1. Data modeling. Presentation by – Anupama Vudaru, Phani Kondapalli Content by – Prathibha Madineni, Subrahmanyam Kolluri October 2010

2. Preface Agenda – Basics of Data Modeling, Insurance industry and Erwin Duration and timings – 4 days x 2 hrs Expectations – In-class, hands on and post session work Course contents – Divided into slides, videos and print outs Legends used – Post-session work – Attendees are expected to do hands-on home work assigned for the day

3. Contents Day 1 A.Data Modeling overview B.Data Modeling development life cycle C.Components of Data Modeling D.Data Modeling notations and design standards E.Case study – CDM overview Day 2 A.Conceptual data model B.Types of Data modeling C.Various tools available D.Developing CDM using Erwin E.Case study – LDM overview Day 3 A.Logical data model B.Developing LDM using Erwin C.Meta Data preservation for Design Considerations D.Dimensional Data Modeling E.Case study – PDM overview Day 4 A.Physical data model B.Logical Data Model vs Physical Data Model C.Developing PDM using Erwin D.Advanced Features of Erwin

4. A.Conceptual data model B.Types of Data modeling C.Various tools available D.Developing CDM using Erwin E.Case study – LDM overview Day 2

5. A. Conceptual Data Modeling First step in constructing a data model in top- down approach A clear and accurate visual representation of the business of an organization Visualizes the overall structure of the database and provides high-level information about the subject areas or data structures of an organization Discusses main subject areas of an organization and then all the major components of each subject area Comprises of subjects and processes Dependency and inter dependency of subjects and their components is identified Functional and executive teams project their ideas for building a sound conceptual data model Example of Conceptual Data Model

6. B. Types of Data Modeling Relational Data Modeling Greater variations to access data Multiple selection criteria to obtain data Less aligned to how end user sees the data More flexibility to address business questions Content of table(non-key attributes) driven by relationship to key Less space is required due to reduced redundancy Data is separated into more entities Detailed level of transactional data Data is normalized Typically employed in data warehouse and ODS Data is atomized, current, process oriented - processing one record at a time, suited for highly structured and repetitive processing Dimensional Data Modeling Fewer variations to access data Fewer selection criteria(Dimensions + Facts) More aligned to how end user sees the data Less flexibility Content of table driven more by business requirements, performance and usability More redundancy(around dimensions) allowed to reduce query times Data is placed in fewer entities Summary of bulky transactional data(aggregates and measures) Data is de-normalized and used in data warehouse and data mart Typically employed in data marts Data is summarized, historical, subject oriented - processing many records at a time, suited for highly unstructured analytical processing 1. Types

7. B. Types of Data Modeling 2. Data redundancy Normalization The goal is to reduce and even eliminate data redundancy Easier to map objects to data schema More performance cost Data is spread across multiple tables Techniques to normalize: 1 NF 2 NF 3 NF De-normalization The goal is to optimize the performance of the database Better data accessibility Less performance cost Data is spread across fewer tables Techniques to de-normalize: Identify grains and levels in hierarchies Identify facts and dimensions Add duplicate keys /attributes to tables

8. B. Types of Data Modeling 3. Examples Dimensional Relational

9. Popular tools available for data modeling: Erwin by Computer Associates ER/Studio by Embarcadero Technologies Enterprise Architect by Sparx Toad Data Modeler by Quest Software Power Designer by Sybase Corporation Oracle Designer by Oracle Corporation Xcase by RESolution LTD Rational rose by IBM Corporation Visio and SQL Diagrams by Microsoft SmartDraw by SmartDraw.com Corporate Q1: Name the product and the vendor? A: SmartDraw suite from SmartDraw.com company. Q2: It is a popular logo. Does this vendor sell data modeling product? Name it. A: Yes. TOAD Data Modeler. Q3: Enterprise Architect is a data modeling tool. Who is the vendor? A: Sparx. Q4: Resolution XCASE – is it a product or a vendor? A: Resolution is vendor and XCASE is the product. Q5: Identify the logo – the product and vendor? A: ER/Studio by Embarcadero Technologies. Q6: Who created Erwin? A: Logic Works. Platinum Technologies acquired it. CA, in turn, acquired it. Q7: Erwin is a CASE tool. What does CASE stand for? A: Computer Aided Software Engineering. C. Various tools available

