What is a Citizen Data Scientist and How Has the Role Changed?

Defining and Understanding the Citizen Data Scientist

The world-renowned technology research firm, Gartner, first introduced the concept of the Citizen Data Scientist in 2016. Since then, the idea has grown in popularity, and the role has grown in importance and prominence.

‘To fulfill the role of a Citizen Data Scientist, business users today can leverage augmented analytics solutions; that is analytics that provide simple recommendations and suggestions to help users easily choose visualization and predictive analytics techniques from within the analytical tool without the need for expert analytical skills.’

Gartner defines a citizen data scientist as, ‘a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.’

Who is a Citizen Data Scientist? The role of a citizen data scientist is played by a business user or team member within the organization. The typical profile of an ideal Citizen Data Scientist is a person who is respected within the organization, and often shares data and information with other users to collaborate and produce outcomes that are designed to achieve goals and objectives and produce a successful outcome. These individuals may already be ‘power users’ of business applications and may have developed and reported or presented data to others with an eye toward clarifying their decision-making. Citizen Data Scientist candidates may also be IT team members who are interested in data science. In any case, these candidates will typically be uniquely curious, interested in data analytics and devoted to fact-based decisions and team collaboration.

The Definition and Evolution of the Citizen Data Scientist Role

Who are Citizen Data Scientists within your own organization? You will know them by their willingness to learn new things, and to advance their own visibility and their own careers by using new skills to improve results within your organization. What are Citizen Analysts? They are team members who are not IT professionals, data scientists or business analysts but are willing and able to leverage analytics and data science tools to solve business problems.

It took a while for the global business community to embrace the concept of Citizen Data Scientists and, even today, there are those naysayers who believe that the only correct approach to analytics is by using Data Scientists or business analysts or engaging the internal IT team to create reports and provide analytics for decision-making.

But the race to compete and the complexities and rapid rate of change have forced businesses to look for alternatives and the Citizen Data Scientist role has become more popular as those leading the charge prove the value of the role to the organization and to the business users, data scientists and IT professionals.

The role of the Citizen Data Scientist began as a simple augmentation to gather data and create reports for daily use but Interest In The Role Has Tripled Over The Past Decade, and the responsibilities and visibility of the Citizen Data Scientist have evolved.

Much of the evolution and the potential of the role has been driven by the evolution of business intelligence (BI) tools and the introduction of augmented analytics and solutions that employ natural language processing (NLP) and machine learning to enable those with average technical skills to gather and analyze data and produce results for clear insight, using sophisticated tools that are designed to be simple enough for the average business user to understand.

As team members perform these tasks, share data and collaborate, the business can engender data democratization and improve data literacy across the enterprise.

To fulfill the role of a Citizen Data Scientist, business users today can leverage augmented analytics solutions; that is analytics that provide simple recommendations and suggestions to help users easily choose visualization and predictive analytics techniques from within the analytical tool without the need for expert analytical skills.

When a Citizen Data Scientist uses these tools, the resulting analysis can be combined with the professional knowledge and specific domain skills of the individual to better understand and gain insight into trends, patterns, issues and opportunities and improve time to market, accuracy of predictions, and metrics and measurements.

Adopting these tools and techniques and actively engaging in augmented analytics allows the Citizen Data Scientist to more effectively interact with and collaborate with the IT team and data scientists to prepare data and use data in use cases, and to refine outcomes and improve data-driven decision making across the enterprise.

One of the most important lessons learned in the past decade is that the Citizen Data Scientist role can be rewarding to the organization and to the business user. But to succeed, the enterprise must plan carefully. It must understand how to use Citizen Data Scientists and create an environment that allows for this transition. Selecting a business intelligence or augmented analytics tool and deploying that tool does not, in and of itself, solve your problems. You must plan for the cultural shift and ensure that the business users have the support they need to transition into the citizen data scientist role.

‘The typical profile of an ideal Citizen Data Scientist is a person who is respected within the organization, and often shares data and information with other users to collaborate and produce outcomes that are designed to achieve goals and objectives and produce a successful outcome.’

For a detailed discussion of Citizen Data Scientists and related topics, read our article: ‘What Is A Citizen Data Scientist, What Is Their Role, What Are The Benefits Of Citizen Data Scientists…And More!

