Excel spreadsheets, SQL databases with thousands of rows of data or a webanalytics account (Google Analytics, Adobe Analytics, etc.) including several years’ worth of data… Unprocessed, it is impossible to make sense of this data. Thankfully, data visualization—or dataviz—helps you get a clearer picture of your data!
What is data visualization?
Data visualization is a technique used to represent datasets visually so that people can quickly grasp key information. Still not 100% clear? Let’s take a real-life example. Since 2014, the French train company SNCF has organized its lists of reported lost property declarations into a database which can be extracted as an Excel spreadsheet with over 800,000 rows of data. But how can we see which type of object has been the most frequently reported as lost? Without reprocessing the data, this is impossible.
To start with, you could process the Excel spreadsheet using a data processing software. Tableau, for example, achieves the results pictured below (see part 2 of this article for more information). The data has been aggregated and is much easier to read. We can now quickly see that luggage is the most frequently lost item.
But you could make things more intuitive. Using Tableau again, we can also visually show the data in a pie chart. Immediately, we can see that luggage accounts for 29% of lost property declarations, making it the most frequently lost item:
The example above is the very definition of data visualization: processing raw data and representing it visually. Often, this is done using conventional graphs such as bar charts, diagrams, curve or bubble graphs. However, any type of visualization is valid as long as it is capable of conveying the important information, such as cartography, heat maps and Sankey diagrams. Or even more innovative and fun forms, such as this ‘heartbeat’ visualization by Manhattan Population Explorer, which shows the flow of people in Manhattan, hour by hour over the course of a week:
Data visualization: what does it do and who is it for?
Continually increasing amounts of data and ever-growing numbers of indicators have made it very easy to get lost in an information overload. It is therefore essential to be able to access useful information quickly.
Data visualization allows you to:
- Make complex data accessible to everyone by summarizing it
- Answer questions when the necessary information lies in masses of data
- Highlight the message you want to convey and back it up with proof
Feel like you’re looking for a needle in a haystack? Well, data visualization makes the needle bigger and instantly visible. Sounds like magic doesn’t it? The good news is that you can use data visualization on all corporate levels, from the most operational to the most strategic of tasks. Here are two examples of how data visualization can be used within a company:
- For an agency managing an advertiser’s SEA campaigns: the visual representation of the data obtained from Google Ads’ Auction Insights allows the agency to see instantly which campaigns need to be optimised to secure a dominant position on the results page. Thanks to Auction Insights, advertisers have access to information about their campaigns’ performance in auctions and the impression share of their campaigns, as well as those of their competitors who are bidding in the same auctions.
- For the head of communications in a company: the visual representation of the company’s web traffic or the generic requests entered into a search engine (such as ‘which insurance is best?’ for an insurance company), allows the company to identify traffic peaks and seasonal trends. This information can be used to create the annual communications plan.
Data visualization: what are the tools available to help you format your data?
If you want to visualize your data, you can choose from a range of different solutions. They are characterized by their effectiveness, their different features and the objective of use. For example, Excel is a perfectly plausible option for starters, as it includes many different types of charts. However, its connection and processing capacities are too limited to work with third-party platforms or large databases. Other more adapted tools exist, such as Qlik, Spotfire and Power BI. Based on our own experience, we have shortlisted two tools in particular: Tableau and Data Studio.
1. Tableau: data exploration
Tableau is a Business Intelligence software. Although it is not free, it has many advantages, including:
- its number of connectors, which means that it can be linked to over 60 different sources (Excel, MySQL, Google BigQuery, Google Analytics, Oracle, Salesforce and many more)
- its ability to transform data, which allows users to rework their data sources or combine several different sources together (through joining or blending)
- its powerful processing capacity thanks to its many functions (over 160) and its quick calculation capabilities
- its number of different visualizations: there are currently more than 22 types and it is also possible to create your own
Tableau is therefore an ideal tool for data exploration. It also gives you the opportunity to create detailed dashboards (reports which summarize performance results and often use data visualization) which build on its powerful processing capacities.
2. Data Studio: showing and sharing data interactively
Data Studio is a free, online data visualization solution. It is part of the Google Marketing Platform suite. Its main strengths are:
- its native connection with other Google tools (Google Analytics, Google Ads, Search Ads 360, Campaign Manager, etc.). Thanks to this, users can access data in real time
- its accessibility, thanks to its sharing features which allow several users to work on the same file at the same time, in the same way as Google Drive. Users can also share the document immediately with other people
- its ease of use, thanks to its simple interface which allows users to customise every chart
- its interactivity as users can instantly filter different types of data visualization
Data Studio is the ideal tool if you need to create dashboards quickly which are easy to share internally and externally. The visualization below was generated by Data Studio and interactively represents the SNCF example mentioned earlier.
As you may have understood, data visualization is critical if you want to make your data understandable. It extracts and highlights the information you need to answer specific questions. Knowing how to visualize your data means managing operations better and gaining a better insight in your business, on all levels!