Introduction

Data analytics is the science of analysing raw data in order to draw conclusions. Many of the techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption. Data analytics techniques can reveal trends and metrics that would otherwise be lost in the mass of information. This information can then be used to optimize processes to increase the overall efficiency of a business or system.

The process involved in data analysis involves several different steps:

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

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

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

• 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 the data go to the analyst

Key Learning Points

• Data analytics is the science of analysing raw data in order to make conclusions about that information.

• The techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption.

• Data analytics helps a business to optimise its performance.

Course Contents

We cannot look at and solve all data analysis problems and cases but here is a glimpse into the areas where data analysis is being applied very successfully:

• Retail

• Health

• Sports

• Weather

• Financial modeling

• Energy

• Social Media Analysis

• Internet of Things

Throughout this course, we will be assessing examples from these areas as an aid to our greater understanding of the usefulness and application of data analysis.

Please visit https://www.ctsolutionsglobal.com/data-analytics or email enquiries@ctsolutionsglobal.com for more information