CertifiedBasics of Data Modeling
What is a Data Modeling?
Perquisites for becoming a Data Modeler
Data Modeler Duties and Responsibilities.
Data Modeler vs Governance
Who Needs Data Modeling.
Essence of Data Modeling in an Organization.
Data Model Overall Process
Understanding the Business Process
Identify the Grain
Identify the Dimensions
Identify the Facts
Notations:
IDEFIX Methodology
IE Methodology
Schema Types
Star Schema
Snow flake Schema
Data Modeling Types
Conceptual Data Models
Logical Data Models
Physical Data Models
Difference between Logical Data Model and Physical Data Model.
Relational Data Models
Dimensional Data Models
Enterprise Data Model
Data Modeling Development Life Cycle.
Dimension Types
Junk Dimension
Confirmed Dimension
Degenerate Dimension
Role Playing Dimension
Type 0 Dimension
Type 1 Dimension
Type 2 (Slowly Changing Dimensions)
Type 3 Dimension
Type 4 Dimension
Type 5 Dimension
Type 6 Dimension
Type 7 Dimension
Fact Types:
Additive Facts
Non Additive Facts
Semi Additive Facts
Fact Table Types
Transaction Fact Tables
Periodic Fact Tables
Accumulation Fact Tables
Relationships
One to one Relationship
One to Many Relationship
Many to Many Relationship
Resolving Many to Many Relationship
Self-Relational Integrity Relationship
Normalization Process - 1NF, 2NF, 3NF
Super type and subtype
Exclusive subtypes
Inclusive Subtypes
Identifying and Non-Identifying.( Mandatory , Non Mandatory)
Weak Entities
Strong Entities
Associative Entities
Transaction Tables
Classification Table
Data Modeling Standards
Naming Standards of Objects( Tables, Attributes, Data Types)
Abbreviating Column Names
Abbreviation Table Names
Description of Column
Description of Table
Consistency in Column Names
Dealing with Hierarchy Information
Parent and Child Hierarchy
Balanced Hierarchy
Unbalanced Hierarchy
Ragged Hierarchy
Static Hierarchy
Dynamic Hierarchy
Data modeling more info
Forward Engineering
Reverse Engineering
Subject Areas
Comparison of Data Models
Mapping Documents.
Versioning of Data Models
Data Model Reports:
Table Level Reports
Model Level Reports
Subject area Level Reports
XML, PDF, XLS, CSV reports.
Erwin Latest Features
Annotation
Bulk Editor
Design Layers (Erwin)
Macros (Erwin)
Source to Target mapping in erwin (Erwin)
Subject Area (Erwin)
Other Important areas to cover
Data Quality & Data Governance
Data lineage
DW Architecture (Inmon /Kimbal)
Kimbal BUS Matrix
Metadata management
Business process Modelling
Data Flow Diagram
Data Dictionary
Performance tuning
Source document collection
ETL/ELT/ Data Ingestion Strategy
Business Requirements understanding/ Analysis
SQL / PL-SQL and
Query Tuning
Data Security and access
Certified
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