Today’s enterprises collect and analyze enormous amounts of data that would take years for the human eye to observe and read, let alone understand. The amount of data created by small and larger corporations is growing exponentially every year, thus posing a challenge for organizations to quickly grasp their current business situation and use the right data at the right time. Thanks to innovations such as the Internet of Things and Artificial intelligence, the growth of data generated daily shows no sign of diminishing while at the same time complex numbers and figures remain uncovered by analysts for further data exploration.
What is data visualization?
The point of data visualization is to represent data of almost any type and especially complex amounts of it in a pictorial or graphical format, thus making it easier for users to understand and comprehend it at a glance. Data visualization tactics go from pie, bar charts, and histograms to more interactive and graphical illustrations including personalization and animation to display figures and establish key relationships among pieces of information.
Studies in neuroscience and human learning show that the human brain processes information in the form of graphs and images 60,000 times faster than texts or numbers, while 90% of information transmitted to the brain every day is visual. Given the facts, this means that when managed and displayed in the form of images and interactive visualizations, raw data gives powerful insights and leads to much easier data processing and therefore enhanced decision-making.
Visualization is central to operating with raw data within an enterprise. It goes far beyond graphs and charts used in Microsoft Excel spreadsheets. It displays complex data sets in a more sophisticated manner giving users the freedom of choice to visually sort and shape them.
People vary in the manner in which they absorb, process, and recall perceived information. Statistics show that 65% of the world’s population is visual learners. 30% of them learn better by hearing and 5% are experiential learners – they learn by doing and touching.
Figure 1: World’s population techniques of learning
Why big data visualization matters?
1. Visualization communicates the whole story to users
The core power of data visualization lies in its ability to be an effective communicator of insights to employees and end-users in need of data knowledge. Graphical transformation of data conveys meaning very quickly by extracting all the necessary information from the database. It gives users and developers huge competitive advantage because subsidiary data is not overlooked. Instead, a clear and precise representation is given of all aspects of the analyzed information. Data storytelling is a powerful mechanism for sharing facts and algorithms in a way that is memorable and engaging.
2. Visualization pinpoints true challenges that influence performance
With powerful graphics and interactive charts users can identify areas in the analyzed data flow that need attention or improvement. This helps eliminate minor or significant problem areas before they prevail or affect business processes. Data visualization could be used to show analysis of low employee performance and its indicators or to display another bad aspect of a given set of findings. The visualizations represent the key data in a manner that points to sound courses of action and helps business units develop a plan for improvement in a well-defined direction.
3. Visualization reveals the real value of data
Collecting great masses of data and finding trends within the data allows businesses to be more agile and to run processes quicker than before. Comprehensive analysis of information makes it easier for companies to generate valuable answers and increase enterprise productivity through detecting correlations and unexpected relationships at a glance. According to a Nucleus Research on analyzing ROI from analytics, a business intelligence solution with data visualization capabilities will offer a ROI of $13.01 back on every dollar spent.
Big data visualization with QlikView and Qlik Sense
QlikView and Qlik Sense provide enhanced user experience through beautiful and comprehensive data representations and visualizations. The two applications have the same technical core: this is the Qlik associative engine.
QlikView is a tool for situations where users want to prepare business applications or applications created by developers who put a lot of thought into the data model, the layout, the charts, and the formulas; and deliver the applications to end-users who consume the applications. This is called Guided Analytics. The end-user has total freedom to explore data, select, drill-down and navigate the information, and can this way discover both questions and answers in the data. Qlik is a great tool for every data analytics project.
Figure 2: QlikView representation of monthly sales performance
Qlik Sense is a tool that allows the end-user to create a layout of their own and in it, new visualizations and charts that the developer couldn’t imagine the user would like to see. It is very intuitive and has a simple drag and drop interface. With it, you can create flexible and interactive data visualizations which makes it better for custom development.
Figure 3: Qlik Sense representation of monthly sales performance
To discover the visualization tool that best suits your needs, you must make difficult decisions. There isn’t a single data visualization technique that works best for every user or circumstance.
Flexibile or Easy to Use
Flexible visualization tools include rich feature sets that offer total configuration control, fine-grained design tweaks, and more sophisticated analytical capabilities.
Best for: Skilled developers and analysts
A focus on usability makes it simple for non-technical people to get going. The ability to customize, manage, and functionality might be compromised. The very finest tools have sensible default settings.
Best suited for: Business users and non-technical users
Visual Analytics or Data Storytelling
Tools for visual analytics increase the efficiency and power of data analysis. So that the analyst can seek out further and deeper insights into the data, the visualizations highlight trends.
Best for: Data scientists and analysts who work with a variety of data types.
Data communication between people is the main emphasis of data storytelling tools. To a certain audience, the user want to communicate a message or some observations. To fully tell the story, the data can be coupled with data and graphics.
Business users, consultants, and subject-matter experts are the best candidates.
Benefits of data visualization
Data visualization improves insights
By converting enormous volumes of data into understandable graphics that are more valuable to decision makers than lines of text and figures, data visualization streamlines the data analytics process. Data correlation in a visualization tool can reveal hidden information and knowledge to support decision-making. The hidden links, patterns, and trends in large data sets can be vividly illustrated by a single graph, which can also be used to spot abnormalities and outliers.
Decision-making is expedited by data visualization
The analytics process is accelerated by data visualization. Businesses want speed because quicker decisions produce quicker outcomes. Businesses with a data analytics advantage can outperform their rivals. You can take action on your data more quickly if you can make sense of it more quickly.
Data visualization creates a narrative out of the data.
The human mind is not very good at handling vast volumes of data, but computers are. An image is processed by the brain more quickly than lines of identical, colorless data. Because they provide meaning, colors and patterns are beautiful.
Stories are simple to comprehend and to retain, and visuals tell stories. Your audience, whether it be the C-suite or potential customers, will absorb the data more quickly and be more likely to remember it if you deliver it as a narrative.