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Predictive Analytics

Why Predictive Analytics Projects Fail?

Implementing a predictive analytics strategy can be an expensive proposition with uncertain outcomes if not done right. Following are some reasons why most predictive analytics projects go awry.

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Failure to achieve enterprise adoption
insights
Failure to provide actionable business insights
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Failure to deliver complex architecture in reasonable time
Predictive Analysis
Failure to modularize predictive analytics components

Predictive Analytics Simplified

PiCube provides an easy-to-adopt model to operationalize and manage your predictive analytics investments.

  • Designed-to-use for predictive analytics
  • Industry-leading components that are selected, configured, integrated and performance-tuned by our team of experts
  • Built-in connectors that enable easy integration with standard data sources and visualization engines
  • Easy to deploy in a variety of environments, in-house or virtualized
Improved Business Agility

Value co-creation with customers

Automated risk-based decisions

Sustainable growth through improved decision distribution

Designed for Predictive Analytics

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Modular predictive analytics components

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Ready-to-use
generalized data sets

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Composable computational models

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Technology
architecture governance

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Composable
delivery models

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Data
source adaptors

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Evaluation and refinement frameworks

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Managed technology infrastructure

Adaptable Architectural Framework

PiCube has a unique value proposition that makes it easy to build and deploy your predictive analytics applications using technology architecture and infrastructure that is designed for predictive analytics.

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