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Blog > June 2018 > 6 Tips to Set Up Your Citizen Data Scientists for Success

6 Tips to Set Up Your Citizen Data Scientists for Success

As democratized data continues spreading across the modern enterprise, you may have noticed a new role emerging along IT and business positions: Citizen Data Scientists (CDS). Your organization may feel overwhelmed by the volume of big data it’s generating — especially as you are increasingly pressured to leverage that data to inform decision-making and business initiatives. To keep up, more enterprises are rolling out new tools and technologies that CDSs can use to create data models that extract deep insights for business, a role that builds on their primary positions as line-of-business professionals or business analysts. In fact, Gartner predicts that CDSs will surpass data scientists in the amount of advanced analysis produced by 2019. This will allow data scientists, who are fully dedicated to analyzing and interpreting digital data, to focus on more complex analysis and create a more analytics-driven business environment for your organization.

While CDSs don’t have to be data science experts, they do need to master the data tools at their disposal and know which insights are important to business — though it is the organization’s job to set them up with the right tools, environment and mindset to succeed. Here are six tips to ensure your CDSs contribute value to your business:

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  1. Know what it takes to be a CDS. Being a CDS requires some experience and a detailed understanding of the business — as well as a commitment to discovering usable results and driving decisions based on data. A skilled CDS knows what questions to ask and is willing to persevere through data complexity and imperfection to find the answer. While the ability to learn how to use the tools is important, that technical facility offers no value without a business-minded approach.
  2. Distinguish CDSs and data engineers. Think about how you want to split workloads between CDSs and data engineers. You need to define the CDS’s role by providing a framework for the areas of data they should explore and the portfolio of tools they should use. CDSs are unlikely to survive in isolation — they need support. Data engineers — in addition to optimizing the implementation, monitoring and maintenance of IT systems — may need to help CDSs with data preparation. Or, when it comes to understanding different approaches to data challenges, CDSs may require guidance from data scientists. With this assistance, CDSs can focus on completing data-centric projects rather than enabling them, taking guidance from IT on which tools and strategies to leverage.
  3. Equip CDSs with the right tools. There are many tools available on the market today, and their capabilities overlap. Make sure to assess CDSs’ scope of work and provide tools with capabilities that meet each need for every task. The major building blocks include data ingestion, understanding, preparation, analysis, documentation, publication, collaboration and governance.
  4. Create a supportive environment. For every tool that you decide to make available to CDSs, you must provide a supporting environment. Identify the training, reading materials and useful websites necessary to ensure CDSs can leverages tools to the best of their abilities — and always have an expert on hand to assist with particularly complex problems.
  5. Encourage documentation. Make sure that CDSs document their work. Metadata is, and will always be, vital. Help CDSs to avoid having to go back and re-understand the data they created but left, even for a short time, untouched.
  6. Provide Boundaries. Not every type of data belongs in the data lake, and not everyone should be able to access every type of information. Set expectations for CDSs for where they should focus their investigation, where they should apply results to drive business decisions, and in what cases they need to refer to others in the organization.
The emergence of big data technologies embodies the essence of the fourth Industrial Revolution — enabling business users to work more closely with data on their own initiatives, with a much-lessened dependence on data specialists. Ultimately, the contribution of CDSs will help control costs related to data workflows, make it easier to document and track the data behind business decisions and enable data scientists to focus more on their responsibilities.

For examples of the types of tools that CDSs can leverage to make data-driven business decisions, check out our Enterprise Data Intelligence solution and Content Solutions.
 
Posted: 6/7/2018 10:14:51 AM by Ian Rowlands | with 0 comments


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