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Data Visualization

  • Four steps to make a data visualization project succeed

    Feature -Data scientist Jennifer Shin offers advice on how to manage a data visualization project and create effective visuals that meet the information needs of business decision makers.

  • Data visualization techniques, tools at core of advanced analytics

    Feature -Data visualization's central role in advanced analytics applications includes uses in planning and developing predictive models as well as reporting on the analytical results they produce.

  • Effective data visualization crystallizes a company's crystal ball

    E-Zine -What's in your toolbox? October's issue of Business Information turns the tables and puts that burning question to Capital One and several other business intelligence and data analytics software users. As the burgeoning worlds of structured and unstructured data collide, companies see urgency in predicting consumer behavior, technology trends and marketplace hiccups. Predictive analytics can foretell the future, but peering into a crystal ball chock full of statistics is tantamount to walking through a strange town with no street signs. Effective data visualization tools are the street signs in the form of easy-to-understand charts, graphs, illustrations and more. Visualized data helps business executives make sense of the analytics and arms them with the ammunition they need to see the big picture and formulate intelligent corporate, marketing and sales decisions. In a TechTarget survey on planned software investments, predictive analytics and data visualization tools top the list of BI and analytics technologies. But visualized data goes far beyond presentations for business executives.

    In our cover story, reporter Ed Burns reveals that data scientists and analytics managers at companies like Capital One,, BuildingIQ, ArcBest and Omega Point Research rely heavily on effective data visualization throughout the analytics process, from initial exploration to predictive modeling to reporting results. "Visualization is the bread and butter," says Boris Savkovic, lead data scientist at BuildingIQ. "It helps expose patterns over time as well as patterns between different variables."

    The surge in predictive analytics and visualization tools can be largely attributed to the rise of big data. For IT teams charged with assembling big data architectures, editor Craig Stedman, in another feature, examines the abundance of technologies available and, paradoxically, the complications that creates. And therein lies the rub. "To pull it all together, I can say that 10 people didn't sleep for a year," relates Vinoth Chandar, Uber senior software engineer.

    Also in this issue, learn how a security expert and cryptographer is using big data analytics and the cloud to make open source code safe for app developers and off-limits to hackers.

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