This Data Modelling training will help you learn how to design a relational data model, dimensional model, incorporate entities from a decomposed JSON document, NoSQL data stores, and more. Also, you’ll understand how Data Modelling determines and interprets data from experts through step-by-step methods and examples. By the end of this certification course, you will have a firm understanding of what a data model is, data model types, how to apply normalization, how to create both a dimensional and relational data model, and much more.
Course content
Basics of Data Modelling
- What is a Data Modelling?
- Perquisites for becoming a Data Modeler
- Data Modeler Duties and Responsibilities.
- Data Modeler vs Governance
- Who Needs Data Modelling.
- Essence of Data Modelling 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
- Snowflake Schema
Data Modelling 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 Modelling 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 Modelling 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 modelling 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.
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Course Prerequisites
- There are no prerequisites for this course. Anyone who wants to learn Data Modelling techniques can join the course
Who can attend
The Data Modelling course is designed for the following professionals:
- Database Modeler
- Database Administrators
- Data Scientists and Analysts
- ETL and BI Developers
- Analytics Managers
- Anyone who is looking to build a career in Data Warehousing
Number of Hours: 40hrs
Certification
CBDM: Certified Business Data ModellerKey features
- One to One Training
- Online Training
- Fastrack & Normal Track
- Resume Modification
- Mock Interviews
- Video Tutorials
- Materials
- Real Time Projects
- Virtual Live Experience
- Preparing for Certification
FAQs
DASVM Technologies offers 300+ IT training courses with 10+ years of Experienced Expert level Trainers.
- One to One Training
- Online Training
- Fastrack & Normal Track
- Resume Modification
- Mock Interviews
- Video Tutorials
- Materials
- Real Time Projects
- Materials
- Preparing for Certification
Call now: +91-99003 49889 and know the exciting offers available for you!
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