Data Analytics

Data analytics can also help organizations identify opportunities to streamline operations, reduce costs, or maximize profits. Companies can use insights from data analytics to quickly determine which operations lead to the best results—and which areas are underperforming. This allows decision-makers to adjust their strategies accordingly and proactively anticipate problems, manage risks, and make improvements. A company can also use data analytics to make better business decisions and help analyze customer trends and satisfaction, which can lead to new—and better—products and services. 

The process involved in data analysis involves several different steps:

1.     The first step is to determine the data requirements or how the data is grouped. Data may be separated by age, demographic, income, or gender. Data values may be numerical or be divided by category.

2.    The second step in data analytics is the process of collecting it. This can be done through a variety of sources such as computers, online sources, cameras, environmental sources, or through personnel.

3.    Once the data is collected, it must be organized so it can be analyzed. This may take place on a spreadsheet or other form of software that can take statistical data.

4.     The data is then cleaned up before analysis. This means it is scrubbed and checked to ensure there is no duplication or error, and that it is not incomplete. This step helps correct any errors before it goes on to a data analyst to be analyzed.