Data scientists and analytics experts aren’t the only ones who can use big data to gain valuable insights. By limiting to an elite group of specialists, businesses also limit their ability to realize the full potential of their data.
A recent Forbes*article describes the next big challenge for business as making the valuable information hidden within massive volumes of data available to any business user. Armed with more data and better analytics, business users can contribute to greater productivity and improved decision making—and ultimately the bottom line.
Visualizing the bottom line
How can business push analytics down into the organization and help drive dollars back to the bottom line? Visualization is one powerful tool to help businesses see their data in ways that identify trends, patterns, successes, and problems. These results are derived from advanced analytics, algorithms that enable the business to look at the data from different perspectives and experiment with various scenarios to find hidden insights. Typically though, advanced analytics and visualization are the purview of specialists rather than business users.
Organizations with a strong business intelligence (BI) strategy already have many of the pieces in place to provide business users with access to important data. Expanding access to advanced analytics is the next step in the evolution of data usage in the organization. Yet most business users do not have the knowledge and skills they need to apply analytics to big data. They will need training on how to frame their business problems as data mining problems and how to work more effectively with data scientists. Ideally, some may be interested enough to become capable of performing intermediate data mining projects themselves.
Intel IT is rolling out advanced analytics to the enterprise
As part of an overall strategy to use big data for competitive advantage, Intel IT is laying the groundwork for broader access to advanced analytics in the enterprise. Business teams are beginning to receive data mining and advanced analytics training. With a wider segment of employees who are fluent in analytics, those teams are becoming able to solve some of their own problems and work more easily with data analytics specialists. Some employees have pursued higher levels of training that enable them to create and validate their own analytics models.
The full Intel IT model includes training classes, mentoring, building a community of practice, and identifying instructor candidates and will be fully rolled out by the end of 2014. Early success stories suggest that this approach has the potential to make all 100,000 Intel employees more analytics savvy, more data driven, and better able to contribute to their teams.
Intel’s exciting training and support efforts have the potential for significant payoff over time. Does your organization have a plan for pushing analytics down into the organization? I invite you to comment.