Data is factual information used as a basis for reasoning, discussion, or calculation. In the modern age, the aim is to have almost everything connected, and data previously produced on paper is now available online. This is attributed to the recent advances in technology, such as data processing, transmission, and storage associated with improved computer software which reduce costs and increase data capacity. Are you in need of data analysis services?  Well, then look no further because our company is well known for offering accurate data analysis services to gain meaningful insights that help in decision-making.

Get the most out of your business data by hiring our expert data scientists for data analysis services and data analytics services. Every day, a larger quantity of data is generated and consumed. This data provides a rich source of information that can be transformed into useful and understandable knowledge utilized for decision-making.

Two words often used interchangeably but have a significant difference are data analytics and data analysis. Even though both are used to gain an understanding of raw data, their scope, techniques, and aims are different. This post gives a comprehensive overview of the similarities, differences, and examples of an application of both processes.

What is data analytics?

Data analytics is the science that analyzes raw data to gain useful knowledge used for decision-making. It involves data collection, organization, preprocessing, transformation, modeling, and interpretation. This data can be structured, unstructured, semi-structured, or big data depending on the structure.

Multiple companies globally are realizing the potential of using data analytics to their advantage to increase the value of their products and profits. According to Statista, the number of organizations using big data analytics in market research steadily increased between the years 2014-2021 by 46%.

What is data analysis?

Data analysis, on the contrary, is a sub-division of data analytics that involves the transformation of data into useful facts that can be used either qualitatively or quantitatively. It involves simplifying complex factors into simpler parts for the preparation of interpretation. Data can either be qualitative or quantitative.

The aim of data analysis is to summarize and explain data, find the relationship between two or more variables, find the differences between variables, or predict outcomes.