CAT provides a range of Data Analytics solutions to assist our Clients across thevalue chain. Each of these Data Analytics solutions is customized to address theunique business requirements of our Clients.
	Data Acquisition and Cleansing
	We reduce waste by improving data quality and improve data value by acquiring and integrating internal/external data. It reduces your direct cost of data decay and maintenance, and reduces alternate costs of lost/misdirected client communication/targeting.
	Data Processing
	We reduce in-house low-level work and IT infrastructure costs, and improve efficiency and quality in the reporting process. Therefore, the information is turned into an actionable operational decision support and your Internal Research and Analysis resources can focus on strategic work.
	Data Modeling
	We produce new insights with existing/new data assets and flexible cutting-edge statistical and modeling expertise. As a result, you can keep a more important budget for vital evaluation of existing and potential business.
	Our Data Analytics capabilities cover a number of possible analyses, using different programming tools and software such as SAS, SPSS, Excel, SQL, Matlab and Siebel. The following is a sample of the techniques used for various types of analysis.
		Link Analysis Conjoint Analysis Survival Analysis  Decision Trees Clustering Logistic Regression Factor Analysis Multivariate, Linear, Ordinal and Multinomial Regression  Kohonen Maps Simulation Techniques Discriminant Analysis Vendor Performance Management Tool Sales and Retail Dashboards  Market Basket Analysis Econometric Forecasting Reporting and Analysis Optimising Cash and Accounts Payable Management Bayesian Analysis  Neural Networks Time Series Analysis Contact Search Tool Launch Performance Tracking Tool Cycle Research for Technical Analysis