Harnessing the power of big data to gain a competitive edge

To compete effectively in today’s digital, highly-connected economy, it is clear that enterprises must have a thorough understanding of their customers, markets, solutions, regulations, competitors, third-party partners and staff. It is equally clear that this understanding can’t be reached without harnessing the power of big data.

Those that are doing this successfully are finding entirely new ways to compete and win in their markets. If well managed, big data can significantly improve decision making, enabling more intelligent, faster decisions, and ones that make a real difference.

So says Adeshni Rohit, Business Unit Manager for Cisco at Axiz, SA’s leading value-added ICT distributor, add-ing that this is no mean feat, as big data covers multiple types of data from a plethora of sources, including traditional and non-traditional sources.

“To date, data and analytics haven’t been used as widely or as effectively in businesses, as the tools have been complex to manage and understand. But this needs to change if they want to realise the benefits of their data, and achieve significant, measurable business value from it.”

With this in mind, Rohit says data scientists are always on the lookout for newer and better methodologies and techniques to unlock the value of big data and drill down into these results even further, to pinpoint any additional insights that could boost productivity and give the business a competitive edge.

“True value from data can also only be realised if businesses have information foundation in place that sup-ports the rapidly growing volume, type and speed of data,” she explains. “Two technologies they are turning to are artificial intelligence (AI) and machine learning (ML). These have seen incredible development in terms of introducing new frameworks and forms of compute to work on data to glean crucial insights.”

Rohit says according to Cisco, although data lakes have traditionally been data-intensive workloads, the advancements in technologies just mentioned, have led to a growing need for compute-intensive workloads to operate on the same data.

And although data scientists want to be able to use the latest and greatest advancements in AI/ML software and hardware technologies on their datasets, IT teams are also continually looking to enable data scientists to provide such a platform to a data lake, which has led to architecturally siloed implementations. This is because once data has been taken in, worked and processed in a data lake, it still needs to be further operated by AI/ML frameworks, which then leaves the platform and has to be on-boarded to another platform in order to be processed, she explains.

“This wouldn’t be an issue if this demand only applies to a small portion of workloads, but this isn’t the case. Look for example at data lakes in customer environments. They are experiencing a flood of data from a varie-ty of new use cases including IoT, autonomous driving, smart cities, financials and many more, all of which are generating an increased demand for AI/ML processing of this data.”

Because of this added complexity, IT needs better solutions to help data scientists to operate on a data lake as well as an AI/ML platform, without having to concern themselves with the underlying infrastructure. “At the same time, IT needs this to seamlessly expand to cloud scale, and at the same time, lower the total cost of ownership, without impacting on utilisation.”

She says Cisco recognised this demand and introduced the Cisco Data Intelligence Platform, a cloud-scale architecture which brings big data, AI/compute farm, and storage tiers together, to work in unison as a single entity, and at the same time, allows them to scale independently to address any IT issues the modern data centre may have.
“The Cisco Data Intelligence Platform provides an architecture that allows for extremely fast data ingest and engineering done at the data lake AI compute farm. It also allows for various AI frameworks and compute types, such as graphics processing unit (GPU), central processing unit (CPU) or field-programmable gate array (FPGA), to work on this data for additional analytics.”

In today’s data-driven world, the organisations who are able to truly harness the power of data, and turn it into real business insights to drive performance, lower risks, and chase new opportunities, will be the tomorrow’s success stories, she concludes.

“Luckily, Cisco is giving us the technology to thoroughly mine these enormous treasure troves of information, and extract the meaningful and insights that will allow us to make better, quicker decisions.”

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