More Analytic Value with Big Data Visualization

Simply put, big data analytics can lead to more data exploration for more users. In addition, big data can enable you communicate and visualize business insights in more compelling presentations and graphics to support faster strategic and operational improvements.

Big data technology is becoming available on lower-cost platforms, and there is a large flow of information being circulated on its adoption and deployment. Business areas such as marketing, customer service, and ecommerce can derive value from big data analytics in the areas of predicting sales, clarifying customer behavior, and optimizing product placement, as well as many other high-value activities.

Big data analytics—the collection and analysis of large sets of data to discover patterns, tackle difficult concepts, and obtain more detail—is key to improving operations and decision-making. Better usability and possibilities for self-service to end-users can be realized with the addition of visualization techniques. An approach to visualization that facilitates presentation of analytics data in a pictorial or graphical format is key to success. Concentrating on broadening accessibility to larger data sets obtained from a wider variety of data sources is a good way to quickly garner business value from big data analytics and visualization techniques. This quick-win approach can easily be made part of a wider strategy.

Larger Variety of Data Sources

Dealing with new types of data will enrich data analytics and involve new users, especially when combined with compelling data visualization. Start with the data you know users want—for example, online public databases and tweets that you have not had the resources and tools to tackle. Also concentrate on finding ways to communicate analytical insights for people who do not have extensive data-interpretation experience. Value can be derived from multivariate relationships that enable a wider view of key data and attract new users and sponsors for the next big data phases.

Broader User Base

Sales associates, insurance brokers, executives, and middle managers should have access to usable analytics data, and ultimately a self-serve analytics capability should be broadly deployed. The value to the organization this will provide is immense when insights and actionable information are available and are broadly distributed.

Caveats

The necessity of planning for pilots and phased project launches cannot be overestimated. People have lived with procedures and data management tools for a long time and don’t see themselves as data scientists. The vision and business value of accessible and highly relatable big data analytics must be communicated and reinforced often.

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