When you launch an analytics solution within your enterprise, you are probably concerned about getting your business users to adopt that solution. If you can’t engage the business user and achieve user adoption, your return on investment (ROI) will be poor! But, it is important to understand that the right augmented analytics solution can provide the structure and foundation for business users without requiring them to have a sophisticated knowledge of algorithms and analytical techniques.
Features and tools like Assisted Predictive Modeling, Smart Data Visualization and Self-Serve Data Preparation allow users to get auto-recommendations, suggestions and guidance that will produce clear results – results that business users will not have to interpret. The format for visualization will guide a user to the right displays and graphics based on the type and volume of data and other factors. The predictive analytics tools will allow the user to choose the right type of algorithm or analytical technique based on the type of data, what the user wants to know about the data and other factors. Self-serve data prep allows users to quickly gather and assemble data for analysis without knowledge of programming, scripting or data extraction, transformation and loading (ETL) techniques.
In short, the user does not need to be an IT professional, a programmer or a data scientist to get the results they need. The only requirement (and it is an important one) is that business users have a basic understanding of analytics as follows:
While advanced, comprehensive training is not required to ensure that your augmented analytics solution is adopted across the enterprise, your business must have a plan in place to provide the most basic instruction and support so that business users are encouraged and eager to use the augmented analytics solution you provide.