Big Community: Do you feel data visualisation is a necessary element of Big Data Analysis?
Andy Zook: Never has so much data been generated in human history than in the past two years. This shift is forcing businesses who want data-driven insights to analyze enormous volumes of data with thousands or even millions of variables.
They then have to quickly review the data, identify areas that need attention or improvement, ascertain the factors that influence customer behavior, pinpoint emerging trends, recognize relationships and patterns and more in a short amount of time.
Data visualization, when correctly aligned, provides a shorter route in the decision-making process and becomes an essential tool in conveying information critical to any form of data analysis. Data visualizations also need to contain the right amount of interactivity, be well designed, easy to use, understandable, meaningful and approachable to be a truly effective.
Through visualization, companies can benefit from being able to easily determine when, how and through what means to engage their customers, how to increase their sales figures or even improve operational efficiency, among others.
Big Community: How does data visualization enhance insight and decision making?
Andy Zook: Every business has data and those who make good use of them thrive. Data visualization enable business users to discover and analyze data on their own and quickly share their findings with others, thus strengthening and accelerating the decision-making process.
This is an especially critical feature for those in the financial sector where fraud is commonplace and transactions need to be monitored regularly and unusual patterns detected promptly. One SAS banking customer, Hungary’s OTP Bank, uses data visualization to explore the data from multiple angles very quickly and report on them in real-time for appropriate follow-up actions to be taken.
SAS Visual Analytics – visualizing data from different sources to find links and correlation
Apart from increasing the speed at which decisions can be made, visualizations help businesses get more information, faster. It provides the insights that can help improve the functionality of teams, provide clarity on the linkages between data points that seemingly did not have any links at all and enables users to locate good and bad data which helps them to maximize their productivity as well as the value of the information they had collected.
Example of location capabilities in data visualization, from SAS Visual Analytics
We have clients who have used the location-specific capabilities of data visualization to tackle human trafficking by drawing relationships between source and destination countries. Marketers can also capitalize on this feature to identify low penetration areas of their products from sales data, helping them determine the right locations for their campaigns.
Big Community: What key functions should people consider when selecting a visualization tool?
Andy Zook: A good practice for selecting a visualization tool is to determine what data your business is going to analyze and how. The tool needs to enable the types of analysis a business will need and use. It must enable multiple visualizations including tabular reports, pie, bar and radar chart types to appear on a single screen either independently or interconnected with others.
Ease of use, intuitiveness and self-service capabilities are important factors in selecting a visualization tool. You want your business users to be able to get the insights they need when they need them, with easy to use options and analytical tools designed for even non-technical users to quickly create and change queries to suit their needs.
The ability to derive insight from text – from analysis to visualization – is critical. With social media and free-form text documents becoming a part of every organization’s data ecosystem, it is imperative the tool provides much needed assistance in the discovery of text-based data points such as topic and sentiment; providing a view of how consumers are reacting to the business.
Big Community: Are different charts and visuals more appropriate for different lines of business?
Andy Zook: The real question is whether the data used provides the insights a business is trying to glean. Charts and visuals make it easier to understand the data and better decisions, but the value of the insight is dependent on the quality and type of data being meshed together to derive the results before even beginning the analysis.
When creating data visualizations, users need to keep the parameters small to derive accurate insights. A wireframe that answers strategic questions about the business including KPIs, concerns, and challenges needs to be developed. Visualizations must be designed for maximum impact – and that means dashboards must be kept simple.
Most organizations will present their data in comparison, composition, distribution or relationship formats. Bar charts are good for comparisons while line charts are better for trend analysis. Having too many graphs or different formats, or simply too much information in one graph can be distracting and make it harder to see the main points.
That’s why it is necessary to determine which chart best suits an organization’s needs, it must ascertain the number of variables, data points and period of analysis.
Big Community: Is there anything unique you would like to tell us about your data visualization offering?
Andy Zook: SAS Visual Analytics is designed to be easy to use and aid data discovery by end users. It comes with powerful capabilities like data prep and predictive analytics built-in, without relying on third-party applications and unlike anything else in the market. We also ensure that using SAS Visual Analytics is seamless: it supports a wide variety of sources and formats, and can be integrated into existing systems and governance processes. The platform is built to be used on SAS Viya, our next-generation high-performance and visualization architecture which is open, cloud-enabled and with scalable advanced analytics.
These capabilities have made SAS Visual Analytics popular with data scientists and IT departments, and useful for different industries throughout the world. For example, CrescentCare in the US uses visual reports on multiple data sources to ensure continuity of care to their patients, and DirectPay in the Netherlands uses location maps of high-incidence areas to better deploy resources for credit management.
Increasingly, we see business analyst and citizen data scientist using the platform themselves to get data-driven insights to inform business decisions; a testament to its ease-of-use.
For more information please download DSA Spotlight on SAS Viya
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