Online Data Modeling Training Syllabus

Online Advanced Data Modeling Training Course on

OLTP, Data Warehouse, Datamart, Dimensional and Snow Flake Data Modeling and Normalization. 

Data Modeling Course Syllabus & Feedback:

https://youtu.be/Pk341pqGW4c

Course Description:

This online training course is Job focused and 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.

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

Course Information:

Start Date:
  • We offer Training at your convenient time frames. Please call us at 91-9080157239 for more details!
  • Course Name: Advanced Data Modeling Training through GotoMeeting.
  • Mode of Payment: To USA Savings Account or India Savings Account or through www.Xoom.com
  • Total no. of theoretical/Practical classes: 20 Hours (Will be extended if required!)
  • Mode of Teaching: Online through GoToMeeting
  • Instructor: Neelesh (US Employee) & Antony (Trainer of LearnDataModeling.com)
  • Office: USA and Chennai
Course Requirements:
  • Internet connection
  • Lap Top or Desk Top
Training Certificates:
  • Will be provided.

Case Study:

  • How to capture Driver, Rider and Ride Information in OLTP/OLAP Data Model for UBER/OLA?
  • How to create OLTP/OLAP/SaaS Data Model for Microsoft Office 365 or similar Software Product?
  • How to create Training Center Data Model for Online/Classroom and Recorded Video Sales?
  • How to create Clinic OLTP/OLAP Data Model from a Receipt?
  • How to create OLTP/OLAP Data Model for Point of Sales (POS) transactions?

Case Study – Exercise:

  • How to create OLTP/OLAP Data Model for 1003 URLA Form?
  • How to create OLTP/OLAP Data Model for Banking/Debit Card Transactions?

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

Part 12:  Introduction to NoSQL Data Modeling

  • Explanation of JSON
  • Explanation of Document Database

Part 13:  Introduction to Big Data:

  • HDFS
  • MapReduce
  • Hadoop
  • Hive
  • Pig Script
  • Yarn
  • ZooKeeper
  • Tez
  • Spark
  • Storm
  • MongoDB
  • HBase
  • MySQL
  • Cassandra

Data Modeling Demo Videos:

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
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