How Is Data Analytics Different From Statistics? Essay Sample

Published: 2023-10-09
How Is Data Analytics Different From Statistics? Essay Sample
Type of paper:  Essay
Categories:  Data analysis Statistics
Pages: 2
Wordcount: 513 words
5 min read

While data analytics and statistics are used simultaneously in solving business problems, the two terms differ. Data analytics is different from statistics in that it involves inspection, presentation, and reporting of data in a useful way to non-technical people. Analytics involves translating numbers or figures to people who want to know about them, such as business decision-makers (Udegbe et al., 2019). On the other hand, statistics involve collecting, analyzing, interpreting, presenting, and organizing data. Data analytics is different from statistics in that it involves exploring what is presented in data, while statistics focuses on inferring what is beyond the data.

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Analytics tools fall into three categories: descriptive, predictive, and prescriptive. What are the main differences between these categories?

Descriptive analytics involves describing existing data by use of business intelligence tools that already exist to get a better understanding of what is happening (Bumblauskas et al., 2017). Predictive analytics emphasize on the prediction of possible outcomes by use of machine learning techniques or statistical models (Grover & Kar, 2017). Prescriptive analytics focus on recommending the course of action after data analysis.

Explain how businesses use analytics to convert raw operational data into actionable information. Provide at least 1 example.

Business clearly defines their corporate goals which help analysts in focusing on the data to mine or eliminate. To convert raw data into actionable information through analytics, the business has to make decisions with clean data, considering the scope of work, automating data analysis and visualizing data to reduce complexities (Ghasemaghaei, et al., 2018). For instance, retailers understand the demographics of their customers by using artificial intelligence and machine learning tools to capture data rapidly, filter it and analyze it to get the most useful information.

Consider the organization you work for (or another organization you’re familiar with). Does this organization use data analytics? If so, how is it used? If not, how could the organization use data analytics to improve its performance?

Amazon uses data analytics to analyze data about its customers to predict what they might want to purchase. The company uses data analytics by gathering data about customers who visit their site, monitoring what they view, their shipping address, and whether they leave any reviews.


Bumblauskas, D., Nold, H., Bumblauskas, P., & Igou, A. (2017). Big data analytics: transforming data to action. Business Process Management Journal.

Ghasemaghaei, M., Ebrahimi, S., & Hassanein, K. (2018). Data analytics competency for improving firm decision making performance. The Journal of Strategic Information Systems, 27(1), 101-113.

Grover, P., & Kar, A. K. (2017). Big data analytics: A review on theoretical contributions and tools used in literature. Global Journal of Flexible Systems Management, 18(3), 203-229.

Udegbe, E., Morgan, E., & Srinivasan, S. (2019). Big data analytics for seismic fracture identification using amplitude-based statistics. Computational Geosciences, 23(6), 1277-1291.

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