Administrative professionals are often required to possess a wide range of skills in this day and age. As such, learning new skills is always a great way to get ahead and unlock new opportunities. Data analysis is one skill that can prove hugely beneficial to many administrative professionals.
The volume of data being used in business today is much greater than ever before. In recent years, the influx of advanced technology has created new opportunities for data collection and data analysis. In addition, honing your data analysis skills is a great way to provide more value and advance your career.
Here is a quick guide to essential data analysis tools, software, and skills you can apply to your own career.
Pivot tables are one of the most useful data analysis tools, and virtually anyone can master them. They can be created relatively easily in Microsoft Excel, and are great for quick, efficient data management.
The purpose of a pivot table is to present and reorganize data so that it can be analyzed from various perspectives. Pivot tables are commonly used in business data analysis to review things like quarterly sales or productivity across departments.
Two other simple data analysis tools you can use in Excel are Flash Fill and Power Query.
Flash fill is an Excel feature that allows users to automatically fill cells when the program recognizes a pattern. This is incredibly useful if you are entering large quantities of data with a consistent variable.
Power Query is a bit more complicated, but just as helpful. This is an Excel function that enables users to import data, and then alter or transform that data for their own analytical needs.
The most well-known and widely-used data analysis software is Microsoft Excel. In fact, we’ve already mentioned it with the data analysis tools above. Excel is familiar and straightforward, with an easy-to-understand interface. It’s also highly flexible, making it an essential resource for anyone interested in data analysis.
SAS is a popular visual data analysis software that is used by many analysts. This system is reliable because it combines several important data analysis tools. Also, it’s unmatched when it comes to analyzing visual data, such as charts and graphs.
Whereas SAS is used for visual data analysis, Tableau is widely used for data visualization. Tableau is an essential data analysis software because of how easily it allows users to convert data into effective visual graphics.
Before you can analyze data, it needs to be collected, stored, and analyzed. All of this falls under the umbrella of data management. Data management is a foundational data analysis skill. You should learn data management skills alongside, or prior to, developing your data analysis skills.
Probability and statistics are two branches of math that deal with collecting, analyzing, and interpreting data. While programs like Excel can handle much of the math for you these days, it’s still important to understand key mathematical principles. Brushing up on your statistical proficiency can only help when it comes to improving your data analysis skills.
If you’re serious about data analysis, you’ll need to be familiar with at least one coding language. SQL is one of the simplest, and most frequently used, languages for data analysis.
Other statistical programming languages, like Python, are also in high demand among data analysts. Learning one of these languages may take time, but it can be a worthwhile endeavor.
Want to learn more about growing your professional skills and resources? Browse ASAP’s efficiency & skills or technology education resources for more helpful guides and seminars.