Every business faces the challenge of managing and using data in a way that is meaningful, accurate and easy for users. To meet objectives, plan strategies and analyze information, the average enterprise must juggle best-of-breed, legacy systems, and many other data repositories that sometimes seem to hide data from even the most gifted analysts and IT staff members.
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.
Why would your business need Self-Serve Data Preparation? Perhaps you have a team that includes IT professionals that can prepare data for analysis or maybe you have a business analyst or a data scientist to serve that need. But, there are plenty of good reasons to consider data preparation tools that are easy enough for every team member to use.
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!
If your team is using business intelligence (and it should be), you may be working with a more restrictive business solution that is not designed for a business user. If that is the case, you are missing an opportunity to cascade analytics throughout the organization and to optimize your resources and improve productivity. Self-Serve Business Intelligence solutions are designed with guidance and recommendations to guide a business user with average skills through the process of preparing and analyzing data and to encourage collaboration and data sharing across the enterprise.
Here’s some good news! If you want to predict or forecast results for your business, you don’t need to be a data scientist, a statistician, a business analyst, or a rocket scientist! Today, augmented analytics solutions provide all the help a business user will need to gather data, prepare it for analysis and then choose the right algorithm or analytical technique to analyze the data and get clear, easy-to-understand results.
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.
