Category: Data Modeling Videos

A step-by-step Data Modeling Video Tutorials to learn/design: OLTP/Dimensional Data Modeling with Data Model Deliverable.

Following is the Syllabus for the Data modeling Videos:

1 – Introduction about Data Model

• What is a Data Model?
• What is a Logical Data Model?
• What is a Physical Data Model?
• What is the difference between Logical and Physical Data Model?
• Salary of a Data Modeler
• What are the other titles for Data Modeler?
• Duties and Responsibilities of a Data Modeler
• Data Modeling Development Life Cycle
• Data Modeler Deliverable

2 – Conceptual, Logical, Physical Data Model

• Difference between a Domain and a Datatype
• What is ER Diagram (Entity Relationship Diagram)?
• What is an Entity? And Entity Naming Convention Rule.
• What is an Attribute?
• What must be included in Conceptual Data Model?
• What must be included in Logical Data Model?
• What must be included in Physical Data Model?
• How DDL scripts looks like?

3 – Oracle Database 12. 1..0.2.0

• How to connect to Oracle Database

Examples in Oracle:

• How to create table, drop table and alter table
• How to insert records into table
• What is Tab and commands like Describe, Clear Screen, Commit and To-Date Function
• How to create primary key, composite primary key, check constraint, not null constraint, unique constraint, foreign keys, composite foreign keys?

4 – Oracle database 12.1.0.2.0

• Insert, Update, Delete Statement
• Select Statements
• NULL, NOT NULL
• Aggregate Functions (Group By, Having, Count)
• Where Clause, Sub Query
• Operators (IN, NOT IN, >, <) etc.
• Boolean Operators AND, OR NOT
• Commit, Rollback
• Create Index, Drop Index
• How to use System Tables: All_Ind_Columns, User_Constaints, User_Cons_Columns
• and much more

5 – Data Modeling Concepts

• What is a Data Model?
• Entity Relationship Dagram
• Logical Data Model
• Identifying Entities
• Datatype
• Basic Attribute, Deriving Attribute, Multivalued Attribute

Keys:

• “Key, Unique Key, Identifier, Super Key, Trivial Super Key, Candidate Key,
• Primary Key, Natural Key (Business Key, Domain Key) Alternate Key, Foreign Key, Surrogate Key”
• What are the interview questions related to keys?
• Examples to understand keys

6 – Data Modeling Relationship

• Cardinality
• Notation
• Exactly One, Zero or one, One or more, Zero/One/More, More than one

Relationship Cardinality:

• One to One, One to Many, Many to Many
• Optionality
• Relationship Cardinality and Optionality Notations
• How to read the relationships?
• Not Null Constraint

7 – Relationships in an OLTP Data Model using Erwin

• Introduction by the trainer and students
• Introduction about data model
• Use Case: H1B Applicant Data Model
• Identifying lookup table and transaction tables
• Creation of data model using Erwin
• creation of entity and primary keys in Erwin
• Creating conceptual data model
• Identifying null and not null
• Identifying cardinality
• Identifying one to one, one to zero/one/many, one to one/many
• Non identifying relationship

8 – Relationships in a Data Model using Erwin

• Many to Many relationship
• How to create a Conceptual Data Model
• Identifying relationship
• How to handle composite primary keys in a data model
• Why data analysis is important?
• Self-Referential Integrity Relationship
• Cardinality
• How to create a Logical Data Model
• How to create a Lookup Script?
• How to do forward engineering (schema generation)?

9 – SuperType, SubType

• Generalization with subjoin subtypes (Mutually exclusive)
• Attribute Inheritance
• Disjoint (Exclusive) Constraint
• Overlapping (Inclusive) Constraint
• Participation (Completeness Constraint)
• Specialization (Top Down Approach)
• Generalization (Physical Data Model)
• Super Type Implementation (Single Table)
• Sub Type Implementation
• When we should use supertype implementation?
• When we should use subtype implementation?

10 – Normalization Concepts

Business Process: What happens in a clinic with doctors patients visiting fee and medicines provided?

