Put Your Data to Work With Business Analytics
Today’s organizations are facing diverse issues and heightened global competition with stringent regulatory requirements. Customer acquisitions, retention and profitability are the key business concerns. Moreover, reduced margins, risk management, new products initiatives have put tremendous pressure on traditional decision making tools.
Business Analytics is the art and science of developing new insights and understanding business performance strictly based on data and statistical / predictive analysis methods. An organization’s competitive advantage increases with the degree of intelligence that it gains with its own data.
Analytics provides more than traditional Business Intelligence. Historical reporting generally constitutes “what has already happened”. On the other hand, analytics tries to analyze the historical information and predict “what might happen in the future”.Analytics delivers the true value of Intelligence to Business Intelligence.
Services and Solutions
Syntel’s Business Analytics solutions enable businesses to assess their analytical maturity and effectively utilize data to gain better insight and drive business planning based on statistical methods. Our experts have unique skills and expertise in deploying analytics services and assets that address specific, targeted analytical applications.
Syntel has developed its DEMAND methodology based on CRISP-DM (Cross Industry Standard Process for Data Mining) and extensive analytics deployment experience.
Our robust DEMAND methodology for business analytics includes five phases from Discovery through Deployment and Monitoring. We'll help you discover the power of business analytics and the value impact it can have on your business.
- Discover & Explore – Exercise to assess the analytical maturity, understand data sources and prepare the data for modeling. This takes 60-70% of the time.
- Modeling – Identify a suitable modeling algorithm, create, select, modify and determine the key variables for modeling.
- Assess Performance – Once a model is built, evaluate the reliability of findings. Estimate performance using model-test strategy.
- Notify Results – The model accuracy denotes the applicability of the model on a fresh set of data. This is an iterative process until the model is finalized.
- Deploy & Monitor – The finalized model is deployed in production and put to use in operation. Regular monitoring of model performance is conducted. If need be, the model is re-calibrated. The above process is further repeated.
service is one of the Syntel’s accelerators which helps you to understand the level of maturity within your organization. It’s a simple approach to identify your organizational strengths & weaknesses, and provides a roadmap to a mature data-driven culture 
Enhancing customer satisfaction through an open-source text analytics application.
| Banking / Financial Services |
Insurance |
Healthcare / Pharma |
Retail |
Manufacturing |
Telecom |
-Anti Money Laundering
-Campaign Management
-Credit Risk Management
-Credit Scoring
-Cross-Sell & Up-Sell
-Customer Profitability
-Customer Retention
-Customer Segmentation
-Fraud Management
|
-Campaign
Management
-Cross-Sell &
Up-Sell
-Customer
Retention
-Customer
Segmentation
-Fraud
Management
-Ratemaking |
-Case
Management
-Clinical Data
Management
-Drug Discovery
& Development
-Drug Safety
-Fraud
Management
-Health Plan Analytics |
-Customer
Insight
-Markdown
Optimization
-Promotion
Price
Optimization
-Regular Price
Optimization
-Revenue Optimization
-Size
Optimization
-Transaction
Insight |
-Demand Driven
Forecasting
-Inventory
Optimization
-Predictive
Asset
Maintenance
-Quality Life
Cycle Analysis
-Service Operations
Optimization
-Service Parts
Optimization
-Warranty
Analysis
-Warranty
Reserve
Forecasting
|
-Campaign
Management
-Cross-Sell &
Up-Sell
-Customer
Churn
-Customer
Profitability
-Customer Retention
-Customer
Segmentation
-Payment Risk
-Price Plan
Optimization
-Revenue
Assurance
|