Predictive Analytics consists of techniques mainly from statistics and data mining that analysis that present and past data to make predictions about future events. As the competition is increasing in the global marketplace the companies are facing major challenges in retaining the customers and increasing the market share. Analytics helps clients to provide insights that helps in making decision making process.
Here are some of applications for Predictive Analytics:
• Response Modelling
• Churn Modelling
• Market Basket Analysis
• Customer Segmentation
• Credit Default Modelling
• Sales Forecasting
R is a open source programming language and provides environment for data analysis and data visualization. It has emerged as one of popular programming language used by data analysts. Revolution R Enterprise brings performance and power, greater productivity and enterprise readiness to R for data analysts at work – for a fraction of the cost of legacy commercial statistical software. RevoScaleR is package from Revolution Analytics which is scalable, fast (multicore), and provides extensible data analysis with large data in sets R supporting distributed computing using Microsoft Windows HPC Server 2008 clusters. For enterprises who want to deploy their R-based business solutions to multiple users, RevoDeployR is a Web Services framework that can integrate dynamic R-based computations into Web applications. R has also many packages for analyzing unstructured data, accessing Google API etc.
Here are some of the advantages of Revolution R Enterprise:
• Built in extensibility via custom functions and packages
• Data Step to pre-process multi-gigabyte data sets for analysis
• Custom data visualization
• Supports in-memory database processing with Netezza
• Hadoop connectivity
• Distributed processing to support use of multi-node clusters
• Web Services Integration into multi-user applications via RESTful API
• Developers IDE with intelligent source code editing /management and step debugging
• Access to 3000+ open source packages for data access, statistics and visualization
R can be used for doing social media analytics. Using various APIs provided by social networking sites we can collect the data from social networks like Facebook, Twitter and Google +. Pre-processing of the collected data is done in packages like XML, RCurl etc. After pre-processing of data various charts like wordcloud, sentiment over time, comments by type etc. can be plotted using packages like ggplot2 etc. All R charts can be embedded in Jaspersoft's Ireports. We help you to decide which data to analyze and how.