• Normalization Intro
• What is Normalization? Why Normalization is required?
• What is redundancy?
• Insert, Update, Delete Anomaly

Data Analysis of a clinic (clinic, doctor, patient, fees and medicines provided) – Case Study

• Functional Dependency
• 1NF, 2NF, 3NF

11 – Normalization – Data Analysis of Student data (student, course, grade, instructor)-

Business Process: What happens in student, course, instructor relationship?

• Create tables in 1 NF, 2NF, 3NF with the business rule “1 course can be taught by only one instructor”
• How to modify the data model when business rules change “1 course can be taught by more than one instructor”

Normalization – Small Retail Sales Data – 1NF, 2NF, 3NF

Business Process: How to analyze retail sales data

• Data Analysis of a small Retail Sales Data which consists of order, payment, shipment, federal tax, state tax, billing, items, items ordered, item name, total price, ordered quantity and how to handle multiple payment for an order

12 – UBER-OLA OLTP Data Model – Sample Case Study

• Business Process: How to store Rider Information and how to query the data

OLTP:

• How to build conceptual data model?
• How to build source schema (OLTP)?
• How to build target schema (Dimensional)?
• How to aggregate the data on daily basis and monthly basis (olap analysis)?
• How to calculate the daily trip cost?
• How to find out the drivers who cancelled the trip?
• How much money driver made?
• How to run different queries on top of this data model?
• Uber carpool scenario

Business Process: How to capture Training Center Employee/Student/Course Information/fees/training session

• How to capture the products that are explained?
• How to capture the training videos that are sold?
• how to implement identifying, non-identifying relationships?
• How to implement super type and sub type?

14 – Cloud OLTP Data Model – Sample Case Study

Business Process: How to store the online sales for a product? – Microsoft Office 365 as example from Web browser Application

• Explanation of office 365 application
• Explanation of table creation
• How to capture users, plans, option and subscription

15 – How to create a Staffing OLTP Data Model? – Sample Case Study

Business Process: How to hire a candidate.

16 – US Banking OLTP Data Model – Sample Case Study

Business Process: How to store financial and nonfinancial transactions for a Checking Account?

17 – US Mortgage OLTP Data Model

• Business Process – How to create an OLTP Data Model for US Mortgage URLA 1003 Application Form?

18 – Dimensional Data Modeling:

Concepts:

• What is Business Intelligence?
• What is Data Warehouse?
• What is Data Mart?
• What is ETL Process?
• Difference between OLTP and Dimensional
• What is Inman’s Approach?
• What is Kimball’s Approach?
• What is Dependent Data Mart? And What is an Independent Data Mart?
• What is Source Schema and What is Target Schema?
• How to design the Data Mart?
• What is Star Schema?
• What is Snowflake Schema?
• What is Business Process?
• What is a grain statement and what is the lowest level of Granularity?
• What is a Dimension?
• What is a Degenerate Dimension?
• What is a Causal Dimension?
• What is Junk Dimension?
• What is Outrigger Dimension?
• What is Slowly Changing Dimension Type1, Type2, and Type3?
• What is a Fact or a Measure?
• What is Additive Fact, Semi Additive fact and Non-Additive Fact?
• What is a Fact Table?
• What is Fact less Fact Table?
• What is Transaction Fact?
• What is Aggregate Fact?
• What is Accumulation Fact?
• What is a Periodic Fact?
• What is a surrogate key?
• What is the specialty of Date Key as a surrogate column?
• How to avoid NULL VALUES in the primary keys of a Fact Table?

19 – Dimensional Data Models – Case Study:

• Point of Sales Data Model – How to design the star schema?
• US Mortgage URLA 1003 Data Model
• Retail Bank Data Model– How to store ATM Transactions?
• OLA/Uber Data Model – How to store ride information?
• Cloud Data Model – How to store products sold on cloud environment
• Banking Data Model: How to store Daily and Monthly Data?

20 – Fundamentals:

• How to use Erwin Data Modeling Tool, Oracle SQL Data Modeler, TOAD Data Modeler, SAP Power Designer.