An advanced analytics solution that is designed for augmented analytics, must be easy enough for the average business user to achieve results without IT skills or the skills of a data scientist. When a business user can leverage clickless analytics search capability, the user can achieve rapid, clear results and use those results to solve problems, share information and optimize opportunities for the business.
When a business is considering an advanced analytics solution, it must sell its management team and investors on the value and benefit of that solution and the merits of implementing such a solution or upgrading an existing solution.
Smarten is pleased to announce the introduction of its eLearning Workshop, ‘Be a Citizen Data Scientist – Aspire, Inspire, Become‘. This online course is designed to provide a solid foundation for one’s business and, more importantly, for those members of the team who may be considering as early adopters or champions of the Citizen Data Scientist transformation within their organization.
What is a Citizen Data Scientist and what is the role of a Citizen Data Scientist? It isn’t as complicated as you might think. A Citizen Data Scientist is a business user working in a professional capacity within an enterprise – one who is collaborative and curious by nature and willing and ready to adopt augmented analytics tools to prepare and analyze data and use that data to gain insight into business issues and opportunities. The role of a Citizen Data Scientist is to interact with and liaise with IT and data scientists to define use cases and refine data output to be used in making fact-based decisions.
Creativity is the lifeblood of an enterprise! But, it is easy to get into a rut and do what has worked in the past. If a business is to succeed, it must constantly generate new ideas and new ways to address the market and its consumers. Augmented Data discovery and the new world of self-serve tools has added an interesting dimension to this discussion as it encourages business users to become Citizen Data Scientists and encourages organizations to embrace data democratization.
It is a great idea to get your business users involved in analytics and to encourage and build data literacy in your enterprise but one of the things that often stops an organization from implementing self-serve analytics is the need to gather and prepare the data for analytics. How can IT or data scientist staff turn over day-to-day analytics when data is spread across the enterprise and it is so difficult to integrate that data and prepare the data for analytics?
I had a conversation with a dear friend the other day and one of the things we discussed was the ubiquitous mention of Citizen Data Scientists in technology and industry publications and conferences. My friend (who shall remain nameless), insisted that this was just another passing fancy and that Citizen Data Scientists were not really all that important in building the enterprise of the future.
If you’ve heard the Digital Transformation buzz, you probably have a lot of questions. Let’s dive into some of those questions and see if we can clear up the confusion!
Digital Transformation (Dx) is achieved when an organization plans and exploits digital technologies, workflow and processes, and its core capabilities and skills with an enterprise culture that evolves and shifts to engender a digital business model that advances business. Any Dx plan must include a review and appropriate modification of businesses processes, business models, operations, team collaboration and customer relationships.
As businesses struggle to remain competitive and to do more with less, every enterprise is looking for a way to optimize resources, and to get the most out of every team member. To do that, the business management team must leverage the knowledge and skills of each team member as those skills relate to their role and their responsibilities. Businesses must use team member knowledge gleaned from experience and education and merge that knowledge with data and analytics to make context-based, data-driven decisions.
