Improve Your Analytics By Growing Beyond Microsoft Excel
03/27/2019 by Ben Murphy Modernization - Analytics
Everybody using Microsoft Office as a primary means for data analysis needs to reconsider whether it’s truly the best option. As the amount of data that is available in every industry and every organization continues to increase, the number of people using data to help inform better decisions continues to increase as well. Unfortunately, using Microsoft Office will slow down progress and could lead to costly mistakes and rework.
The two main Microsoft Office tools that people use as a primary data analysis software are Access, a database offering, and Excel, a spreadsheet offering. People tend to gravitate to these tools because Office is so easy to setup and use in Windows. We’re going to explore alternatives that are more robust and require a little more effort to get going, but offer enough benefits to be worth it. These alternatives usually involve learning some kind of programming language and installing some kind of software so that analysis can be done using computer code.
Let’s go through my top reasons to avoid using Office as your primary data analysis tool, the most common excuses for not making the transition away from Office, and some of the great options to replace Office as your primary data analysis tool.
Here are the top reasons to stop using Microsoft Office as a primary tool for data analysis:
Automation & Efficiency
Being able to run analysis in code with the press of a button saves time, and being able to run analysis repeatedly without having to recreate everything makes it easier to setup sustainable processes that have longevity.
Accuracy & Reliability
Writing the steps for data analysis in code is less likely to have errors, and will make it easier to find any errors that do exist. Spreadsheet formulas spread across multiple steps of analysis can be difficult and time consuming to review and verify compared to code. A program verified to be correct helps to ensure accurate and reliable results, which increases trust in output and buy-in from others.
Portability & Collaboration
Code is easier to send and share in teams, especially when data can be centralized. Teams can build and share analysis without having to send all the data long with it, and can more easily recreate and repeat previous analysis using code than spreadsheets.
When presented with the advantages of using more robust tools, you may still want to use Microsoft Office tools. It’s understandable that there could be reasons that make using Office more appealing. Here are the biggest reasons and why you should reconsider:
For most people, the biggest obstacle to changing their data analysis tools to something more robust than Office is an existing comfort and familiarity with what Office does and how they use it. There’s no way that starting a new tool will feel as comfortable as using a tool that’s been part of your computing lives for years, but progress and improvement sometimes require change. Remember, some initial discomfort will dissipate as we get used to the new tools and enjoy all the benefits that the new tools can offer.
The ability to feel like one tool can do everything you need is tough to beat; for example, we tend to feel like Excel is a one-stop shop for data cleansing, data analysis, and reporting. However, many tools offer almost all the same functionality available in Excel with the added benefits of many more options for methods and techniques for finding patterns and gleaning information from reams of data. Additionally, combining tools that are excellent in some of these steps can result in improved output.
Since Office is already installed and ubiquitously approved by IT departments everywhere, it’s easy to get into Office any time you want it. Years ago, it was much tougher to get open source alternatives approved and setup for people to use, especially in large organizations, and commercial software can be a tough sell if it isn’t already on the approved software list for your organization. Now open source options have made significant strides, and as time has gone by and open source options have demonstrated stability, there are minimal concerns that modern open source software presents any risks that are not inherently present in other software options. Open source tools have become extremely easy to install and setup, often requiring only a few clicks to get downloaded, installed, and opened for the first time.
While cost can be a consideration for some situations, there are a plethora of free open source software options that can match the data analysis functionality found in Office with the added benefits of efficiency, reliability, and portability. Additionally, the benefits and relative increase in popularity of open source software options has put some cost pressure on commercial software vendors to make their software more affordable, which benefits analysts everywhere regardless of their software preferences.
If you’re considering making the transition away from using Office as your primary tool for data analysis, the key functionality that you should look for in your alternative options includes:
Data should be stored in something like a SQL database that can be accessed across the organization’s network (with proper security, of course) meaning that more people can perform data analysis simultaneously and also help ensure that they are using the same source for starting their analysis. Building a data repository that is trusted to be accurate and clean is the most important starting step for robust analytics.
The goal is to build data analysis that is easy to repeat when data is refreshed or if a mistake is found. Having code or data work flows that perform analysis and calculations will be easier to review for potential issues, easier to share with other analysts, and easier to update and maintain when things change.
As technology evolves, having a tool that has a wide variety of methodologies available, especially the latest and greatest options for complicated or advanced techniques in machine learning and artificial intelligence can be very helpful. Even if the tools you choose to use don’t have everything that is available on the cutting edge, tools that are updated with new functionality are preferred.
As you search for the best place to start your next data analysis task, try a variety of options. There’s never been a better time to dive into new technology tools for data analysis. With so many excellent possibilities, everybody should be able to find one they like using.
If you have additional questions or need help migrating your existing work from Office to something more robust, efficient, and reliable, let us know and we can help!
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