Move Over Unicorn, It’s the Rock Star’s Time

As the world of data analytics continues to evolve and reshape after a tumultuous 2020, the need for agility is rapidly driving a new era in data culture in which it is imperative to handle data immediately and at scale. While emphasis on self-service data and analytics has been top-of-mind for some time now, the shift to self-sufficiency is held back by culture, not technology. With the new year pushing more robotics process automation at all levels of the business—and for all data users—organizations are becoming more acutely aware that true enablement isn’t just about tools and tech. It’s about people.

Achieving enterprise value from all data requires a new animal, and we’re not talking about the elusive unicorn—the data scientist. While the blend of business, big data, and math that the data scientist brings to the table will always have a home in data-driven organizations, the most impactful animal going forward will be the data professional—a business-oriented user who can confidently, efficiently, and actionably work with data.

Similar to musical rock stars, “data rock stars” crave independence, freedom of movement, and the opportunity to show off their skills. They are collaborative, inspirational, and driven to push the limits of their ability. Going forward, true data enablement in an organization will be organic and viral—and what’s more rock ’n’ roll than that?

Pick an Instrument

Contrary to popular opinion, becoming a data rock star isn’t only about mastering a specific skill. Rather, it begins with having a vision (or, a melody) you want to manifest, then picking the right instrument—in this case, an area of expertise, be it in data visualization, architecture, integration, or so on—and learning to make music, whether as a solo musician, band member, or part of a larger data symphony.

The ability to pick your instrument—your skill of choice—is a liberating one that propels the data rock star from jam sessions in the garage to touring in their venue of choice. Becoming an empowered data user means going beyond learning how to use data and analytics in any particular role and attaining transferrable job skills that supersede job function.

Learn to Play

If music theory is the study of the practices and possibilities of music, then data theory is the foundation that data users need to develop the skills and competencies to become true data rock stars. Just as music theory is a practical discipline that encompasses the methods and concepts musicians use in creating music, so, too, is data education of paramount import for the data rock star.

An uneducated data user is a dangerous data user. Before one can learn to play their instrument, budding data rock stars need to understand the principles, best practices, and limitations of working with data and analytics. Here, not only is attaining data literacy critical, but, as with many things, practice—or, more aptly, iteration—is key. Once the basics have been established, data rock stars will be equipped with the knowledge and theories needed to learn to play in harmony with the rest of the organization.

Be a Conductor

Enabling business users to become data rock stars requires culture change, and when we talk about culture, there are myriad strategies to achieve pervasiveness across dozens, hundreds, even thousands, of people within the organization. Many call it “stages of maturity,” but what it truly distills to is this: How can you empower an individual and make them a luminary so others will want to emulate and follow in their footsteps—or, how do you transform data users into data rock stars?

Leaders should focus on enabling their people to become data rock stars, both for the organization and for their employees’ personal career development. Create positive paths with engaging education and certifications, and facilitate engaging communities while removing negative obstacles of intimidation, embarrassment, and risk-taking that come while learning. Think low-barrier, high-reward.

Ultimately, as organizations continue to look for ways to achieve data at scale, it’s not a matter of using tools and technologies to their full potential—it’s about helping people reach their full potential. After all, even skill areas are tools. It’s people who make the music.


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