Biz Users Get Plug n’ Play Analytics, Data Scientists Get R Integration!
When someone says ‘plug n’ play’, a lot of people think of the idea of plugging in an electrical appliance and having it run instantly. I think plug n’ play analysis should be that simple as well!
My business users don’t have the skill, the patience or the time to become data scientists. But, they don’t have to be data scientists to use augmented analytics. Tools like Assisted Predictive Modeling allow the average business user to become a Citizen Data Scientist with tools that offer guidance and auto-suggestions to help the user arrive at the outcome they need without being frustrated or having to call in an army of analysts and IT staff to help them complete their analysis.
Predictive Analytics for business users leverages machine learning and assisted predictive modeling to help users achieve the best fit and ensure that they use the most appropriate algorithm for the data they wish to analyze. With these tools, users can explore patterns in data and receive suggestions to help them gain insight on their own without dependence on IT or data scientists. The enterprise can provide the tools needed at every level of the organization with tools and data science for business users that are sophisticated in functionality and easy-to-use for users at every skill level.
Predictive modeling capability and auto-recommendations simplify use and allow business users to leverage Predictive Analytics Algorithms without the expertise and skill of a data scientist. The plug n’ play predictive analytics and predictive modeling platform is suitable for business users. 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.
In addition to all of these benefits, you can sell your organization on this type of easy-to-use, sophisticated augmented analytics tool by pointing out that data scientists who want to leverage R Script can use these tools to capitalize on their expertise and on enterprise investments in R open source platform. They can perform statistical and predictive algorithms, and complex analysis to provide the depth of detail and advanced analytics and reporting the organization needs for strategic decision-making.
So EVERYONE is happy. Business users have the plug n’ play predictive analytical capacity they need to function at peak performance and data scientists can leverage sophisticated tools to add value to strategic initiatives.
What could be better? If this sounds good to you, I can tell you how to get started. Assisted Predictive Modeling with R Integration
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