Vendor Comparison in Predictive Analytics, 2016 – MnM DIVE Matrix
[60 Pages Report] In today’s data driven world, one of the biggest challenges for the companies is to manage the rapidly generating, voluminous data. Along with this, the ever-increasing business demand for maximum flexibility of resources and the inevitable advancement of big data are encouraging the enterprises to adopt the predictive analytics model. It empowers an organization to identify untapped opportunities and expose hidden risks buried inside enormous amounts of data. With the availability of predictive insights to everyone in the organization, organizations are empowered to make the right choices at the right time and shape their future in a positive way.
MarketsandMarkets 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.
The increasing amount of business data across industry verticals and the rising demand for market and competitive intelligence have fueled the growth of predictive analytics solutions within the organizations. Predictive analytics has become an indispensable practice for enterprises, to sustain in the competitive environment.
The report on Vendor Comparison in Predictive Analytics based on MnM DIVE Methodology analyzes and evaluates the key vendors in the predictive analytics market.
Vendor Inclusion Criteria
We have selected 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 MarketsandMarkets 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. The below table describes the company types with their revenue range:
To know about the assumptions considered for the study, download the pdf brochure
The report covers the comprehensive study of the key vendors offering solutions for predictive analytics. We have evaluated the following 10 vendors: Alpine Data Labs, Alteryx, Inc., Angoss Software, Birst, Inc., Fair Isaac Corporation (FICO), IBM Corporation, RapidMiner, SAS Institute, Tableau Software, and TIBCO Software.
Predictive analytics is the practice of extracting meaningful information from present as well as historical data sets. The practice determines the patterns of data and predicts the future outcomes and trends. Basically, predictive models and analysis are used to estimate future probabilities with an acceptable level of consistency. Predictive analytics implements mathematical, regression modeling, statistical, neural nets, machine learning, genetic algorithms, text mining, decision trees, clustering, and data exploration techniques to extract insights from historical and present data. It also helps organizations uncover the hidden trends and patterns from big and complex data sets. It evaluates the structured as well unstructured data such as e-mails, chat interaction, and social media interaction. Predictive analytics estimates which type of involvement will be required, where, and when.
The key benefit of predictive analytics is that it enables organizations to identify untapped opportunities and expose hidden risks buried inside vast amounts of data. By making predictive insights available to everyone, organizations are empowered to make the right choices at the right time and shape their future in a positive way. The major growth drivers of the predictive analytics market include increase in the amount of data generated across industry verticals, increased focus on market and competitive intelligence, and higher and cheaper computing power. The predictive analytics market faces challenges such as lack of transformation from legacy architecture and lack of appropriate analytical skills. Factors such as complex analytical workflow and diversity of data models based on business needs are expected to limit the market growth.
The report on vendor comparison in predictive analytics based on MarketsandMarkets DIVE methodology reviews major players that offer predictive analytics solutions and outlines the findings and analysis on the basis of two broad categories: Product Offerings and Business Strategies. Each category carries various criteria, based on which the vendors are evaluated. The criteria are provided below:
Based on the extensive secondary and primary research, key information about the vendor’s product offering and business strategies was gathered. After the completion of data gathering and verification process, the scores and weightage for shortlisted vendors against each parameter was finalized. After evaluating all the vendors, a comparison scorecard was prepared and each vendor was placed in the MnM DIVE matrix based on their product offering and business strategy scores.
This report is instrumental in helping the stakeholders, such as predictive analytics vendors, system integrators, consultants, value-added resellers, and technology partners, to make business decisions on predictive analytics solution deployments.
The report covers the comprehensive study of key predictive analytics vendors, including Alpine Data Labs, Alteryx, Inc., Angoss Software, Birst, Inc., Fair Isaac Corporation (FICO), IBM Corporation, RapidMiner, SAS Institute, Tableau Software, and TIBCO Software.
To speak to our analyst for a discussion on the above findings, click Speak to Analyst
Table of Contents
1.1 About the Document
1.2 Market Definition
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
6.6 Tibco Software, Inc.
6.7 Alpine Data Labs
6.8 Fair Isaac Corporation (FICO)
7.1 MnM Dive Vendor Comparision Methodology
7.2 Quadrant Description
7.3 List of Abbreviations
7.4 Related Research
Growth opportunities and latent adjacency in Vendor Comparison in Predictive Analytics, 2016