Mastering the Art of Data Visualization: Crafting Engaging Visual Stories for Impactful Insights.

From a disjointed approach to your analytics to data-informed organizations: Embrace the power of data for better decision-making, lower your risk exposure, and sustainable business success. Learn how the?Graphiti?solution can help you empower your GTM organization. Discover the opportunities and challenges of this transformative shift, and harness the?full potential?of your data assets for long-term growth.

A study by the Harvard Business Review found that companies that use data visualization to make decisions are 23% more likely to be profitable than those that don't. Another study by the University of California, Berkeley found that people are 60% more likely to remember information when presented visually.

Putting these two together, you see the picture. Data visualization can make you a more agile, data-informed, and efficient organization. How often you've seen the CEO sharing the big tables or numbers without appropriate visuals that nobody remembers after the meeting? You will only remember or recall the numbers from that meeting if you are a trained finance professional or executive. There is a reason why Investor Relations departments or executives use their time to depict the results through illustrative dashboards so that audience can faster understand but also recall the numbers in the conversation. In other words, our brain is wired to understand through storytelling visuals. I won't go through the history of primal cultures and their depicted day-to-day scenes. However, there is something in the visuals that help us understand the story of others.

Before diving into how to create a compelling visual, let's try to understand the most common mistakes analysts or managers make to create a compelling story with visuals.

• Using the wrong chart type.?Many different chart types are available, each best suited for a specific data type. For example, a bar chart is a good choice for comparing categories, while a pie chart shows proportions. Using the wrong chart type can make it difficult for viewers to understand the data.
• Using too much data. When visualizing data, focusing on the most critical information is essential. If you include less data, it can be manageable and easier for viewers to focus on the key insights.
• Using poor design.?The design of your visuals is just as important as the data itself. Make sure your visuals are clear, concise, and visually appealing. Use colors, fonts, and layouts that are easy to read and understand.
• Not considering the audience.?When you're creating visuals, it's essential to consider your audience. Whom are you trying to reach with your visuals? What do they need to know? Tailor your visuals to your audience's needs and interests.
• Not testing your visuals.?Before you share your visuals with anyone else, testing them with a small group is essential. This will help you identify any problems with your visuals and ensure they're effective.

The?data visualization?has seven (7) principles grouped into two (2) parts that can help you with better storytelling. I'll briefly describe them at this point before diving deeper into them in the next series of articles. It's important to dissect each stage separately to understand the optionality and how to select the right configuration for these visuals depending on the data nature and the targeted audience.

Part 1 - focus on making the data connected with the format.

1. Correct Data?In this, the focus is on identifying and selecting the most relevant and meaningful data to be visualized. It involves understanding your analysis's or presentation's objectives and determining which data points best support your message. The key here is to have the correct data for your data story. You can't talk about details if you have only totals.
2. Visualizations?Choosing the appropriate visualizations is critical to effectively communicating the insights. This involves selecting charts, graphs, or other visual representations that best represent your data's relationships, patterns, and trends. The goal is to use clear, intuitive visualizations that align with the information being conveyed, enabling your audience to depict the insights you found in the data quickly. There are no better or worse visuals, but whether they fight the found insight.
3. Configuration?The configuration of your data visualization plays a significant role in its message. This phase emphasizes arranging the visual elements, such as labels, axes, legends, and colors, to enhance comprehension and readability. As an analyst, you must understand the audience's expectations around how they review or would like to see the data presented. Paying attention to your audience's point of view should help you configure your visuals in how the audience consumes the data. If your audience must do their math, you failed to configure your visuals properly.
4. Remove Noise?To create a clean and focused data visualization, it's essential to eliminate unnecessary elements or distractions that may obscure the main message. This phase involves removing any visual clutter, redundant information, or irrelevant details that could hinder the audience's understanding. By eliminating noise, you ensure that the data visualization delivers a clear and concise narrative, guiding the viewers' attention to the most critical aspects of the data. Getting things right means curating the information so that you maintain the found insight you convey in your message. You won't be able to discuss or depict everything you have in your data to take a deliberate approach to select only what you need. Anything that drags attention outside your message puts you at risk of derailing the conversation and ending without a conclusion.

Phase 2 - tune the data into your audience by asking key questions.

1. Focus attention?To engage your audience effectively, it's important to direct their attention to the most critical aspects of the data. This phase encourages asking questions to identify the key insights or findings most relevant to your audience's needs or interests. By highlighting these focal points through thoughtful design and storytelling, you can ensure that your data visualization captures and retains the audience's attention.
2. Eliminate complexity.?The?data can be intimidating or overwhelming for some audience members. This phase focuses on making the data visualization approachable and accessible to a broader range of viewers. You can bridge the gap between technical data and non-technical audiences by simplifying complex concepts, using familiar language, and providing contextual explanations. Making the visualization approachable encourages active engagement and facilitates a deeper understanding of the information presented.
3. Building trust?in your data and visualization is crucial for effective communication. This principle involves addressing potential concerns or skepticism by proactively answering your audience's questions. By providing transparent information about data sources, methodology, and any limitations, you can instill confidence in the data visualization's accuracy, reliability, and integrity. Instilling trust establishes credibility and encourages the audience to rely on the insights derived from the visualization.

Conclusion:?Data visualization is a pivotal tool in modern decision-making processes. The time you spend making a decision matters, and visuals help you use the shortcut. It's that simple. Based on the survey, visuals can enrich your decision-making process, increase organizational awareness about specific metrics, and keep your teams focused on working towards a clearly understood goal. However, the most significant benefit is the insight that each of these visuals provides your teams, helping them internalize and make them think about their contributions. Knowing the assumption or driver behind the visuals and the ability to drill down through several dimensions helps to educate the audience and drive the correct conclusions or action plans. The time between understanding and acting is critical. Visuals can help with that if done right.

The other benefit to the audience is to ability to ask the key questions. This involves focusing on critical aspects of the data, simplifying complex concepts to make them approachable, and instilling trust in the data and visualization by addressing potential concerns and providing transparent information. As an analyst, you must demonstrate the versatility of points of view. Putting yourself into your audience's shoes will help you guide them through the questions and answer discovery process.

Analysts can create data visualizations that effectively tell a story, engage audiences, and facilitate decision-making by understanding and applying these principles. In subsequent articles, we will delve deeper into each principle, exploring various techniques and considerations to optimize the impact of data visualization.