When working with data, we often focus on where and how to find it. What we don’t think about nearly as often is what we do with it once we have it. Data analysis is a process that goes deeper than the surface of your data and involves various ways of exploring its meaning and significance. Thus, given the popularity of Microsoft Office, data analysis in Excel is a useful skill for medical writers.
If you’re an Excel user, your first thought may be: “Great! Now, I have another great opportunity to show my love for this software again.” However, you might be pleasantly surprised at how useful these tricks are, even if you use other tools more frequently. Read on to learn 7 hidden tips that will help improve your output in data analysis using Excel.
In this article – data analysis in Excel:
- Data cleaning is your friend
- Use conditional formatting to highlight important data
- Consolidate duplicate data using VLOOKUP and SMAP
- Add a timestamp using formulae
- Use IF function to show what’s most important at a glance
- Finding themes and trends
- Change the look and feel of the data
- Conclusion
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Data cleaning is your friend
Before you analyze data, you need to make sure that it is accurate and consistent. This process is called data cleaning, and it is a vital part of data analysis. Data analysis in Excel is no different from the use of other software programmes. There are many ways to clean data, but they all come down to two things: Identifying inconsistencies and removing them There are many reasons why data may be inconsistent.
For example, an employee might have incorrectly recorded their hours worked during a certain period, or an incorrectly labelled sensor might have recorded data that doesn’t make sense. Most inconsistencies are easy to spot, but some might be harder to see. However, without removing them, your analysis will be incomplete, or worse, inaccurate.
Use conditional formatting to highlight important data
Conditional formatting is a useful function in data analysis in Excel. You can use conditional formatting to highlight data that meets certain conditions. For example, you can highlight data that is greater than or less than a certain value, or that falls within a certain range. You can also highlight data that is equal to a certain value. These visual cues can help you spot important data you might otherwise miss.
You can use conditional formatting to highlight your data in many different ways. Some ways to use this include highlighting positive and negative values, highlighting outliers, and colouring data according to a certain category.
Consolidate duplicate data using VLOOKUP and SMAP
If you are analyzing data from various sources, you will likely run into duplicate data. Duplicate data might stem from a mistake that was made in data entry, or it might be the result of linking data from multiple sources. If you are analyzing data from multiple sources, you will have to deal with duplicate data.
However, you don’t have to just leave it as it is. You can use the VLOOKUP and SMAP functions to consolidate duplicate data into one cell. This will help you clean up your data and make it easier to analyze.
Add a timestamp using formulae
If you are analyzing data that covers a long period of time, it is useful to add a timestamp that indicates when the data was recorded. This is especially true if you are comparing data from different time periods. This is easy to do in Excel. Simply select a cell and type “=TODAY()” followed by “&” and the date you want to add the timestamp to.
For example, if you want to add the timestamp for July 11, 2019, you would type “=TODAY()&7/11/2019”. This will add the date and time when your data was recorded.
Use IF function to show what’s most important at a glance
This is another popular function in data analysis in Excel. If you have a lot of data, it can be challenging to find what you are looking for quickly. You might solve this problem by adding a column for filters and a column for your notes, but you can do even better. You can use the IF function to highlight the most important pieces of data at a glance. This is useful when you are looking at data over a long period of time, or when you are exploring data from many different sources.
For example, if you are analyzing data and want to know how many sales you made on a specific day, you can plot the data and use the IF function to highlight the sales data in red. This way, you can quickly identify the sales data, even if all the other data is plotted in red as well.
Finding themes and trends – data analysis in Excel
The best way to analyze data is to look for trends and themes. These will help you understand the data better, and they can even give you some ideas for what to do next. You can look for trends and themes in many different ways, including by using pivot tables, sorting your data in different ways, or using graphs. You can also use Excel’s Data Analysis tool to conduct an exploratory analysis. This will allow you to go a little deeper and identify themes and trends in your data.
Change the look and feel of the data
When we look at data, we don’t always see the same thing. Your analysis may lead to you seeing a different story than others do. You can recognize this, but others might not. In these cases, changing the look and feel of your data can be useful.
This can be as simple as changing the data’s colour or its chart type. This can be helpful if you want to compare your data with similar data.
Conclusion on data analysis in Excel
Data analysis is a crucial step in the business intelligence process. But before you can analyse data, you must get your data into shape. Cleaning up your data to remove inconsistencies and improve its quality is essential.
You can use that data to find trends and themes. You can also change the look and feel of your data to make it easier to compare it with other data. When you use these tips, you will discover that data analysis is actually quite enjoyable. Overall, data analysis in Excel is an essential skill for many medical writing tasks. Taking some time to master this craft will pay you several folds over.
