This case study is an assignment I submitted and hence sharing with readers.
ABC Auto Insurance is under immense pressure from competitors due to reduce Auto Insurance prices and high risk underwriting. ABC Company has huge data resources from business operation, however, it is difficult to get required information in timely manner. ABC Company has to make major steps for informed decision making and important data analysis.
ABC Company has an OLTP database which keeps records on motor vehicle insurance information. This database contains detailed information in respect of drivers, vehicle and claim information.
Current database model has been designed for fast data entry and is sufficient for individual client’s specific information as well as fast transaction processing. Company critically needs to make comprehensive analysis like identification of contracts with a high loss ratio and low overall customer value.
Appropriate actions needed to be taken with high risk customers, such as premium adjustment, loss prevention measures and in some cases contract cancellations and reduce gross claim expenditures.
By making evidenced based management and informed decision, company will focus on profitable customers by lowering their premiums and overcoming competitive pressure. It will help company make better risk management and overall profitability for the company. ABC Company is in urgent need to utilize the existing data resources efficiently for better risk management and obtain competitive advantage in Auto Insurance Industry.
ABC Company has decided to implement a Data Warehouse to leverage its data resources. ABC Company needs to reorganize the existing process of information delivery and to establish one single, unified and integrated data warehouse. A data warehouse is an integrated subject oriented, time-variant, non-volatile database that provides support for decision making.
In order to support decision making ABC Company decided to reorganize the data into Star Schema in Data warehouse. In effect, the star schema creates near equivalent of multidimensional database schema from the existing OLTP relational database . It will help in advance data analysis for Risk management and overcoming competitive pressure.
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Structure of Star Schema
Star schema yield an easily implemented model for multidimensional data analysis while still preserving the relational structure on which the operation database is built.  The basic star schema has four components: facts, dimensions, attributes and attributes hierarchies. The STAR schema would most likely be a read-only database due to the widespread redundancy introduced into the model. 
ABC Company has a factual data in Claim Information such as date, location, type of accident, cause of accident, liability, recovery cost. Fact tables contain the quantitative data or factual data about a business. This information is numerical, additive measurements and can consist of many columns and millions or billions of rows.
Claim Information facts can be analyzed by dimensions such as Driver, Location, Time, and Automotive. Dimension tables are usually smaller and hold descriptive data that reflects the dimensions.
For example Driver name, Driver ID, gender, age group, race, and other attributes. Some of these attributes might relate to each other hierarchically.
Provide top down data Aggregation, Drill down or roll up data analysis. For example in time dimension there are Attribute hierarchies such as day, week, month, quarter, and year. When decision maker want to see company yearly claim information, then they are using year hierarchy level, they can further drill down to quarter level sales quantity, as per there needs. Same as in Location dimension is data can be analyzed by Country, Region, Province City and town.
Benefits of Data warehouse to ABC Company
By organizing the ABC Company data around star scheme company can analyze information like what customers are high risk and what group of customers is profitable. What cities have more accidents ratios and what time of the year accident happens? What habit of drivers is may be considered high risk? What vehicles are considered low risk and so on?
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In addition to the internal information some external information like Auto Industry statistics can also be integrated into data warehouse.
By having answers to ad-hoc queries and in depth data analysis, ABC Company will be able to manage customer relations, smartly overcoming competitive pressure and most important of all is significantly improved risk management.
Data Warehouse will enable company have the business Intelligence for making strategic decision for Risk management and keep the company ahead of the competition and possibly diversify into new auto insurance products. 
1- Data model overview
2- The Benefits of Data Warehousing for Insurance Company Wolfgang Hofbauer, Mannheimer AG Holding, Mannheim, Germany
3- Database Systems By Peter Rob, Carlos Coronel, Keeley Crockett – Published by Thomson Learning; International Ed edition (12 Mar 2008)
4- Oracle Data Warehouse Tips by Burleson Consulting.
5- Class notes and research with Insurance companies.