10. D. Developing CDM using Erwin 1. Introduction to Erwin Key Components of the CA ERwin Modeling Family Data modeling and database design Collaborative modeling Data profiling and multi-source data analysis Metadata integration for applications Data model validation Process and data integration CA ERwin Data Modeler data modeling and database design features Complete Compare Database Forward Engineering And Design Generation Database Reverse Engineering Reusable Design Standards Reporting And Publication Metadata Exchange And Data Model Reuse Multiple Model Types Logical Physical Logical/Physical 01. Intro to Erwin

11. D. Developing CDM using Erwin 2. Components of Erwin Erwin provides a workspace with a Model Explorer Menu structure Dockable toolbars Drawing objects Drawing window Model Explorer – Provides a hierarchical text-based view of the data model that is displayed in the Diagram Window. Menu Structure – Context based menu which behaves different for different model type. Menu items seen can differ based upon the license and options purchased. Dockable Toolbars – Toolbars contain task buttons, which can be used as shortcuts to quickly perform common ERwin tasks. Place the pointer on toolbar icon for tool tip. Drawing Objects – Easily accessible set of objects that can be used to draw the components of Data Modeling. Diagram Window – Displays a graphical view of the data model. 02. Toolbars and Workspace panes

12. D. Developing CDM using Erwin 3. Subject areas and Stored displays Subject Areas By default, every ERwin data model has a Main Subject Area, which includes all of the objects in the model. You can create other subject areas to divide the model into smaller manageable parts. You can create a new subject area and add members to it by dragging entities or tables from the Main Subject Area into the new subject area. Note: Keep in mind, that subject area members just reference the objects in the Main Subject Area, so changes automatically apply to an object in every subject area in which it is a member. Stored Displays By default, every ERwin data model has one Stored Display, which is named “Display 1”. You can rename “Display 1” and create other Stored Displays to customize the view of your data model. Note: In a Logical/Physical model, you can easily toggle between the logical model and the physical model by selecting the model type from the option list on the ERwin toolbar. 03. Subject areas

13. Understanding the Requirements About JFI John Life is the largest life insurer in the Dream valley nation in the northern hemisphere, with more than $1 trillion of life insurance transactions. A leader in savings and retirement products and services for individuals, small business, and large institutions, John Life serves 9 of the largest Fortune 10 companies. Also, John Life acts as reinsurer and retrocessionaire. Case study John Life Inc. is involved into providing various life insurance products, such as Term life insurance and Whole life insurance. It sells the products through various channels like campaigns, internet, agents, agencies, etc. John Life has an obligation of repaying an agent’s efforts with 10% of the premium amount for each contract. The insurance firm invests the obtained funds in assets such as mortgage-backed assets, equity securities and fixed income securities. Also, the insurance firm sends annual performance reports to all the parties which involve in the firm’s activities. It has an obligation to send annual regulatory reports to the federal government and state and other insurance bodies. Mr. Bond is a celebrity in Dream valley nation. Owing to his risky life due to his occupation in movies, he decides to insure himself with $ 20 million as sum assured. As per the formal process of John life, Bond gets into an agreement for term life insurance with the firm. Underwriters at John Life have calculated the risk involved and the premium amount is fixed $ 50000 every quarter for a period of 4 years term. Insurance agent – agent Triple X is dealing this contract by acting as an intermediary. Immediately after Bond opens an account with the insurance company, it identifies the efforts of agent Triple X and pays 5000$ to the agent. John Life understands that this policy might demand heavy claims upon Bond’s death in the term. So, John Life decides to get into a reinsurance treaty with Harrison Re, thus mitigating any possible risk. D. Developing CDM using Erwin 4. Case study 04. CDM