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GCN : February 2014
While redefining organizational landscapes and spurring innovation, strategy and technology solutions are critical for success. > CDWG.com | 800.808.4239 wade through. Consulting firm Gartner Inc. reports that enterprise data growth rates now average 40 percent to 60 percent annually. For another, data increasingly resides in systems and pools that are difficult to access and put to use. e task isn't getting any easier. In many cases, organizations are attempting to tap into transactional data extending back decades. In addition, they're coping with mountains of unstructured data --- including geolocation information, audio and video, photos, websites, voicemails, messaging streams, data from machine sensors and more --- generated from a growing array of digital devices, including mobile phones and social media. "Combining everything and making sense of everything is the challenge of the digital age," says Gary Curtis, chief technology strategist and managing director at consulting firm Accenture. Ultimately, how can organizations tap into Big Data to gain valuable insights? What type of approach is necessary to produce real-world results? " e biggest challenge is finding a way to cut through the sheer volume of data and the inherent complexity of different databases and unstructured systems," states Scott Schlesinger, vice president and head of North America Business Information Management at consulting firm CapGemini. "A well- conceived strategy and the appropriate tools for conducting advanced analytics and modeling are critical." A New Era of Analytics Emerges Big Data is more than hype. e flow of digital data through the global economy has grown from a trickle to a torrent over the last decade. Consulting firm McKinsey & Company estimates that the typical large organization now holds somewhere in the neighborhood of 200 terabytes of stored data. Today, organizations capture trillions of bytes of transactional data about citizens, constituents, students, suppliers and operations. is is done via vast networks of computers, mobile phones, sensors embedded in machines and an array of other sources. Although there's no exact definition for Big Data, McKinsey and other consultancies generally apply the tag to datasets that extend beyond the range and scope of a single database or application. Typically, an organization will require an overarching strategy as well as tools and technologies to put the various databases, repositories and data sources to work in a deeper way. e ultimate goal is to create greater transparency across systems and provide insights that wouldn't be possible using conventional approaches. Typically, Big Data combines structured and unstructured data --- and incorporates the use of metadata to make information actionable. In some cases, Big Data uses artificial intelligence and specialized algorithms to analyze overall data patterns --- and the relationship with data points against other data points. What makes today's data environment so challenging is that it's impossible to build a database big enough to accommodate all the data sets that can potentially fuel innovation or a competitive advantage. What's more, it's nearly impossible to identify the specific data to tap into at any given moment and know how to apply the data to real-world problems. Much of the power of Big Data is applying combinations of data sets in new and unusual ways. ver the last few decades, organizations have turned to a dizzying array of IT systems to capture and store data. In sectors as diverse as government, education, healthcare, retail, manufacturing and financial services, the desire to gain insights into a vast array of activities and events is increasingly at the center of success. Yet, as organizations amass repositories tipping into the terabytes and attempt to pull data elements from a dizzying array of sources, achieving bottom-line results has never been tougher. Enter Big Data -- today's big IT buzzword. Amazon Web Services refers to Big Data as any amount of data that's too big to be handled by one computer. While Wikipedia defines Big Data as data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage and process the data within a tolerable elapsed time. Regardless of the definition, Big Data represents a resource from which to extract meaning and drive better decision-making --- all from the proliferation of digital bits and bytes that fill servers, hard drives, mobile devices and websites. Yet, as organizations turn to Big Data to spur innovation and gain a competitive edge, many are finding that they face big challenges. Enormous Volume For one thing, there's the sheer volume of data organizations must O