Data visualization is a technique to represent data in a visually easy-to-understand format. If you’ve recently navigated anywhere using a map or attended a meeting where someone used a bar graph to explain a market trend, then you’ve encountered examples of data visualization. Humans find data represented in a pictorial form easy to understand. More importantly, humans are particularly good at seeing patterns when data is presented visually, which leads to deriving actionable intelligence. This process is known as data analysis and is particularly important now, as business decisions increasingly rely on interpreting vast amounts of data.
Data Visualization: A Short History
Modern data visualization can be traced to the early 1800s. A French engineer named Charles Minard first demonstrated the power of visualization effectively. His 1867 chart, once called “one of the finest statistical graphics ever drawn” correlated the failure of Napoleon's army during their Russian campaign with six separate impacting factors, allowing readers to draw powerful insights.
In the information technology age, concepts like Big Data analytics have taken correlative analysis to a new level with near-real-time data analysis and even predictive capabilities. These are powerful breakthroughs with implications for a host of fields, from healthcare to private equity. For a business leader, this business intelligence-driven decision making can create more predictable results in all aspects of the business, from generating better market insights to streamlining operations. No wonder then that business intelligence and data visualization are one of the fastest-growing digital transformation initiatives in companies today. This movement towards analytical decision making is set to grow in the future.
Data Visualization Trends
Smart Tech Integration Boom
As data capture becomes more comprehensive, complex systems can be analyzed and understood with mathematical techniques. However, in all “human in the loop” decision workflows, the data visualization needs to be as detailed and rich as the analysis itself. For example, medical diagnostic techniques like tomography and magnetic resonance would be of little use without the rich imaging they generated to give doctors powerful insights that aided their decision making. In the modern world, this is going even further: tiny sensors as part of IoT networks generate big data in real-time as well as sophisticated AI assistants to take the guesswork out of difficult decisions in healthcare, public policy, and businesses in Industry 4.0 setups.
The Ripple Effect of Virtual Reality
Another promising trend is the continuing rise of Virtual and Mixed Reality. This technology is considered the ultimate data visualization. Its promise in a host of fields - from engineering to gaming - has been appreciated for a long time. However, improvements in hand-held computing, data transmission technologies, and democratized content creation could finally signal mainstream applications in the next five years. VR and other visualization technologies like Augmented Reality (AR) and Mixed Reality (MR) are expected to impact a wide range of industries, such as security, industrial operations, and gaming.
Visualization for Marketing & Mass Consumption
In 2011, the scientist/artist duo of Martin Wattenberg and Fernanda Viegas stated that data visualization could become a mass medium, and would attempt to engage audiences who weren’t actively looking for information.
By 2020 this has become mainstream. Businesses are eager to engage consumers with visualizations, like infographics and motion graphics, that communicate mood and culture as well as factual information as part of their marketing campaigns. These new rich graphics, replete with color and flair create a different, more emotive value proposition than traditional informative graphics. As software tools add motion graphics and video infographics become easier and cheaper to use, rich content is here to stay.
Data Visualization News & Challenges
Businesses have an urgent need to use analytical methods to make business decisions, which is great news for data professionals. However, this democratization of visualized data also creates new challenges. For one, the variety of applications and sophistication of visualization techniques now requires specialized tools and trained experts, but the challenge is ensuring they have the business understanding to choose the correct parameters in creating the visualizations. This need has led to the emergence of specialist business analysts and other business intelligence experts, who are trained domain experts as well as visualization experts.
Another challenge is mastering the complicated data visualization software development itself. Fortunately, this need is increasingly met by off-the-shelf applications, so business leaders can focus on building their businesses rather than proprietary software. Most data visualization companies offer standardization and flexibility, but the better ones go one step further and offer automated business insights and predictive analytics to round out the full suite of capabilities.
This allows businesses to focus on building workflows that are customized for them via three important steps: data consolidation across functions to create holistic business insights, data management to deliver information based on logic and metrics that the business cares about, and data intelligence to understand the data and solve real challenges.
Are you ready to adopt business intelligence into your workflow? Get in touch with the team at InsightOut to learn how. InsightOut is built by data visualization and analytics experts to deliver next-generation analytics to business users for companies of all sizes and across industries at any stage in their data journey.