Post: The Key to Analytics Success is in the Next Cubicle

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The Key to Analytics Success is in the Next Cubicle

Citizen Data Scientists Are the Critical Staff You’ve Already Hired

For the past two decades, web development has been a bottomless reservoir of employment for developers, especially those with skills like Javascript. But the next decade belongs to data science. Case in point: a recent study found that the popular programming language Python is now used more widely for data science than for web development.

The pivot to data science has caught businesses (and educational institutions) short. Data scientists are currently in short supply and high demand. As machine learning, AI, analytics and big data technologies become ubiquitous, businesses will need high-level analytics capabilities to stay competitive. Unfortunately, the challenge is that there aren’t enough experts in SQL, analytics, and databases to meet their needs. To bridge the gap, businesses have started to rely on what Gartner calls “citizen data scientists.”

It’s likely you have the makings of citizen data scientists on staff already – you may just not know who they are. They may be developers who are more data than process-centric. They may be your power users who combine strong analytical skills with subject matter expertise. Both types of employees offer great potential for augmenting your data science teams.

Creating Citizen Data Scientists

Training and support are critical for the success of citizen data scientists. Business analysts have basic knowledge of statistics, and developers an understanding of data and databases. But to fill a citizen data scientist role, they’ll also need to know how to formulate questions to ask of the data, determine the types of models and approaches best used to gather results, then present those results meaningfully in visualizations and presentations.

Even if they already have strong business knowledge and analytics experience, to be effective, citizen data scientists will need further training and empowerment, specifically:

  • Technical training to earn new skills like SQL, Python and R
  • Data democratization – better access to an organization’s digital assets
  • Clear, well-established company policies on data usage, provenance, modeling and compliance.
  • In-depth understanding of data access, security and management
  • Support for algorithm and modeling development
  • Established procedures and processes for interaction with IT departments
  • Access to software tools for analytics
  • Infrastructure to provide data access, security, governance and oversight
  • Career paths that include analytics

The Role of Self-Service Analytics Tools

Organizations today face the heavy challenge of becoming data-driven. Citizen data scientists can help effect this change in three ways. First, they can round out your data science team. Second, they can provide subject matter expertise that data scientists may lack. Finally, many of the skills, processes and toolsets they learn can be extended to frontline business users, to promote data literacy throughout the enterprise.

According to Gartner VP Mike Rollings, 80% of organizations aim to start data literacy projects by next year, because “…although digital business thrives on data and its analysis, we still see that data and analytics only plays a supportive role when it comes to business initiatives. This has to change.” Self-service reporting and analytics solutions like Orbit have an important part to play in helping business users better understand their data to make the right decisions.

Orbit offers self-service reporting and analytics to accelerate real-time operational reporting and analytics for your business. Contact us for a live demo of the next generation of reporting and analytics.

Image credit: Asa Wilson [CC BY-SA 2.0], via Wikimedia Commons

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