The Dead End of BI Dashboards in New Data Addiction Age

Despite big data being a “quiet star” at C.E.S., wrestling with a huge variety of data from a plethora of new devices and sensors is a big challenge ahead for an Internet of Things’ future.

Watching the unveiling of all kinds of new connected devices at the annual Consumer Electronics Show, the Internet of Things is on the brink of exploding with new offerings coming onto the market during 2015 – including wearable devices, self-driving cars, home security and Wi-Fi enabled everything.

As Information Week’s Jeff Bertolucci wrote, big data was the annual gadget fest’s “quiet star” this year. Consumer Electronics Association’s chief economist Shawn Dubravac outlined how “falling costs of key technologies, including a mix of low-cost sensors, digital cameras, 3D printers, drones, and wireless network protocols, are coming together to enable information-sharing on an epic scale, something not feasible a few years ago.”

J.P. Gownder, a Forrester Research analyst, referred to this year’s C.E.S. as “a coming-out party” for the Internet of Things. During Dubravac’s curtain-raiser presentation, he called it, is the “third stage of the Internet” where 50 billion connected devices come online. In comparison, there are about 2 billion Internet-connected smartphones today, he said.

The exuberance over our brave new Internet of Things’ future is contagious, and there are huge opportunities to put this accelerating proliferation of data to work for organizations of all kinds. There’s no doubt all the new data generated will need to be harnessed faster, and the appetite for more insights into usage consumer behavior and trends will scale.

Yet, there are major obstacles to overcome. The biggest challenge is putting an ever-exploding “data variety” – most of it unstructured or semi-structured – into context and “harmonizing” it into a blended view to provide real-time insights that let business leaders instantly visualize and immediately collaborate on-the-fly to make better decisions faster.

Business leaders already struggle with a broadening variety of data sources. Based on a poll of 500+ business leaders last October: data variety, not volume, is the biggest bottleneck holding up data-driven business decisions. Data quality was one of the top challenges, but even that is now diminishing as the top concern, at least where analysis is concerned. Based on a different InformationWeek survey, only 51 percent of organizations put data quality on their “top barriers” list versus 59 percent in 2014.

Based on the poll, organizations increasingly struggle with the complexity brought about from a growing number of data sources and formats that need to be blended together and harmonized faster than ever for a holistic, business-ready view that’s easily consumable.

The vast majority of those polled need to blend four or more data sources, and nearly half (49 percent) report they need to blend eight to 15+ data sources. The formats are a mix of semi-structured, unstructured, flat files and legacy sources. There’s little homogeneity across the various sources business users need to make critical decisions.

Another key finding from the survey is that old-school tools and methods – like Excel and other BI tools, dashboards, or relying on IT or data experts – are hindering insights and effective decision-making for businesses. More than half report they use email (69 percent), dashboards (59 percent), and Excel (54 percent) to share, discuss, or collaborate on insights.

Like consumers who are rapidly becoming addicted to data and information (e.g. personal fitness tracking, social channels, news feeds), business users will become pleasantly addicted to big data in the very near future. They’ll be able to intuitively work with new data solutions that are fast, interactive and easy to use. And, this new functionality will let them question more, uncover more, collaborate on insights in real-time, and reach better decisions faster.

A recent survey of 500+ business leaders exposes what’s been holding data to decisions back:

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