Page 220 - Artificial Intellegence_v2.0_Class_11
P. 220
1. The collection of huge data is quite difficult.
2. After collecting the data, it is difficult to prepare the data which includes updating, cleaning, and keeping only the
necessary portion.
3. Building variables and categorising variables which is known as Data Wrangling is a tedious task.
4. The next step is Data Analysis which includes various tools for visualization and conducting basic to advanced
analysis that requires a skilled team of people.
5. The final stage is data insight generation wherein the right interpretation as required by the consumer or stakeholder.
This also requires a lot of experienced people.
Despite all these difficulties, data storytelling has gained a lot of momentum in recent years because of its impact on any
organization in terms of growth, economy, and other life-changing scenarios. Here’s why data storytelling has acquired
a place of importance:
• It is an effective tool to transmit human experience. Complex data can be made meaningful, relevant, and interesting.
• Even after data analysis, it does not assure to bring change in the people unless it is narrated properly.
• The analysis which is having both data and analytics with a good narrative is much more effective than anecdotes
or personal experiences.
• There is a standardization of communication, which makes information memorable, easier to retain and take better
decisions.
Even after data analysis, there is no assurance that the analysis alone can bring change in the people unless it is
narrated properly. The analysis which is having both data and analytics with a good narrative is much more effective than
anecdotes or personal experiences.
Storytelling for Audience
A story can be used to persuade, motivate and inspire in ways cold facts, bullets, and guidelines cannot. The seven key
points to make our stories compelling, engaging, and interesting are:
• Engage your audience in your story
• Make a connection to your personal story
• Create suspense until the end
• Bring characters to life
• Show, not tell
• Create an ‘aha’ moment
• The climax is expected to have a positive outcome
Now, let’s see the elements that make data storytelling interesting, fruitful, and insightful:
• Characters - who populate the story.
• Plot - what happens in the story.
• Setting - where the story takes place.
• Point of view - participation of narrator and/or audience.
• Style - skills acquired for telling the story.
• Literacy devices - acquaintance with technology.
218 Touchpad Artificial Intelligence (Ver. 2.0)-XI

