Alpine Touchpoints, accessible Predictive Analytics to the Business User
Alpine Touchpoints, accessible Predictive Analytics to the Business User : Alpine Touchpoints, is a new way to make Advanced Analytics accessible across an Enterprise. Touchpoints is an industry-first application services layer that enables business users to interact with complex analytic assets and incorporate them into their existing activities and workflows. Touchpoints transforms the genius of data science into business assets that enrich the daily activities of the people who drive business value every day.Enterprises have spent billions of dollars on big data platforms and initiatives but have struggled to find enough data scientists to create business value. Alternatively, it is extremely difficult for business analysts to utilize insights from data scientists at everyday scale. To resolve this gap, some have attempted to train business users to build complex models themselves, or to deploy data scientists tactically, but neither approach addresses the larger need to scale data science to thousands of employees.
Touchpoints bridges this gap, allowing business users to transform their daily workflows with machine learning without requiring them to learn data science or retraining them to use new systems. Enterprises can deploy task-specific Touchpoints in forms that are immediately recognizable, such as a text or email alert, or an interactive experience within an existing application.
“Combined with Alpine’s Enterprise grade management platform, we have a solution that will allow us to effectively distribute operational analytics throughout the organization,” said Matthew Cunningham, Executive Vice President at eviCore healthcare. “Our goal is to eliminate the silos that inhibit collaboration, data sharing, and slow the implementation of innovative solutions. We rely on Alpine to help us bridge the gap between our analytics, technology, and operational teams and significantly accelerate the deployment of sophisticated analytic models into our operational business units.”
Touchpoints places the power of predictive models in the hands of business users, without forcing them to learn the language of data science. The Alpine Enterprise platform gives a place for data scientists to build complex models and for analysts to distribute these to a diverse set of roles within any company. Business analysts can now deliver intuitive user interfaces on top of complex analytical models to as many end users as needed, and put the syntax of a model in a format that can be more broadly put to use. Instead of going through an endless cycle of approaching siloed data science teams with a problem, business users can use Touchpoints to interact with a model and retrieve powerful results that can affect their day-to-day activities.
Touchpoints allows business analysts to wrap analytic assets in use case specific interfaces which hide the complexity of the underlying models. Places the output of analytic assets (or an Interactive Touchpoint) directly into a third party environment, such as CRM, BI and logistics applications, or bespoke internal software; and makes insights available in familiar mobile interfaces, such as SMS alerts and use case driven applications.
Touchpoints also provides a constant feedback loop between the end user and business analysts. Business analysts can monitor and better understand which insights are being used and how they are consumed. By collecting metadata from employee activity, the analysts can constantly optimize the models and delivery of the insights.
“Too much has been invested in big data to reap such minimal business value,” said Joe Otto, CEO of Alpine Data. “Everyone on the vendor side has been focused on the different ways to create insights with little regard for how to connect these insights into the business layer. Touchpoints is an extension of our Enterprise management framework, and just the start of our plan to make predictive analytics part of day-to-day business.”
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More Information on Predictive Analysis Process
For more information of predictive analytics process, please review the overview of each components in the predictive analytics process: data collection (data mining), data analysis, statistical analysis, predictive modeling and predictive model deployment.