Contact Us to find out how augmented analytics Technology can support your enterprise, and ensure analytical clarity and results. Discover the next level of Self-Serve Analytics and explore online Citizen Data Scientist Training and the features and modules of a seamless, sophisticated, easy-to-use augmented analytics solution to see how your business can use analytics to achieve its goals. Explore our complementary articles on Citizen Data Scientists: ‘The Importance And Benefits Of A Citizen Data Scientist Initiative,’ ‘Planning And Preparing For A Citizen Data Scientist Initiative,’ ‘Engage A Skilled IT Partner And Achieve Citizen Data Scientist Success,’ and ‘What Is A Citizen Data Scientist, What Is Their Role, What Are The Benefits Of Citizen Data Scientists…And More!

Citizen Data Scientists Can Partner With Data Scientists!

A Citizen Data Scientist Initiative Can Optimize Data Scientists and Encourage a Data-Driven Culture!

According to some estimates, the average salary of a Data Scientist in the United States is over $150,000 per year. If your business wishes to accommodate a ‘data-first’ strategy to improve metrics and measurable success and avoid guesswork and strategies that are based on opinion rather than fact, it can either employ a team of expensive professionals, or it can take a different approach.

‘Citizen Data Scientists can use their knowledge of a business sector, industry, function or market to drive questions and develop reports and presentations to illustrate issues, identify problems and find opportunities for growth and competitive positioning, and share this data (and the search and analytical techniques) with other users.’

Citizen Data Scientists are business users who have a place on your team and are hired because of their professional and career experience in a particular industry, business function or discipline. When they are given access to data analytics, they can merge their knowledge of an industry, e.g., research, healthcare, law, finance, sales, supply chain, production, construction etc., with data integrated from databases, best-of-breed software programs, ERP, SCM, HRM and other systems and use sophisticated analytical tools in an easy-to-use, intuitive environment to gather and analyze data and produce insightful, concise results that are meaningful to their role.

Leverage Citizen Data Scientists to Augmented Data Scientist Teams

Depending on the size, market and industry of your business, you may choose to augment your staff with one or more data scientists to refine results produced by Citizen Data Scientists on a day-to-day basis. So, if a power user or business users discovers a challenge or an opportunity and your management team wishes to further explore the issue to understand its strategic or operational value, a Data Scientist can take the predictive model or other analytical report produced by a Citizen Data Scientist and refine the results for executive review.

Whether you choose to employ the services of a Data Scientist, provide business analysts or IT professionals to support your business users, you can create a comprehensive foundation for analytics across your organization.

By democratizing data analytics you can achieve many benefits, including:

  • Improved Data Literacy Across the Enterprise
  • Improved Productivity of Data Scientists, IT and Business Analysts (who can spend time on strategic initiatives rather than producing daily reports)
  • Optimized Return on Investment (ROI) and Total Cost of Ownership (TCO) for all software and systems
  • Fact-Based Decisions and Metrics-Driven Strategies, Goals and Objectives
  • Team Member Career Advancement
  • Optimization of Resources and Improved Team Productivity

A comprehensive self-serve augmented analytics solution will include Modern Business Intelligence (BI) and Reporting with Key Performance Indicators (KPIs), Self-Serve Data PreparationAssisted Predictive Modeling, and Smart Data Visualization with auto-suggestions to drive the analytical techniques and illustration of data based on data type, volume, etc., and other tools like Embedded BIMobile BIKey Influencer AnalyticsSentiment Analysis, and Anomaly Alerts and Monitoring.

With these tools, the Citizen Data Scientist can leverage Natural Language Processing (NLP) and search analytics with machine learning to ask questions using simple human queries and receive insightful answers. They can use their knowledge of a business sector, industry, function or market to drive questions and develop reports and presentations to illustrate issues, identify problems and find opportunities for growth and competitive positioning, and share this data (and the search and analytical techniques) with other users.

Citizen Data Scientists can predict customer responses to new product features, and to new marketing campaigns, analyze the likelihood of fraud or risk, identify supply chain issues, etc. These tools can also help the organization to foster collaboration and data sharing and encourage business users to innovate, create and explore opportunities using data-driven, factual information.

