Latest Insights on Vendor Comparison in Predictive Analytics Market 2016

The report on vendor comparison in predictive analytics 2016 will help the stakeholders such as application control vendors, technology partners, system integrators, distributors, and value added re-sellers to make business strategies and decisions on the deployment of application control solutions.

The vendor comparison report on predictive analytics based on MnM DIVE methodology covers a detailed study of the major players offering predictive analytics solutions. The key 10 vendors of predictive analytics were analyzed on the basis of their product offering and business strategy. The vendors were shortlisted based on their solution capabilities, technology innovations, industry coverage, viability, breadth of product offering and others.

Complete report on vendor Comparison in Predictive Analytics 2016 spread across 60 pages, profiling 10 companies is now available at .

The research defines predictive analytics as a technology for predicting the future outcomes, on the basis of analyzing either historical data or present data. It helps in determining the trends and patterns within the data that is beneficial for organizations to estimate and make predictions about the future and take appropriate actions according to the predicted results. Predictive analytics solutions comprises an array of capabilities including automated analytics, advanced visualization, predictive scoring, big data analytics, R integration, risk management and other capabilities.

Vendors Evaluated

The report covers the comprehensive study of the key vendors offering solutions for predictive analytics. We have evaluated the following 10 key vendors:

• Alpine Data Labs
• Alteryx, Inc.
• Angoss Software Corporation
• Birst
• Fair Isaac Corporation (FICO)
• IBM Corporation
• RapidMiner
• SAS Institute
• Tableau Software
• TIBCO Software, Inc.

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Vendor Inclusion Criteria

We have selected the 10 vendors for evaluations based on their breadth of product offering and robust business strategy. The focus of our vendor evaluation is based on the product they offer in the predictive analytics market. A comprehensive list of all the vendors in this market was created through a product mapping strategy and analysis. Based on their capabilities, innovations, and breadth of product offering, vendors were shortlisted. Our selected vendor mix includes companies from tier 1 to tier 4 and covers the whole market comprehensively.

Table of Contents

1 Introduction

1.1 About the Document
1.2 Market Definition
1.3 Stakeholders

2 Premium Insights

3 MnM Dive Overview

3.1 Dive Evaluation Overview
3.2 Vendor Inclusion Criteria
3.3 Vendors Evaluated

4 MnM Voice – Predictive Analytics

4.1 Predictive Analytics: A Prevailing Tool to Analyze Big Data and Predict the Future of Business Outcomes
4.2 Predictive Analytics: Best Practices

5 Predictive Analytics: Vendor Comparision

5.1 MnM Dive Scorecard
5.2 MnM View

6 Vendor Profiles

6.1 IBM Corporation
6.2 SAS Institute
6.3 Angoss Software Corporation
6.4 Tableau Software
6.5 Rapidminer
6.6 Tibco Software, Inc.
6.7 Alpine Data Labs
6.8 Fair Isaac Corporation (FICO)
6.9 Alteryx
6.10 Birst

7 Appendix

7.1 MnM Dive Vendor Comparision Methodology
7.2 Quadrant Description
7.3 List of Abbreviations
7.4 Related Research
7.5 Endnotes/References

On a related note, another research on Vendor Comparison in Application Control 2016: MnM DIVE Matrix covers a detailed study of the major players offering application control solutions. The report will help the stakeholders such as predictive analytics vendors, technology partners, system integrators, consultants, distributors, and value-added resellers to make business strategies and decisions on the deployment of predictive analytics solutions. Vendors like Symantec Corporation, Intel Security (McAfee), Trend Micro, Inc., Cyber Ark Software Ltd., Carbon Black, Inc., Digital Guardian, Check Point Software Technologies Ltd., LANDESK Software (AppSense) and Thycotic (Arellia) have been profiled in this 60 pages of research report available at .

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Release ID: 112555