3.4 - Stages of Data Analysis
2016 - Unit 2
Data analysis is the process of identifying and collecting data to be viewed and modelled, in the aim of discovering patterns or trends that can be used for conclusions and decision-making.
1. Identify the need
Before anything else can take place, objectives are set for what the data analysis will hope to achieve. Aims must be clear and well defined. For example, an organisation should define what information will be needed and what exactly they want to find out by the end of the process (the purpose of the data analysis).
Not clearly defining the required information or purpose could lead to worthless results and a waste of the entire data analysis process.
2. Define the scope
In this stage the restrictions of the project are defined. Scope includes factors such as budget, content, detail, timescales (deadlines) and any further constraints.
3. Identify potential sources
Project planners must identify a wide range of sources for the potential information, ensuring that it is unbiased and covers the objectives. The specific data will depend on the project but it could include sales figures or customer surveys for example.
4. Source and select information
Information is gathered from the identified sources in stage three. Any unsuitable data is excluded so that results are not unreliable as poor quality information can lead to numerous negative consequences. Planners will have to determine the accuracy and reliability of any identified sources and select the best.
5. Select the most appropriate tools
There are many different data analysis tools that can be used as part of this sequence; in this stage the most appropriate tool for the project is selected.
Examples include methods of presentation such as charts and graphs for a visual representation of data.
Regression analysis can also be used - regression is the determining of relationships e.g. if the amount spent on advertising bottled water increases, will consumption increase too or are other factors involved? If there is a link, a business can continue to spend more on advertising if consumption and profit also rises.
Trend analysis is another option - this shows patterns over time, for example, bottled water consumption each year over the past decade.
6. Process and analyse data
Data has now been collected and can be inputted into software such as spreadsheets or databases to further analyse. Putting collected data into a spreadsheet for example allows for analysis to begin as graphs can be created from the data and any patterns or trends discovered.
7. Record and store information
The data has been collected and analysed and now any findings are written into a report. Any patterns, trends or findings can be described with statistical evidence generated from the analysis.
8. Share results
A report is worthless if not shared with the stakeholders. Sharing can take different forms such as a typed document posted out to stakeholders, an email with major findings summarised or as a post on a website.
3.4 - Stages of Data Analysis:
1. List the 8 stages of data analysis in order. 
2. A supermarket chain called 'Fresh Food UK' wants to complete data analysis to see which stores across the country have been most profitable in the last year. Explain how Fresh Food UK would use each of the 8 stages of data analysis.