to first briefly talk about the main categories of analysis. Starting from descriptive analysis to prescriptive analysis, the complexity and effort of evaluating data increases, but so does its value to the company.
a) Descriptive analysis: What happened.
Descriptive analysis is the starting point of every analytical process, and seeks to answer the question “what happened?” and does so by ordering, manipulating and interpreting data from various sources to transform it into valuable insight for your business.
Performing descriptive analysis is essential because it allows us to present our data in a meaningful way. However, it is important to make it clear that this analysis will not allow you to predict future results or answer questions about why something happened, but it will leave your data organized to conduct future analyses.
b) Exploratory analysis – How to explore the data relationship.
As the name suggests, the main goal of exploratory analysis is to explore. Before this, there is no notion of the relationship between the data and the variables. Once the data has been investigated, exploratory analysis will allow you to find connections and generate hypotheses and solutions to specific problems. A typical area where exploratory analysis is applied is in data mining.
