When data visualization contributes to winning a war… Excerpt from Churchill War Room bunker in London, 1944–45.

The Best Data Visualization Solution

I recently stumbled on this question in a digital analytics forum:

I would like to open a discussion about tools for visualization of digital analytics data. I would like to know your opinion about this topic, what tools for data visualization you are using in your organization and what is your experience with them.

That’s a great question, although, as is often the case, it can only be answered appropriately if there are more details about the needs and objectives.

Weight of bombs dropped on enemy vs Great Britain, 1940–1945.

I recently had the opportunity to visit the Churchill War Rooms Museum in London. I was simply amazed by the simplicity and efficiency of data visualization used in 1945.

This reinforces my opinion:

Analytics = Context + Data + Creativity

Before jumping into a solution, always make sure you thoroughly understand the goal. As demonstrated by the War Room graphs, understanding the ultimate goal and creating simple, effective solutions is the best approach.

There are numerous resources to help you make a choice, but an article like “The 38 best tools for data visualization” might not be the best approach — honestly, this is an example of an SEO-oriented content, not really an “article”. It is merely an inventory of solutions and I doubt the author actually evaluated each of them… PC Mag published a summary table and more in depth article of “The Best Data Visualization Tools of 2016” — already better because it focus on one type of solution and provide more details. You might want to check G2Crowd and TrustRadius, those are also very useful. Of course, there’s always The Forrester Wave: Agile Business Intelligence Platforms, Q3 2015.

The big questions are:

  1. What are you trying to achieve?
    a) Create dashboards to effectively communicate with your stakeholders; or,
    b) Empower analysts with a self-service, data wrangling slice & dice tool?
  2. What are you/your team abilities and experience? Are you a marketer who would be satisfied with a “black box” tool, or a data scientists who crave for raw data and a good data munging challenge?

Let’s put the potential solutions into a couple of categories:

Lower maturity/easy to use/out of the box solutions

Those would be things like Google Data Studio (still in beta and has some limitations, an important one being the limited connectors — namely, only Google sources + MySQL) and the reporting included with your web analytics tool of choice. There are also numerous cloud-based solutions that offer many connectors and prebuilt visuals, such as DashThis. They tend to be aimed at less experienced analysts and are very easy to use.

Data Studio

Mid maturity/integration/flexibility

Mileage greatly varies in this category: sometimes they have wonderful visuals but suck at data integration; sometimes they are easy to use but difficult to develop, etc. A popular solution among agencies and practitioners in the digital analytics space is Klipfolio — many connectors, good visuals, many learning & support resources, but sometimes difficult to develop.


Higher maturity/powerful/universal solution

I would say Tableau comes at the top of the list — most experienced analysts I know use Tableau Desktop. It is a very powerful slicing & dicing (exploration) tool for analysts, but also an amazingly elegant solution for dashboards where your stakeholders can interact with the data (within the limits of what the dashboard author allows). Tableau Server scales nicely, and there are amazing learning, support, community to do everything you want. When it comes to web data and API sources, you will most likely have to rely on an ETL tool (Extract-Transform-Load) to prepare the data before use in Tableau. One such tool, specialized for GA data, is Analytics Canvas.

Analytics Canvas

Build vs Buy

And there is one last category: hard-core build-from-the-scratch solutions, such as using R or python with visualization libraries. This is often the data-scientist approach and much more geeky, and honestly, sometimes very cool too! But… you should really consider if a solution like Tableau could get you faster and more easily to what you want… This is the old debate of “build vs buy” all over again!

Disclaimer: I can only talk about the tools I use and know. I receive no compensation from any of the mentioned vendors (wouldn’t that be great!)

Stéphane Hamel is a seasoned consultant, teacher and speaker. He shares his passion for digital analytics — be it technical ‘how to’ or assessing organizations’ digital capabilities and maturity.

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