10 Data Storytelling Tips for Beginners Working in FAAMNG

10 Data Storytelling Tips for Beginners Working in FAAMNG

According to Gartner, data storytelling will be the most widespread means of consuming analytics by 2025

Humans are inherently storytellers and use storytelling as a medium of sharing information. Nothing works like a compelling narrative when it comes to putting across a nuanced idea across. Data and numbers though give a clear picture when measured in a few parameters, it is a clumsy affair with Big-data. The hoard of solutions such as Business Intelligence software, dashboards, and spreadsheets can only tell what is happening and not why it is happening. In this context, data storytelling comes as a magic wand in the hands of businesses to spell the magic of business analytics. According to Gartner, data storytelling will be the most widespread means of consuming analytics by 2025. As the importance of data storytelling capability is only going to surge in the future, particularly in FAAMNG companies, we have put together the top 10 data storytelling tips for beginners working in FAAMNG companies.

  1. Choose the right tool: Given the number of tools one has access to it is quite natural to get lost in the maze of confusion. Just keep in mind what you want to achieve, the message that needs to be communicated, and the kind of audience.
  2. Remove junk: It doesn't mean killing data points, but removing unnecessary elements such as unnecessary charts, illustrations, drop shadows, ornamentations, etc. Data visualization can do all the heavy lifting provided the right tool is chosen.
  3. Make more corrections: Once the visualization is created, take a step back and consider what simple elements can be added, tweaked, or removed to make the data easier, Viz., a trend line to a line chart, or remove a few slices from the pie chart.
  4. Include Zero Baseline: A zero baseline gives more context to the data and hence it makes sense to include if necessary. However, the scale can be truncated to showcase variancies if relatively small fluctuations in data sound meaningful.
  5. Choose Efficient visualisation: Visual consistency is an essential ingredient if you want the reader to be able to compare at a glance. Presenting too many visualizations at a time will only overhwhelm the reader. Avoid it.
  6. Place the visualisations appropriately: Two stacked bar charts meant for comparisions won't serve the purpose if placed too apart. It's like playing a lost game.
  7. Tell the whole story: Maybe you had a 30% sales increase in Q4. Exciting! But what's more exciting? Showing that you've actually had a 100% sales increase since Q1.
  8. Keep header simple: Steer clear of verbose and flowery language keeping all the text simple and to the point. Less is more.
  9. Make Purposeful Callouts: Callouts should be used intentionally highlighting relevant information to provide additional context. Definitely, they are not meant for filling space.
  10. Label the lines directly: It is always beneficial to include data label with data points. This avoids the need for going for a legend or a similar point.

Related Stories

No stories found.
logo
Analytics Insight
www.analyticsinsight.net