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Enterprise Digital Transformation

Big Data is likely to be a key element in the digital transformation taking hold in the enterprise, but there are still questions as to how it will influence future business processes and what steps to take now to ensure it provides optimal support in a fast-changing economy. Legacy IT is largely unprepared to meet the requirements of the new digital business: application cycle times measured in months, if not years; siloed infrastructure that prohibits organizations from viewing their data holistically; performance bottlenecks that impact end-user experience in a world that demands constant availability and response times; rigid architectures that force organizations to make forklift upgrades as requirements change; and traditional provisioning processes in which IT is often seen as a barrier rather than an enabler for the business. 

“Organizations must resolve this conflict between Digital Transformation goals and today’s IT reality if the business is to meet its ultimate objectives.”

According to a recent report by the Harvard Business Review, most organizations are looking forward to dramatic improvements in services and business models through Big Data, but few are implementing technology and infrastructure as part of a strategic approach to transformation. The study found that 52 percent expect Big Data to lead to new services for the Internet of Things (IoT), while 44 percent say it will transform their business models.

However, upwards of 78 percent are currently leveraging only limited amounts of IoT data or none at all, while an equal percentage say they need new networking technologies to fully implement Big Data operations. In fact, most Big Data initiatives today are being carried out on an ad hoc basis, not as part of a strategic imperative.

With the amount of data in play, it is easy to see why most enterprises are overwhelmed at this point but data volumes are only one aspect of the challenge. The other is managing the sheer number of streams coming in from countless sensors and devices, all of which has to be gathered, sorted, secured and pre-analyzed before it gets to the main analytics engines that are supposed to isolate the valuable information from the junk. This will require a new approach to enterprise infrastructure incorporating high-speed compute, storage and networking, as well as cloud-scale resources, cognitive computing, and a host of other advances.

Digital Transformation Trends

One of the key habits of the past that no longer applies to the world of Big Data is the idea that more necessarily equals better. In traditional settings, increased data loads were met with more servers, more storage and more network pathways, but in the emerging world organizations will have to look into the underlying relationships between these elements in order to drive greater efficiency in the data handling process.  And to really kick things into high gear, the enterprise should start thinking about a unified storage architecture, preferably with support for containerized workloads.

There is always a lag between what the leading vendors say is happening in the technology market and Big Data vs. what is actually happening.

The fact is that few organizations are leveraging Big Data and the IoT in significant ways because the technologies supporting them have only just started to trickle into the channel. And in this case, the transition will be doubly difficult because we’re not talking about new hardware and software alone but a reimagining of the entire business structure.

But that doesn’t mean the enterprise has time to wait. New businesses are sprouting up every day providing a wealth of services on brand new scale-out, analytics-optimized infrastructure, with none of the technological or cultural baggage that weighs down the traditional enterprise.

To compete, today’s business needs not only new tools at its disposal, but a new way of carrying out its core functions. Contact us today to learn more about how to prepare your digital transformation strategy.

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Re-engineering decision-making environments to mobilize business intelligence and immerse employees in knowledge, producing peak performance and ongoing success.