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Data Visualization: Presenting Complex Information Effectively

Learn how to present complex information effectively with data visualization.

Article featured in KD nuggets

The purpose of data visualization is to present complex data in a way that is clear to understand and engages audiences. Visualizations make it easy to convey an overall message, highlight key insights, and can be very persuasive in terms of guiding an audience toward a conclusion.

In this article, we will consider how to present complex information effectively with data visualization in a simple five-step guide, we will also discuss its benefits and provide a few use case examples.

What is Data Visualization?

Data visualization represents data and information in a graphical way that is easy to comprehend. Visualizations can include charts, maps, graphs, infographics, and other elements that help to simplify data. This makes it easy to identify patterns and trends, spot inconsistencies and outliers, and help an audience conclude the data that is being presented.

Know Your Audience: A Guide to Preparing for Technical Presentations

A structured approach to creating addresses tailored to the stakeholders’ needs and concerns

Article featured in Towards Data Science

The ability to effectively present complex topics to an organization is a skill that clearly sets data professionals apart in the working world. It’s vital to distill intricate information into clear explanations when working with convoluted topics, and the success of this effort hinges on the ability to bridge the gap between complexity and comprehension.

This is particularly true when talking about the difficult topics found in data science, for example deep learning algorithms, Bayesian inference, and dimensionality reduction (to name a few).

This article is the first in a series on preparing material for presentations, in which I want to run through the strategies and techniques I use when creating presentations to transform high-level topics into simple summaries. This series will walk through the various methods I use when considering how to structure my presentations to be clear, concise, and effective.

Is quantum computing overhyped?

Quantum computing may be coming to the enterprise. Here’s what to understand about the benefits it promises, the risks it poses and how to prepare.

Article featured in Tech Target

Quantum computing is not overhyped. Rather, CIOs and IT leaders may want to pay more attention to the tech to understand the disruptions to come.

That’s the take of a number of industry watchers, including Nella Grace Ludlow, director of quantum computing and research professor of computer science at Wright State University.

While quantum computing is still in its early stages of practical development, some companies are already using it to solve difficult challenges. When technology firms are able to fully develop the technology, quantum computers could solve in a matter of seconds complex problems that traditional computers need months or years to solve.

On the downside, quantum computers could also enable hackers to quickly solve the complex mathematical algorithms that data encryption requires, thus placing all data and cybersecurity at risk.

Are Boards Kidding Themselves About Generative AI?

Perhaps the most perplexing finding of the survey relates to benefits already achieved from generative AI.

Article featured in Forbes

Generative AI is one of the most important new technologies organizations can adopt today, and many senior executives I speak with believe that it will transform key aspects of their businesses.

Some even believe that how they address generative AI could be a life-or-death decision for their companies. In order to make decisions about how to use the technology, it’s clearly necessary for business leaders to learn about generative AI and be knowledgeable about its likely impacts. Not only company executives but board members need to be up to speed.

But are they? The analytics and AI software vendor Alteryx recently surveyed 300 board members about generative AI. Some of the respondents’ answers were perfectly reasonable, but some strain credulity.

For example, when board members in companies using generative AI (228 out of 300 total survey respondents, or 76%) were asked about “the collective understanding and knowledge the board of directors in your organization has of generative AI,” they felt they are amazingly well-educated. 28% said the board members are collectively “experts.”

How organizations navigate AI ethics

While many organizations commit publicly to responsible AI principles, a gap often exists when they put those principles into practice.

Article featured in IMD

At this year’s CogX Festival in London in September, the British actor and broadcaster Stephen Fry warned against embracing artificial intelligence (AI) uncritically after discovering that his voice had been impersonated by machine learning. 

While Fry cited the (comparatively) benign case of copyright infringement – his voice was being used to voice a history documentary – the unprecedented pace of development and adoption of AI, ethical concerns like algorithmic biases, intellectual property rights, labor displacement, and privacy protection have become regular topics on the corporate agenda.  

Online retailer Amazon had to shut down its AI recruiting tool after discovering that the system had taught itself not to select female candidates, there were liability questions for Uber in 2020 after one of its self-driving cars hit and killed a pedestrian, and tech giants like IBM have stopped selling general-purpose facial recognition or analysis software because of fears of potential misuse.