WHAT IS DATA ANALYSIS?

There have been different definitions of what data analysis means. Although these definitions are interrelated, I believe this is a much simpler definition for everyone.

Data analysis can be defined as the process of gathering data, studying, cleaning, transforming, and presenting your findings so one can draw insight from them. You can also describe it as the process that raw data goes through before one can extract relevant information or make a conclusion from it.

The outcome of these processes that data goes through can be represented in charts, graphs, and tables.

Why is Data Analysis important?

There are different reasons why data analysis is important in the business world.

A few of these reasons are:

Informed Decision making: Data analysis helps organizations or businesses make decisions regarding their products or services. These decisions are based on visible data or facts and not on assumptions. These decisions can be as fundamental as deciding when to invest money, how to invest, what proportion of revenue and profit is anticipated, or how to address a pressing issue.

Reduced costs:With the aid of tools, analysis assists organizations in identifying where profit or loss originates; these techniques also enable the identification of unsuccessful ventures.

Target customer better: with the help of these analytical tools used in data analysis, an organization can better understand their target customers using information like their communication channels, demographics, and many more., Additionally, by doing this they avoid wasting resources on the wrong consumers.

WHAT IS THE DATA ANALYSIS PROCESS?

The steps in data analysis, or the data analysis process, are as follows:

Identify: This highlights the intention of getting data.

Collect: This is the process of collecting the needed data. At this stage, the type and source of data come in. Data can come from surveys, questionnaires, interviews, and others.

Clean: Cleaning can be in the form of disposing of poorly formatted data, removing duplicate records, and formatting errors.

Analyze: There are so many techniques that help in analyzing data, such as neural networks, regressions, and statistical analysis. These procedures involve the analysis and modification of data to draw out the necessary information.

Interpret: This is the process where the results are interpreted. This step gives the researcher insight into making decisions.

Key takeaway,

Applying data analysis to a business helps it become more innovative, profitable, and capable of making better business decisions.