Telling a Story with Data.

Storytelling was data is about presenting your data to an audience in an engaging manner whilst at the same time ensuring that you're providing them with information, which is meaningful and relevant to their needs. Remember they may well be making decisions based on the information you provide so it must be accurate but also presented in a way that is easy to understand and offers insight which will help them in their decision-making.

Here are five tips, which should help ensure that your presentations are interesting and informative of the same time.

Number one know your audience, number two know your data, number three think about the structure number four remember the visuals, and number five be careful with your chart types.

Knowing your audience. You might think that your charts are interesting and look good, but are they what your audience needs before building a presentation you must define clearly what requirements your audience has from the data, make sure you know the following, do they have any particular questions which need answered? Do they want just the facts or would they be looking for why? If you tell them that prices have dropped rapidly over the last six months, do they need to know why that has happened or just the fact that they have dropped? Do they want a high level overview or a more technical analysis? What are their main goals and objectives? Do they need to explore the data for themselves? If so build, in plenty of slicers and interactive visuals.

What roles do they have? If you're presenting on current share prices for Amazon, you would report that very differently to a client interested in investing, than you would to the financial director of Amazon.

Number two, know your data.

When working with large data sets, it's easy to become overwhelmed, it can be hard to know where to start. The first step is to ensure you understand the data take time to explore it make sure you know, what each field contains and how that relates to other fields.

You will then have to most likely cleanse the data, take the time to do this, right. It will be worth it in the long run and provide you with data that can be properly analyzed and used to create some interesting visuals and insights.

Make sure it is accurate consistent and error-free.

Put the data in context. Do you need to find some more data to help explain a particular pattern or trend? So if you have a visual which shows a dip in sales in May it might be worth looking at some previous years or months to see if the same thing has happened before.

If you haven't been given a particular list of requirements from your audience, start exploring the data yourself, create some basic visuals start to look for anomalies patterns and trends which you can then explore further.

Number three, structure.

Data-driven presentations are like essays, they need structure, a clear beginning, a main content, and a conclusion.

Lay the groundwork at the start take time to remind the audience why they're here what they'll be hearing about and why it matters.

For the main content stick to a linear timeline our brains can cope without much more easily. Show contrast and compare and highlight key stats.

End with insights for your audience to take away.

Number four, visuals.

The difference between a good and a bad presentation can often be down to the visuals themselves. Your audience will lose interest trying to interpret or understand visuals which are too complex and difficult to read keep it simple by using the following guidelines.

One message per visual don't try and make several points in the one chart, this just makes it very hard to understand.

Use appropriate labeling, be descriptive in your chart titles. So instead of just share prices, indicate the time frame and the units. So share prices for Apple in USD, January 21 to July 22.

And be consistent with your colors, your fonts, your titles, and your layouts. If you center align one heading on a visual, center align them all.

Number five, chart types. Choose the right chart type for what you want to show, choosing the wrong chart type can confuse the audience or make it harder to read.

Each chart type is suited to a particular metric try and identify what metric you're showing in your visual and that will help guide you as to which charts would work best. So if you're comparing data smallest largest highest lowest use a column or bar.

Composition, one value as a percentage of a whole, then use pie or donut charts.

If you're showing trends over a period of time use a line chart. Or targets and goals, how they've been met use a kpi or gauge charts.

These tips will hopefully ensure your presentations are engaging easy to understand and provide your audience with exactly what they need.