PREDICTIVE ANALYTICSCODY CARLSON & JAGDEEP SINGH

WHAT IS PREDICTIVE ANALYTICS?

• Predictive analytics is the branch of the advanced analytics which is used to make predictions about unknown future events. • Predictive analytics uses many techniques from data mining,

statistics, modeling, machine learning, and artificial intelligence to analyze current data to make predictions about future.

ANALYTICS TECHNIQUES

• Data Mining• Data Analysis• Statistics• Deployment

DATA MINING

• You can use data mining to automatically determine significant patterns and hidden associations from large amounts of data. Data mining provides you with insights and correlations that had formerly gone unrecognized or been ignored because it had not been considered possible to analyze them.

DATA MINING CASE/EXAMPLE

• For example, one Midwest grocery chain used the data mining capacity of Oracle software to analyze local buying patterns. They discovered that when men bought diapers on Thursdays and Saturdays, they also tended to buy beer. Further analysis showed that these shoppers typically did their weekly grocery shopping on Saturdays. On Thursdays, however, they only bought a few items. The retailer concluded that they purchased the beer to have it available for the upcoming weekend. The grocery chain could use this newly discovered information in various ways to increase revenue. For example, they could move the beer display closer to the diaper display. And, they could make sure beer and diapers were sold at full price on Thursdays.

DATA AND TEXT MINING PERSPECTIVE

Data Mining• Subset of Business Intelligence • Data used for analyzing patterns to predict future behavior Text Data• Big Data is the future• Combining abundant amounts of plain-language that is digitized

to find useful information that has been hiding

A FEW PREDICTIVE ANALYTICAL PROGRAMS

IBM PREDICTIVE ANALYTICS • Designed to bring predictive intelligence to make decisions • Algorithms and techniques used such as text analytics, entity

analytics and optimization• Data collected analyzed, reported, and deployment

RAPIDMINER

• Business analytics workbench incorporating data mining, text mining, to predict behavior• Algorithms and R scripts used • Machine Learning procedures

MACHINE LEARNING?

Ex) Web searching on Amazon; Prediction of equipment failures

• Algorithm to understand the user to make predictions for the future• Reproduce known patterns and knowledge

MACHINE LEARNING METHODS

Unsupervised Learning- Data that has no historical label, and best for transactional data

Semi-supervised learning- Labeled and unlabeled data for training - More of unlabeled data since it is less expensive

Reinforcement Learning- Algorithm learns through trial and error- Through the data select with highest integrity

PROGRAMMING

• R programming language written for statisticians • Extended to do data modeling, data mining, and predictive

analysis• Faster results• R is open-source and has code examples• IDE RStudio

SOURCES

• http://www.predictiveanalyticstoday.com/what-is-predictive-analytics/ • www.help.sap.com • https://en.wikipedia.org/wiki/Data_analysis• http://www.sas.com/en_id/insights/analytics/machine-learning.html• http://www.predictiveanalyticstoday.com/top-predictive-analytics-soft

ware/• http://business.time.com/2012/03/20/why-text-mining-may-be-the-ne

xt-big-thing/• http://infospace.ischool.syr.edu/2013/04/23/what-is-text-mining/