‘When Citizen Data Scientists are given access to data analytics, they can merge their knowledge of an industry, e.g., research, healthcare, law, finance, sales, supply chain, production, construction etc., with data integrated from databases, best-of-breed software programs, ERP, SCM, HRM and other systems and use sophisticated analytical tools in an easy-to-use, intuitive environment to gather and analyze data and produce insightful, concise results that are meaningful to their role.’

These are just a few of the factors you must consider when implementing a Citizen Data Scientist approach. Business users who are interested in becoming a Citizen Data Scientist must be willing to embrace new technology and tools and working at the leading edge of a new approach to collaboration and decision-making. initiative. Consider engaging an expert for your Citizen Data Scientist. IT consultants with experience and skill in this area can provide crucial support to help you succeed with your Citizen Data Scientist initiative and can provide simple Training Programs to bring your team on board and help them see the value to themselves and to the organization.

Original Post : Leverage Citizen Data Scientists to Augmented Data Scientist Teams!

Give Your Business Users Assisted Predictive Analytics!

Assisted Predictive Modeling Enables Business Users to Predict Results with Easy-to-Use Tools!

Gartner predicted that, ‘75% of organizations will have deployed multiple data hubs to drive mission-critical data and analytics sharing and governance.’

With all of this business data, how can your organization a) help your team gather and use data to make fact-based decisions, and b) use that data to predict which products and services your customers will need in the future, how your customer buying behavior is shifting, how your competition will respond to the market, when and how to sell your products, which marketing campaigns will work in the future, and how and when to recruit new resources and open new locations.

‘Giving your team access to sophisticated, complex analytical techniques in an intuitive environment, allows them to leverage predictive analytics without a data scientist or analytical background.’

A misstep in any of these areas can create risk, damage your business reputation, or put you years behind your competition. That’s why your business needs predictive analytics. And, not just any predictive analytics! If you want to democratize data among your team members and provide easy-to-use tools to encourage user adoption and enable data-driven decisions, you must choose wisely.

Leverage Predictive Analytics for Every Business User

Assisted predictive modeling can take the guesswork out of analytics, by helping users to choose the right techniques to analyze the type and volume of data they use to analyze. These tools allow the organization to apply predictive analytics to any use case using forecasting, regression, clustering and other methods to analyze an infinite number of use cases including customer churn, and planning for and target customers for acquisition, identify cross-sales opportunities, optimize pricing and promotional targets and analyze and predict customer preferences and buying behaviors.

Prescriptive analytics for regression models combines predictive modeling and optimization techniques to produce actionable recommendations for decision-making. While descriptive and predictive analytics use past events to predict future outcomes, prescriptive analytics goes beyond this process to recommend optimal actions that will help the business to achieve specific goals. By merging prediction with prescription, the enterprise can proactively identify challenges and opportunities, and drive more effective and strategic outcomes.

These are just some of the tools your business should consider to build a solid foundation for predicting outcomes using historical and forward-looking data analytical techniques.

Giving your team access to sophisticated, complex analytical techniques in an intuitive environment, allows them to leverage predictive analytics without a data scientist or analytical background. Your users can access:

  • Time Series Forecasting
  • Regression Techniques
  • Classification
  • Association
  • Correlation
  • Clustering
  • Hypothesis Testing
  • Descriptive Statistics

‘Assisted predictive modeling can take the guesswork out of analytics, by helping users to choose the right techniques to analyze the type and volume of data they use to analyze.’

With the right predictive analytics solution, your business can also support data scientists, IT and business analysts with tools that allow for R script integration, so these users can perform complex statistical and predictive analysis and reporting to support strategic organizational needs.

Smarten Assisted Predictive Modeling will support your team with tools that are intuitive and easy to use and will encourage user adoption.  Leverage the essential components of Augmented Analytics and improve decision-making and outcomes.

Original Post : Leverage Predictive Analytics for Every Business User!

Choose the Right Mobile BI Solution for Your Business!

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Does Embedded BI Support User Decisions?

Where Does Embedded BI Fit in Business Decision-Making?

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Integrated Tally Analytics = Small Business Results

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