About the course
Data analysis is defined as the process of acquiring data from various sources and unearthing valuable insights or patterns from the data. It has been recognized as an assistive tool for businesses. Businesses use data analysis to make strategic decisions, some of which include:
- Consumer behavioral insight – understanding consumer patterns, needs and preferences
- Identifying ways to increase ROI – measuring data related to operations and sales in order to understand how to improve efficiency, cut costs and increase profit.
- Identify new business opportunities – determine patterns of behaviour to find gaps or opportunities in the market.
These are but a few examples of how data analysis can benefit a company. This programme aims to highlight data analysis as a growing discipline and is demonstrating a larger impact on businesses. It is also becoming more affordable and less daunting for businesses to adopt.
By completing this course, you will develop a broad understanding of the following content matter and should be able to:
- Define high level concepts of data analysis.
- Describe the benefit data analysis contributes to businesses.
- Illustrate the difference between qualitative and quantitative data.
- Discuss when it is appropriate to consider quantitative and qualitative data analysis.
- Translate the importance of data visualization and tools typically used to represent data.
- Recognize that ML techniques can discover valuable insights when processing data.
- Define what Big data processing and data cleaning is and why it is needed.
- Recognize core business intelligence concepts.
- Identify various contributions data analysts could provide to businesses.
This course is made up of three modules.
Is a general introduction to data analysis. This module provides a definition of data analysis and its inception in the modern world. Qualitative and quantitative data is introduced in this section while their uses and contributions to business are mentioned.
Further examines quantitative and qualitative technical processes. Tools and instruments needed for data processing are described here. Popular elements of recent data analysis are briefly presented, these include data cleaning, data visualization, big data processing and machine learning.
Focuses on the application of data analysis in the framework of BI (business insights) and explores potential occupations in the field of data analytics.
Read more about Business Analytics
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.