Information Technology

Predictive Analytics in the Real World

 


RELEASE DATE
23-Oct-2015
REGION
North America
DELIVERABLE TYPE
Strategic Forecasting

RESEARCH CODE
9A37-00-23-00-00
SKU
IT00240-NA-SF_01236
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Predictive Analytics in the Real World
Published on: 23-Oct-2015 | SKU: IT00240-NA-SF_01236

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The field of predictive analytics is one of the most complex and challenging subsets of the Big Data and advanced analytic market. There is also a very wide gap between the practitioners of predictive analytics—most of whom are statisticians, scientific researchers and data scientists—and the people who most want to use predictive analytics for commercial and industrial applications. Bridging this gap with accurate information and clear communication is imperative if predictive applications are to satisfy business users’ expectations. The purpose of this report is to assist in building this bridge: first, by placing predictive analytics in a practical conceptual context for business people; then, by exploring several of the promising solutions that are coming to market.

The Theoretical World of Models and the Real World of Data

How Theoretical Models are Linked to Real World Data Analysis

Important Differences in the Way in Which We Relate to Real World Models

Dato Targets Developers with Single Code Base from Dev to Production

Nutonian Leads with Symbolic Regression and Genetic Programming

Skytree Optimizes for Enterprise Grade Implementations

  • Dato’s Platform
  • Important Capabilities of the Dato Platform

The Predictive Analytics Process

List of Figures
  • 1. The Theoretical World of Models and the Real World of Data
  • 2. How Theoretical Models are Linked to Real World Data Analysis
  • 3. Dato’s Platform
  • 4. Comparing Eureqa’s Model Generation Approach to Traditional Algorithms
  • 5. Skytree High Level Architecture
  • 6. The Predictive Analytics Process

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