BTEC Level 3 Extended Diploma in Information TechnologyUnit 42 - Spreadsheet Design

Task 14; D1: Discuss how organisations can use interpretation methods to analyse data

Organisations will need to constantly use data analysis in order to keep track of their finances and other important statistics that help keep the business running. There are many different methods that an organisation can use for data interpretation. Microsoft’s Excel is an excellent analysis tool that can be used to take advantage of the procedures to obtain clearer management information. Given the importance in financial analysis, the use of Excel should be a core skill for employees to enable them to produce clear and maintainable applications and be proficient in spreadsheet design. I will explain some of the different techniques that can be used in spreadsheets to help present data in a professional and easily legible format.

The need for data analysis is very important in organisations as it will offer a variety of beneficial outcomes, such as structuring the findings from survey research or other means of data collection; acquire meaningful insights from the dataset; basing critical decisions from the findings; offer clear communication amongst employees through the illustrative charts, tables and summaries. Because of these reasons, it is considered imperative for businesses to understand the full functionalities of the different techniques that are used to analyse and present data. This can be done through a variety of specific data analysis methods. The specific techniques that I had used for my own spreadsheet include:

- Trend Analysis- Sorting- Conditional Formatting

I will now explain each of these different techniques in detail and why they are particularly advantageous in analysing and presenting data.

Kieran Emery 1 May 2014

Methods of interpreting data

Trend Analysis

What is Trend Analysis?Trend analysis is a method of time series data analysis that involves comparison of the same item over a set given time to find the general trend for results across the studies. Trend analysis is commonly used in organisations in order to track historical performance and extrapolates the data to make an estimate of future capabilities. One of the most common methods for implementing trend analysis is through the use of charts/graphs.

Charts are graphical illustrations that are used to represent statistical information in an easy-to-read format. There are a vast variety of different charts and graphs that allow the user to present their data in different ways.

Here are some examples of the most popular types of some of the most popular types of charts and graphs:

Bar Cylinder Cone Pyramid

Horizontal Bar Line Curve Step

Area Pie Scatter

Kieran Emery 2 May 2014

How can Charts be used to analyse data?Each chart/graph has their own unique way of analysing data. Most of which will incorporate colours into their design to show clear and illustrative figures for data analysis.

Pie Charts

The Pie Chart image on the left shows proportional data by splitting up the different statistics into various segments of a pie. The whole circle represents 100% and the segments split accordingly to the size of the statistics.

Column Charts

The image on the left shows a Column Chart. Column charts display information as a series of vertical rectangular columns to show the comparisons between items of data. The bars are lined against each other on a marginal scale so that the reader can quickly interpret the value of each figure based on its length.

Line Charts

A Line Chart displays quantitative information in a series of data points called ‘markers’ that are connected by straight line segments. They are also lined up on a marginal scale and typically used to track the trend of something over a period of time.

This could be useful in an organisation to easily check up on the changes in revenue over a set period of time.

Kieran Emery 3 May 2014

How Charts were used in my SpreadsheetI made sure to input as many charts into my spreadsheet as necessary. These charts are useful as they provide a further analysis for the statistics of the members in my spreadsheet.

For example, the column chart on the right was used to show the total income statistics per each membership. Presenting this information in a bar chart allow me to clearly comprehend the marginal differences between each membership group.

I also used another column chart in order to present the data regarding the average of members per each group. This is interesting information as my membership groups are focused entirely upon what the age of the membership recipients are. Presenting the information this way clearly demonstrates the average ages of each membership group. This statistic will be important to consider in my business model as it is important to track the

ages in case the groups need to be altered dependent on how people are subdivided into them, as for example, if the graph shows that the marginal height of one of the groups is too high that they are almost reaching their maximum age requirement of that group then it implies the model needs altering as the members are getting too old for the group they are currently acquainted for.

Finally, the pie chart below was used to clearly illustrate the different numbers of people per membership by presenting itself in a suitable yet different format. Within these scales I can clearly see the difference in the statistical data and present it in a colourful and aesthetically engaging arrangement.

Kieran Emery 4 May 2014

Sorting

What is Sorting?Sorting is a feature that allows the user the user to render the data based on the sorting type of their preference. You can sort data in many different ways, such as normal and reversed alphabetical sort, as well as descending numerical ordering.

