When the company implements an analytics approach, you’re probably concerned about ensuring that the solution is adopted by market customers. If you are unable to engage market users and gain user acceptance, the return on investment (ROI) would be low! However, it is critical to recognize that the correct augmented analytics approach will provide the context and basis for enterprise users without needing them to possess advanced knowledge of algorithms and computational techniques.
Assisted Predictive Modeling, Smart Data Visualization, and Self-Serve Data Preparation features and software allow consumers to receive auto-recommendations, advice, and feedback that result in consistent findings – results that business users do not have to analyze. The visualization format can direct the consumer to the appropriate displays and graphics depending on the data’s type and length, as well as other variables. The predictive analytics tools can allow the user to choose the appropriate algorithm or analytical methodology depending on the type of data, the user’s objectives for the data, and other variables. Self-serve data preparation enables users to rapidly collect and compile data for review without having any prior knowledge of programming, scripting, or data retrieval, transformation, and loading (ETL) techniques.
In brief, the consumer may not need to be an information technology expert, a programmer, or a data scientist to obtain the desired results. The only stipulation (and it is a critical one) is that enterprise customers have a fundamental knowledge of analytics in the following manner:
- Recognize the rationale for analytics and the advantages of dealing with factually accurate data.
- Possibility to operate with a straightforward augmented analytics approach whilst receiving assistance and feedback when required.
- Understanding what analytics might teach them and how it can assist them in their daily activities.
- Awareness of fundamental computational methods and sensitivity to those employed inside the augmented analytics solution.
Although extensive preparation is not needed to ensure that the augmented analytics solution is implemented across the organization, the company must have a strategy in motion to include the most simple advice and support to enable and motivate market customers to utilize the augmented analytics solution you have.