How do we describe something as beautiful? When we think of beauty, data is perhaps the last thing that comes to our mind. Data as raw texts and numbers can be boring or not appealing at all, but when the same data is represented in colours, shapes, diagrams, graphs, it becomes appealing, and when done right — beautiful.
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Why Visualise Or Make Data Beautiful?
Data Visualisation is not just about making the data beautiful, the catch is, when the data becomes beautiful it makes data more interesting and engages the user and delivers information faster. Good visualisations can also help in digging up new exciting insights from the data that was not originally thought of before building the model.
Visualisation is a great way to understand the relation between numbers. Being a Data Scientist or Data Analyst or Business Analyst, looking at thousands of data points and explaining the relationship to the clients can be a hefty task and not to mention how boring your clients can get. But when the same data points are expressed in the form of colourful and appealing visualisations the entire process becomes more engaging and thus more efficiency in delivering information.
Here are three steps you must follow to success with data visualisations
1) Planning and Organising
If you run an organisation that is driven by data, data visualisation is an important skill you must have. One of the most important things to have in mind before you start building your model is that the more beautiful the data, the faster the information is delivered and thus more the users or clients want. The moment you deliver a beautiful visualisation, you will most probably be asked to give something more. Keeping up to the expectations of your users can be challenging.
If you are an organisation here is a list of questions you should ask yourself before building your model:
- Who will create the visualisations? Is there a Data Visualisation team or trained employees?
- What visualisation tools will you use to build the model?
- How will you handle requests for changes from clients? How will you manage user expectations?
- How will you manage existing reports and who will manage them?
- How will you distribute reports (online, via email, etc.)?
The quality, choice of tools, managing user expectations, delivery time, communication and organisation of reports are key factors to success.
If you are a beginner starting your journey to become a Data Scientist or Data Analyst or Business Analyst then following tips will get you to success with visualisations.
- Setting the best foundation
- Exposure to all tools
- Expertise in at least two of the most popular tools of Visualisation
- Practice
2) Standards for Consistency
When you are given a lot of options to make your Visualisation beautiful by the use of a variety of styles, graphs and colours, naturally you might get confused but always keep in mind that just because you have lots of styles to create a visualisation doesn’t mean you have to use it all at once.
A wild mix of styles on each visualisation you create will only lead to confusion and displays amateurism which will result in a bad impression among your top clients. Hence it is important to stick with a standard template for all the visualisations you do. Using a template will also give you more time to spend on analytics than wasting your time trying to figure out what style to use every time you build a model. Using style guides can greatly help in combating inconsistencies in building models.
3) Keeping Your Knowledge Up-to-Date
There are 4 key points to note:
- Knowing what you have already done and improvised on it.
- Interviewing the clients/users of your visualisation to understand their expectations.
- challenge your teammates
- Use your resources well
Your previous works will give you the best examples and ideas to improve. Asking your stakeholders for opinions on improvising and challenging your own team to put their efforts and giving them a chance to contribute, all these will benefit and give you an idea of how to proceed with. It is also important to use all the resources efficiently to stay updated with all the tools and techniques.
Outlook
Data Visualisation is more than putting your data in coloured graphs, data visualisation gives life to the data. It gives more meaning to the data that can be easily transferred or passed to audiences with less effort than explaining to them with just numbers or texts.
The post 3 Things You Must Know Before You Start Working On Data Visualisation appeared first on Analytics India Magazine.