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Just a few years ago, digital transformation was a vague concept—it had no clear definition, nor was there an established path to follow to achieve it. Today, although there’s still no precise definition, we have a greater understanding of what it means to be a “digital” company.

One of the key elements of digital transformation is the ability to use technology to innovate and identify new business opportunities. Technology’s democratization of data is creating abundant opportunities for organizations. Applications like Microsoft Dynamics and Power BI, Tableau, Salesforce, VBA, and SharePoint Designer provide access to unprecedented amounts of data.

To put the data to good use—to extract actionable intelligence, to enable real-time decision-making, to facilitate personalization, and to empower all business users to tell stories with data—organizations must provide employees with the right tools and support.

Considering the shortage of data scientists, as well as the time and costs required to hire staff that can handle complex development work, the reality is that many companies just don’t have the resources to fully benefit from the data available to them.

Even organizations that have employees who are data literate face roadblocks. Data literacy, which is the ability to derive meaningful information from data, is not data expertise. Before employees can interpret data and apply insight, data scientists must create systems they can use. And, according to Gartner Research, most organizations don’t have enough data scientists “consistently available throughout the business,” but they do have skilled workers who could become “citizen data scientists.”

The reality is that many companies just don’t have the resources to fully benefit from the data available to them

With the right support and assistance, companies can mold their skilled employees into citizen data scientists. It’s a simpler, quicker path toward advanced analytics.

To close the gap between the ability of the citizen data scientist and the expertise of the data scientist, organizations can enlist partners for help with advanced products like dashboards—which are intuitive enough that their use doesn’t require a degree in data science—and for dedicated, scalable support and training for those resources.

It’s an optimal solution for many reasons:

  • It means organizations do not need to hire and train experts
  • It’s scalable—organizations have access to as many or as little experts at a moment’s notice
  • It’s comprehensive—companies can provide employees with immediate project assistance and support for a range of business intelligence applications, not just one
  • It prepares organizations for the near future—Gartner predicts that through 2020, the number of citizen data scientists will increase five times faster than the number of data scientists

Perhaps above all, providing outside help for advanced products is a move that encourages organizations to shift to a modern mindset. It enables companies to achieve progress instead of striving for the time-consuming, nearly unattainable goal of perfection. If innovation is one of the larger goals of digital transformation, disruption and timing are what propel organizations toward it.

In a recent CIO.com article about BI strategy, writer Mary K. Pratt highlights a number of ways organizations can work toward success. Pratt writes, companies should prioritize upskilling their “citizen data scientists”—employees who have analytical skills, who know how to interpret the data are comfortable using the technology—and take steps to empower “staff to tell stories with data.”

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