Big data, big changes

Big data, big changes

Leaning on bundled solutions, reference architectures, and proven expertise to achieve big data success.

More sensors and devices. Faster and more economical processing, networking, and storage. And intelligent connections among them. All are converging to create a host of data-driven business opportunities.

“The industry has been talking about the unrealized value within data for more than a decade,” says David Yen, senior vice president and general manager of the Cisco Data Center Business Group. “We just haven’t seen a lot of activity or action until recently.”

More than visionary ideas and hype-inducing promises, big data has become a reality. But there is no distinct path for pursuing the needles of value within the haystacks of enterprise data. No silver bullet for success.

“Big data is here to stay because there is real value in it,” says Yen. “But we are still in the early stages. We must all adapt to these new opportunities and paradigms. Where to invest and how to reap value will be different for every organization.”

In many ways, big data means big changes for those seeking to capitalize. It requires:

  • New platforms
  • New processes
  • New skill sets
  • New software capabilities

While they have similar components and attributes, Yen says big data environments are fundamentally different than standard data center systems.

“You can’t shove a large volume of unstructured data into traditional systems and expect good results,” he explains. “And you can’t piece together a bunch of off-the-shelf servers for big data analytics without running into administration and networking problems.”

Navigating change
According to Yen, Cisco and Intel® are well positioned to help organizations step into the big data waters, minimizing startup challenges and expediting ROI.

  • The the Intel® Xeon® processor-based Cisco Unified Computing System™ (Cisco UCS®) can form the foundation for big data success. Cisco UCS® brings together compute, storage, networking, and management resources, and can be fine-tuned for big data workloads.
  • The Intel Distribution for Apache Hadoop software is the only distribution built from silicon up to enable the widest range of data analyses on Apache Hadoop.

“We don’t want to duplicate or replace existing environments and solutions, we want to complement them,” says Yen. “[Cisco] UCS bridges the gaps between traditional systems, enterprise networks, and big data processing—with one management interface.”

Cisco and Intel also work closely with independent software vendors to make sure their software works seamlessly on Cisco and Intel platforms:

  • Cloudera
  • SAP
  • Splunk
  • MapR
  • Hortonworks
  • IBM
  • SAS

“There are different approaches for big data depending on the use case, the type of data and analytics involved, and how they are consumed,” Yen explains. “We have reference architectures, roadmaps, and partners for all of them.”

Organizations seeking to mine value from big data have two options:

  • They can piece together their own systems and navigate uncharted waters on their own.
  • Or they can lean on bundled infrastructure and management solutions that are tightly integrated with analytics software from industry leaders that have a wealth of big data expertise.

“We have the right experience, the right platforms, and the right partners,” says Yen. “We can help our customers get the most out of their big data investments.”

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