Data Storytelling 101: Determining Your Data Story’s Point of View
This article dives into the first step of your data storytelling journey: choosing a compelling topic from your dataset using Point of View (PoV) analysis.
Foreword
Dealing with large datasets can present a significant challenge. The huge amount of information often leads to analysis paralysis, where you’re overwhelmed and unsure where to begin. Conversely, there’s a risk of inclusion bias, where you want to include every finding in your report or dashboard. The desire to include every finding, while understandable, can hinder focus and clarity — crucial for effective storytelling. This article will explore how to sharpen your focus on a single main topic. We’ll then delve into how to break this topic into sub-topics that ultimately interconnect.
Case Study
There are numerous approaches you can take to start exploring your dataset. For instance, when opening the dataset, you can start by classifying columns into several groups. For our case study, we’ll utilize the dataset provided by the Onyx Data DataDNA April 2024 challenge.
The TMDB Movies Dataset, boasting over 900,000 entries, makes for a compelling case study due to its massive size. This dataset provides a rich resource for exploring data storytelling techniques.
I participated in this challenge with a report exploring the world of renowned movie directors. Further details can be found here:
In this article, I’ll explore my thought process behind choosing this topic.
Have you ever been amazed by the visually stunning worlds brought to life on the big screen? Directors like Christopher Nolan are masters at this, but their creations come at a cost.
My fascination with Christopher Nolan began with Interstellar, his mind-bending 2014 sci-fi epic. It struck me how directors like Nolan can craft such immersive and extraordinary cinematic experiences by combining their creative genius with substantial budgets (often directing and producing the films themselves). This led me to wonder: how much does it actually cost to bring these visions to life, and is the financial investment justified by the potential profits?
Step 1: Establish a Clear Main Topic
The dataset contains 25 columns. To begin the analysis, I will categorize these columns into several groups to facilitate further exploration. I have created a mind map to aid in this process.
A mind map is a visual tool used to organize information. It’s like a brainstorming session captured on a page.
I’ve categorized the columns into three groups:
- Movie Details: This group contains information about the movie itself.
- People: This group includes everyone involved in the movie’s production, from cast and crew to directors, producers, writers, and composers.
- Metrics: This group focuses on numerical data that helps us understand the movie’s performance. Metrics can track progress, success, and overall effectiveness.
Including all these columns in a one-page report might be too overwhelming for the readers. However, if you’re interested in creating a thorough exploratory dashboard, it’s not entirely out of the question. To streamline the process, I decided to focus on a single main topic from the available columns that I found intriguing to explore: movie directors.
Step 2: Refine Your Focus with Subtopics
Here comes the exciting part: endless possibilities! You get to choose where to take your chosen topic. A great way to start is by brainstorming subtopics. Simply connect your main topic to the other columns in the dataset.
Since I’ve chosen directors as my Point of View (PoV), I can now explore how they relate to other relevant variables within the context of my main topic. Here are the variables I’ll be connecting the directors with:
Having identified your main topic and subtopics, the next step is to structure your report for optimal clarity. This ensures your readers can easily grasp the intended message. However, I won’t delve into the specifics of structuring the flow here, as a previous article covered that topic in detail.
Thank you for reading! I hope you gained valuable insights from this article. Follow me or subscribe to my newsletter for more data storytelling content.
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