How have my visualization values progressed as a fresh data analytics and visualization MPS graduate?

After I completed my undergraduate degree, my career took off in higher education administration. Higher education is a hodge-podge of soft and physical skills and I've soon picked up how to build relationships with students (customers, in a strange sense), faculty, administration, parents, high school and college counselors, and transfer advisors. An underlying part, however, is building an understanding of my recruiting territories and how to effectively build enrollment - decisions are made largely through data in these territories.

I always thought I hated numbers, I'm bad at it, etc. until I realized it was quite the opposite. I've picked up on the value of data, whether it's higher education or not, and as a visual communicator and data visualization pivoter, I've come to value specific parts on what can make effective visual information. Here's a quick interpretation of what I value the most in a visualization (other than the data :))

Graphic Elements: Where, how, and when should I place a part of a graphic element for an effective visualization. Color, texture, shapes, sizes, typography, and space are important to think about with an audience in mind. With that, what is the audience getting out of it, how quickly should they perceive information, and is it effective enough for a call to action or for a better understanding on a complex topic. Can they do this within a couple of minutes? The physicality of the piece can matter as well - does the audience need to make a deep dive into the graph or is it a physical paper to take a look and come up with quick questions to induce conversation?

Storytelling (visual and conceptual): I want to make "life" out of the data or topic that I'm creating a visual for. Based on a solidified audience, do they need to feel like the product or topic is serious, relatable, or entertaining? Should they feel confident, scared, or hopeful? Does feeling matter or is it important for a call to action? Some topics or data may be text-heavy, others not so much.

Exploratory or explanatory: I generally want the user to be on a "quest" when they are checking my graphics, but this may not always be the case :) Some topics, stories, or data need a plain and easy explanation in order to draw conclusions or for quick decision/calls to action. Sometimes, data could be fun to "walk" through, as with my analog horror exploratory data visualization prototype.

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My Book Recommendation

To read further, and from an expert on visual storytelling, I highly recommend Ellen Lupton's Design is Storytelling (2017):

Ellen Lupton: Design is Storytelling

Description: This book explores the psychology of visual perception from a narrative point of view. Presenting dozens of tools and concepts in a lively, visual manner, this book will help any designer amplify the narrative power of their work. Use this book to stir emotions, build empathy, articulate values and convey action; to construct narrative arcs and create paths through space; integrate form and language; evaluate a project's storytelling power; and to write and deliver strong narratives.