Data Modeling Training Videos For Sale

Data Modeling Training Videos on

OLTP, Data Warehouse, Datamart, Dimensional and Snow Flake Data Modeling and Normalization Plus 8 Use Cases

Data Modeling Course Syllabus & Feedback:

https://youtu.be/Pk341pqGW4c

Data Modeling Course Feedback & Testimonials:

Training Testimonials

Video Course Details:

This training video explains in detail about database, data warehouse, data modeling concepts, data modeling types and how these are used in OLTP environments and Data warehouse / Datamart Environments using Erwin. Plus use cases on Mortgage, Banking, Ola etc.

To get more information about this, send an email to AntonysTrainingandSolution@gmail.com or call us @ 91-9080157239.

Course Syllabus

Part 1 – Career Path of a Data Modeler

• What is a Data Modeling?
• Explanation of Data Modeler duties in brief
• Certifications in Data Modeling
• Career Path of a Data Modeler
• Salary of a Data Modeler

Part 2 – Data Modeling Concepts

• Who is a data modeler?
• What are the other alternative titles for a Data Modeler?
• What are the duties and responsibilities of a Data Modeler?
• What is the difference between duty and responsibility?
• What is a Data Model?
• Who needs Data Modeling?
• Different Data Modeling Tools
• IDEF1X and IE Methodology

Part 3 – Data Modeling Types

• Logical Data Model
• Physical Data Model
• Dimensional Data Model
• Conceptual Data Model
• Enterprise Data Model
• Data Modeling Development Life Cycle

Part 4 – Data Model Standards

• Naming standards of objects
• Abbreviating column names
• Consistency in Column Names
• Why it is important

Part 5 – Database Explanation from Data Modeling Perspective

• Main object: Table, Column, Datatype
• Constraints: NULL, NOT NULL, Primary Key, Unique, Check, Default Value
• Other objects: Database, Schema, Tablespace, Segment, Extent, Privileges, Index, View, Synonym
• DDL Statements: CREATE, ALTER, DROP
• DML Statements: INSERT, UPDATE, DELETE

Part 6– How to create a logical Data Model

• Entity, Attribute, Primary Key, Alternate Key, Inversion Key Entry, Rule, Relationship, Definition, Index, Unique Index

Part 7– Relationships

• Identifying, Non-Identifying, Many to Many
• Cardinality
• One to One Relationship
• One to many relationship
• Many to many relationship
• Whether Zero option is required or not
• Resolving Many to Many Relationship
• Self-Referential Integrity Relationship
• Normalization process – 1NF, 2NF, 3NF
• Supertypes and Subtypes

Part 8 – How to create a Physical data model:

• Table, Column
• Primary Key Constraint, Unique Constraint Check Constraint, Foreign Key Constraint, Comment
• Default Value
• Unique Index, Non-Unique Index,
• Difference between a logical data model and Physical Data Model

Part 9 – Physical Data Model, Database & Scripts:

• What is Forward Engineering?
• How to generate scripts from a data model and share it with DBA?
• What is Reverse Engineering?
• How to create a data model from a database?
• How to create a data model from a script?
• How to compare data models?
• How to compare database and a data model?
• What is subject area?
• Why do we need so many subject areas?
• How to implement Physical data model in a database?
• How to generate SQL Code?
• How to implement it in Database?

Part 10 – Concepts: Dimensional Data Modeling, Data Warehouse and Data Mart

• What is a Lookup?
• How to maintain data in Lookups?
• What is a Data Warehouse?
• What is a Data Mart?
• How to design Data Warehouse & Data Mart?
• Difference Between OLAP Modeling & OLTP Modeling
• How to resolve the problems found in OLTP & OLAP Modeling?
• How to design the Dimension & the Fact Tables?
• What is a Grain Statement & Granularity?
• Designing using Inmon’s or Kimball’s approach.
• What is Snow Flake Modeling?
• What is Star Schema Modeling?
• Slowly Changing Dimensions – Type I, Type II & Type III
• What is a Degenerate Dimension?
• What is Causal Dimension?
• What is Junk Dimension?
• What is Outrigger Dimension?
• What is Dimensional Data Modeling?
• How to create a data model for Data Warehouse and Data Mart?
• What is ETL?
• Things to learn for mapping/Data mapping
• What is Factless Fact?
• What is Accumulation Fact?
• What is Snapshot Fact?
• What are Additive & Non-Additive and Semi-Additive Measures?
• Importance of Surrogate Key

Part 11 – Repository, Meta Data and Maintenance of the Data Model

• What is a Repository?
• What is Meta Data?
• How to maintain the data model?
• How to work in a multi-user environment

Interview Question & Answer Videos:

• Data Modeling Interview Question & Answer Videos

Data Modeling Demo Videos:

• 01 Data Modeling Development Life Cycle
• 02 Data Warehouse Training – Table & PK
• 03 Simple Select Statement and Alter Statements
• 04 Data Warehouse Training ETL Tools
• 05 Data Warehouse Training Normalization
• 06 Data Warehouse Training – Cardinality and Optionality
• 07 Sale – OLTP AND Data Modeling Training Videos with Erwin

Popular/Top Data Modeling Tools in the Market:

• Erwin
• E/R Studio
• SAP PowerDesigner
• Toad Data Modeler
• Oracle SQL Developer Data Modeler
• MySQL Workbench
• IBM InfoSphere Data Architect