How can Sorting be used to analyse data?Sorting is a particularly useful technique in given situations where the user wants to analyse the data in a given order. For example, if a teacher wanted to assess the students’ grades in a simple format that is easy to read, they may sort the tables to show the names of the students in a sequential order (i.e. in an ascending or descending order). This would make the data more legible for the teacher as they can assess it in a particular order of their choice.

For example, in the below scenario I have listed a table featuring a list of student names and their score in a particular test. I will no show the different types of sorting techniques that are available to make this information more comprehensible for the reader;

Raw unordered data:

This is the table before it has been sorted. It displays a list of names and their scores in a randomised order.

Sorting: Alphabetical order (Ascending):

This shows the process of sorting the information of the names in an ascending alphabetical order (a, b, c…) starting at the top down to the bottom. This makes the information much easier to read; a technique that is commonly used for registers of names.

Kieran Emery 5 May 2014

Sorting: Alphabetical order (Descending):

This method involves the same process but instead reverses the alphabetical order so that it is displayed in a descending manner.

Sorting: Numerical ordering (Ascending):

This technique also works for numerical values. In this scenario, it would allow the teacher to sort the test scores in an order from lowest-to-highest. This would be a useful technique in quickly finding out who got the lowest/highest in

the test.

Sorting: Numerical ordering (Descending):

This is the same technique as above but in reverse (displaying the highest-to-

Kieran Emery 6 May 2014

lowest test scores from the top). This could simply be a preferable method for analysing the data.

Kieran Emery 7 May 2014

How Sorting was used in my SpreadsheetSorting was later incorporated into my spreadsheet for convenience purposes so that the user can easily sort the data based on all the different members that are grouped into the different membership assemblies that were available.

This was created in a different worksheet entitled Sorted Spreadsheet View that allows the user to easily inspect all of the members in the different groups in a sorted and structured view. The data was also colour coordinated (only in this viewing) to allow easier identification of who is in attendance of which group.

Nevertheless, after putting the data into a table format, this has given the user the capability to automatically sort the data themselves (as shown in the screenshot on the right). Selecting on one of these options will then categorise the data to only show that specific membership group. The exemplar screenshot below shows what happens when the user selects on the Red membership sort filtering.

As you can see, only the red membership data is evident in the table. Therefore the sorting filter has proven itself as particularly useful within my spreadsheet if the user wants to inspect only the members of a specific group.

Kieran Emery 8 May 2014

What is Conditional Formatting?Conditional Formatting refers to the formatting of data cells that changes based upon its specific condition. This technique allows the user to alter the appearances of the cells, i.e. changing the colour and font, in order to highlight cumbersome data when it meets a specific criterion.

How can Conditional Formatting be used to analyse data?Conditional Formatting could be a useful technique for analysing data as it can change the values in cells so that the user can quickly identify between distinct values. For example, the user could use a colour scale to differentiate between high, medium, and low temperature values (i.e. the hotter the temperature the more red the cell colour will be, whilst the colder the temperature the more blue the cell colour will be).

In this scenario I have created a simple table that displays people’s names and either the answer “Yes” or “No” to a survey question.

This is the current table format before any conditional formatting rules.

Now I will open up the Conditional Formatting Rules Manager and set rules that inform the spreadsheet that the B column will change the colour of the cells dependent on its text based values. The values are either “Yes” or “No”. If a cell in this column says “Yes” then it will automatically be formatting to a green background. Whilst if a cell in this column says “No” then it will display a orange background.

Kieran Emery 9 May 2014

This technique allows the user to quickly differentiate between the different values based on their correspondent colours.

How Conditional Formatting was used in my SpreadsheetConditional Formatting played a vital role in the structuring of my spreadsheet. As you can see in the exemplar screenshot on the right, conditional formatting was used to format the background colouring of certain cells. I implemented this feature because my business model revolved around different coloured membership groups (blue, red, and green) so I wanted to clearly illustrate these memberships by the identification of colour. To do this, I had to use the Conditional Formatting Rules Manager (as shown below):

I made rules to identify when a cell in a specific column contains the text for one of the membership groups and to then automatically fill in this cell with that correlating colour scheme. For example, if the cell contained the word ‘Green’ then it would automatically filter to a green background. This use of conditional formatting proved itself useful in my design as it meant the user could clearly see who belonged to which membership group.

Kieran Emery 10 May 2014