Data visualization means one thing to someone doing a few charts for a PowerPoint deck, something else to a data journalist, and something different yet again to someone analyzing billions or trillions of rows of data in industry. Learn about the tools, systems, and processes being developed now that are democratizing access to all of us, at every level.
(upbeat music) - Why do organizations visualize data? And you can't really ask that question without repeating the question with a one word change. Why do organizations analyze data? It's not just for their health, right? It serves a purpose. Actually, you know what, you could say it is just for their health, because the health of every organization depends on it. It's about knowing what's going on in the organization so you can optimize for positive results. This applies to every corner of a company. The performance of its employees, the happiness of their customers, efficient processes, you name it. Of course, it's primarily aimed at improving their bottom line. Whether that's profits for a company, impact for a non-governmental organization, or however they define bottom line. We look at data to know what's happening, to predict future possibilities and prescribe changes to improve. In other words, data analysis and visualization is all about enabling smart decisions. That's what it's all about. So, how do you use data analysis and visualization to enable smart decisions? I have a few tips to keep top of mind. First, you need to understand your business or the corner of your business that you're focused on, what you can optimize around, and how to hone in on just the data to allow you to measure and optimize on exactly the right thing. One example, when thinking about data visualization, was a great quote form Elijah Meeks who said, "If you represent a funnel as a bar chart, then the only decisions you can make about it are optimizing that bar chart". In other words, the variables you focus on and the visual used to represent them forces you to only make decisions around optimizing for those variables. Choose your variables and visuals carefully based on your deep and clear understanding of the business and data and strategic goals. Second, you need to know your audience. If you're preparing data visuals for the CEO of a company, or a congressperson, or some other high level figure, your data communications will likely be high level summary data. Generally, the higher you go in an organization the less details required. So, you won't prepare a 40 slide deck with countless details and bullets about some arcane corner of operations for that person. Conversely, if you're presenting the same information to the mid-level manager in charge of that arcane area of the business, that 40 slides with all the details may be exactly what's needed. Now third, scale is always going to be an issue to consider. You can create beautiful, unique, bespoke data visualizations based on complex hand-coded analysis and sometimes that may be necessary. But odds are most of your work will need to be repeatable, automatable, self-serve, and scalable throughout the organization. Your bosses will expect scalability by default in an organization, so strive toward this as a goal. And when something deserves a bespoke approach, advocate for it if it's good for the business. Scale doesn't always have to drive the boat, maybe just like 99% of the time, right. Fourth, be a communicator, not a chart maker. Okay, your job is to enable decisions which can only be done based on knowledge, not data, not the facts, but knowledge. Communicating effectively means providing knowledge to your audience in a way that they can learn from it. As a data analyst, or data visualization specialist, you are a communicator, not a dashboard builder. Never reduce your role to just executing tasks. Be strategic, deliver knowledge always, contribute to the conversation. Those are four key ideas that you can take into any situation and any organization and they will serve you well in your role, analyzing and visualizing data to enable decisions. Up next, we're going to talk to Diana Yoo, Head of Data Visualization Design at Capital One, about her experiences leading data visualization in a company that has built an entire practice around it. She has some really interesting things to say about how the democratization of data is helping Capital One improve its business and its customers' relationship to their finances.