Why? The importance of data visualisation in business intelligence
In our hyper connected world we’re all aware of the critical importance of accurate and timely business data. Just as vital, of course is the need for this huge and ever-expanding mass of information to be summarised into clear and digestible storylines that non-analysts can easily grasp.
This is where great data visualisation comes in. Large chunks of numbers and text don’t easily answer questions such as ‘How do we differentiate ourselves from our competitors?’ and ‘Are we meeting performance targets?’ It’s crucial that we’re able to quickly and simply access the numbers using graphs, charts and data visualisation techniques.
What is data visualisation?
Say, for example that there are four dimensions that describe your raw data – eg period, product, state and age bracket. The data scope reports on 24 periods across 20 products, six states and six age brackets. In other words, 24 x 20 x 6 x 6 – resulting in over 17,000 possible lines of data!
As humans we’re almost incapable of quickly deciphering it all, and then using it to make timely business decisions. With data visualisation these 17,000 lines can be succinctly and clearly summarised in the form of pie, bar or line charts. Alternatively, for a more statistically inclined audience, tools can include distribution of pair plot charts or equivalents, so that hidden messages can be uncovered via trends, spikes or correlations.
Who needs data visualisation?
As the volume of data grows exponentially, so the need to visualise data becomes more pressing, across just about every organisation. Whether you’re an analyst needing to present the findings of a data exploration exercise, a manager arguing the case for more staff because of weekly deliverables being missed, or a business owner wanting to ascertain sales timings and markets, you’re going to need data visualisation. No matter what your industry, it’s become an indispensable tool to communicate clear and persuasive business stories and information.
When should you visualise data?
If your manager provides you with specific instructions on exactly how information is to be presented, you’re in luck. Half your work’s already done. In the real world, of course, this doesn’t often happen.
So, rule of thumb: Whether you’re communicating or commenting on data exploration outcomes, calling for action on a pressing issue, or simply sharing data, your best option is to always provide visuals, along with a more detailed view. In fact it’s best not to present the latter unless you’re specifically asked to do so. Start with a visual presentation and let that spark the conversation. You’ll never be able to predict all the questions that stakeholders will ask, but do prepare yourself as much as you possibly can. Your story will, of course, continue to evolve with your business.
HoW should you visualise your data?
The best data visualisation techniques involve art just as much as logic. These may be as straightforward as using the defaults offered by your data visualisation tool of choice (eg Tableau, Qlik, Power BI, etc. However, subtle tweaks will make all the difference to the appeal and accessibility of your presentation.
Putting yourself in your stakeholders shoes plays a vital role when it comes to tailoring your visuals. Who exactly is your target audience? Are recipients senior or mid-level, details or big picture oriented? Just as importantly, what message do you want to convey, and what data visualisation types will be best suited to this?
If you’re after more help with the data visualisation game, you’ll find a number of useful books on Amazon.com. I’ve found Storytelling with Data by Cole Nussbaumer Knaflic to be a particular standout.
Have any tips or tricks on data visualisation? If so, please share them in the comments below.