This is a guest blog by Tejas Vashi, Senior Director, Product Strategy & Marketing, Cisco Services
Data rules the IT world right now – there is just so much of it. Yet, there are often many missed opportunities when it comes to utilizing this data to extract insights and leveraging them to drive business outcomes
Organizations aren’t executing as well as they can, but the problem may not be what you might think.
In the whitepaper, “Big Data Doesn’t Make Decisions, Leaders Do,” Florian Zettelmeyer and Matthias Bolling propose the theory that Big Data is not so much a data science problem per se. Rather, it’s more of a leadership problem.
Organizations today want to extract insights to obtain value, but the thing is – as McKinsey & Company point out – most of the available IoT data currently isn’t used. Not only is there too much data coming from structured and unstructured sources, but also leveraging the data where it resides and preparing it for analytics is a huge challenge.
For example, on an oil rig that has 30,000 sensors, only one percent of the data points are typically examined. That’s because data is used today mostly to detect and control anomalies. However, analyzing data — and using it to optimize operations and predicting issues before they happen — can provide great value and drive utilization, productivity, profitability and reliability outcomes.
Businesses must find ways to extract insights from all their data in order to succeed and drive better outcomes. One way to approach this change is to match organizational change with technology adoption.
It’s not enough to just capture and integrate this data though. Organizations must also get the data to the right place at the right time (and to the right people) so it can be analyzed. Accomplishing this includes automatic and consistent access to the data and a determination as to when it can best be utilized – whether it needs to be moved to the “center” (a data center or cloud) or analyzed where it is – at the “edge” of the network. Maximum value comes from employing a combination of this edge and the center – not one or the other.
So what does this mean for IT professionals?
Therein lies the rub. The data market is growing, but businesses are struggling to find people with the skills to design, install, operate and manage these intelligent networks as well as expertise to understand how to analyze and use the huge amounts of data being captured across the network. In fact, in a survey conducted by IDC and Computerworld, respondents said that their top business challenge was a lack of enough staff with appropriate analytics skills. And a recent Knowledgent survey revealed that the top business challenge regarding infrastructure is getting the appropriate hardware and software installed and operational, largely due to a lack of skills.
We now see the issues of organization and technology coming to the forefront. From an organizational point of view, businesses need to take steps to identify, address and resolve the issues pointed out by Zettelmeyer and Bolling, including:
- Analytics should start with business problems.
- Analytics needs translators.
- Analytics requires data scientists of different flavors.
- The analytics team should help get the job done.
- All leaders need a working knowledge of data science.
IT pros who gain the skills needed to work with data will have a huge leg up as they look to get ahead. Fortunately, there are certifications and training available to help you prepare. At Cisco, we have created the following:
- Integrated Infrastructure for Big Data: Providing beginning and advanced training for designing, installing and trouble-shooting data solutions using Cisco UCS Big Data infrastructure products.
- Data Virtualization CIS: Basic and advanced training addresses solution architects, solution Integrators and administrators who are familiar with data warehouse, ETL and data management solutions and want to learn how to design, deploy and operate a virtual data warehouse.
I can’t emphasize it enough – when it comes to digital transformation, data is the true competitive advantage. For an organization to stay competitive analytics must be a front-and-center focus – and you must empower your staff with the skills and technology needed to implement and maintain the needed data infrastructure, as well as understand how this data can be best leveraged.