Demystifying Data Part 4: Data Analysis – You have the data, now what?

You’ve identified your questions, you’ve tracked down your data set, you’ve cleaned and verified it – now you need to do something with it. It’s party time!

The good news is that these days there is no shortage of tools that can help you put your data down, flip it and reverse it. If you don’t know where to start, the amount of choices can feel overwhelming. Doing a general search will likely give you a confusing listicle of “top 50 tools you need to be using right now!” Before getting all blurry-eyed with options, as stated in previous posts, ask yourself some basic questions: How much data do I have? What am I trying to accomplish?

Here is a short list of data analysis tools the SHIFT team uses on a daily basis:

Microsoft Excel/Google Sheets

Using a spreadsheet for analysis is a commonly used method. Microsoft Excel and Google Sheets are two really good options. If you don’t have access to either of those, there are a fair number of open source spreadsheet programs available for use. Why use a basic spreadsheet? You can create and format workbooks with multiple tabs and contexts, track data, build models to analyze data, write formulas to perform calculations on that data, pivot the data in numerous ways, and present data in a variety of charts. Using a spreadsheet is the go-to option for most PR and marketing professionals. Keeping your business intelligence (BI) data in a spreadsheet allows for quick reference and informed decisions.


Tableau is a business intelligence (BI) tool that can create visually-appealing reports, charts, graphs and dashboards using your data. These reports are interactive and are easily shared with you audience – much like the data in this recent post. Tableau has both free and paid versions. Tableau is a data visualization software that works with data from Excel, Access, statistical files (such as SAS and SPSS), Google sheets and web data connectors. Why Tableau? Tableau can handle larger volumes of data, more than a standard spreadsheet. With Tableau desktop, for example, you can save your workbooks and just refresh the dataset, updating your analysis in real-time. Tableau also has an active community online and on Slack where analysts share their work, ask questions and learn from each other.


R is an open source programming language and software environment for statistical computing and graphics. R is a tool for statistics, data analysis, and machine learning. R enables you to interact with many data sources such as databases (like Excel and Access) and other statistical packages (SAS, Stata, SPSS, Minitab). Why R? R can be used to conduct predictive analytics; a method being used more and more by organizations to inform business plans using historical data. These predictions allow business leaders to get ahead of slower sales seasons by highlighting where those peaks and valleys have historically fallen and likely will fall moving forward. Many, SHIFT included, use R and Tableau together. Once you’ve conducted your statistical analysis with R you can import the data into Tableau for visualization.

…which will lead us into Part 5: Telling your story through data.

Katie Lioy

Director, Marketing Technology



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