Data Modeling Online Training IQ Online training facility offers Data Modeling online training by trainers who have expert knowledge in the Data Modeling and proven record of training hundreds of students. Our Data Modeling training is regarded as the best online training by our students and corporate clients. We are training partners for corporate clients like IBM. We train students from across all countries like USA, UK, Singapore, UAE, Australia, and India. Our Data Modeling training is your one stop solution to Learn, Practice and build career in this field at the comfort of your Home with flexible class schedules. IQ Training offers the Data Modeling Online Course in a true global setting. Course Contents: I.INTRODUCTION TO DATA MODELING 1. Data Modeling: An Overview Data Model Defined What Is a Data Model? Why Data Modeling? Who Performs Data Modeling? Conceptual Data Modeling Data Model Components Data Modeling Steps Data Model Quality Significance of Data Model Quality Data Model Characteristics ensuring Data Model Quality Data System Development Data System Development Life Cycle Roles and Responsibilities Modeling the Information Requirements Applying Agile Modeling Principles Data Modeling Approaches and Trends Data Modeling Approaches Modeling for Data Warehouse 1 Data Modeling Online Training www.iqonlinetraining.com
2. Methods, Techniques, and Symbols Data Modeling Approaches Semantic Modeling Relational Modeling Entity-Relationship Modeling Methods and Techniques II DATA MODELING FUNDAMENTALS 1. Anatomy of a Data Model Data Model Composition Models at Different Levels Conceptual Model: Review Procedure Conceptual Model: Identifying Components Creation of Models Entity Types Specialization Generalization Relationships Attributes Identifiers Review of the Model Diagram Logical Model: Overview Model Components Transformation Steps Relational Model Physical Model: Overview Model Components Transformation Steps 2. Entities in Detail Entity Types or Object Sets Comprehensive Definition Identifying Entity Types Generalization and Specialization Why Generalize or Specialize? Super types and Subtypes Generalization Hierarchy Recursive Structures Conceptual and Physical Modeling Time Dimension Categorization Entity Validation Checklist 2 Data Modeling Online Training www.iqonlinetraining.com
Completeness Correctness 3. Attributes and Identifiers in Detail Attributes Properties or Characteristics Attributes as Data Attribute Values Names and Descriptions Attribute Domains Definition of a Domain Domain Information Attribute Values and Domains Value Set Range Type Null Values Types of Attributes Single-Valued and Multivalued Attributes Simple and Composite Attributes Attributes with Stored and Derived Values Identifiers or Keys Need for Identifiers Definitions of Keys Relationships in Detail Relationships Associations Relationship: Two-Sided Relationship Sets Double Relationships Relationship Attributes Degree of Relationships Unary Relationship Binary Relationship Ternary Relationship Quaternary Relationship Structural Constraints Cardinality Constraint Participation Constraint Dependencies Entity Existence Relationship Types Identifying Relationship No identifying Relationship 3 Data Modeling Online Training www.iqonlinetraining.com
Maximum and Minimum Cardinalities Mandatory Conditions: Both Ends Optional Condition: One End Optional Condition: Other End Optional Conditions: Both Ends Special Cases Gerund Aggregation Access Pathways Design Issues Relationship or Entity Type? Ternary Relationship or Aggregation? Binary or N-ary Relationship? One-to-One Relationships One-to-Many Relationships Circular Structures Redundant Relationships Multiple Relationships Relationship Validation Checklist Completeness Correctness 4. Data Normalization Informal Design Forming Relations from Requirements Potential Problems Update Anomaly Deletion Anomaly Addition Anomaly Normalization Methodology Strengths of the Method Application of the Method Normalization Steps Fundamental Normal Forms First Normal Form Second Normal Form Third Normal Form Boyce-Codd Normal Form Higher Normal Forms Fourth Normal Form Fifth Normal Form Domain-Key Normal Form Normalization Summary 4 Data Modeling Online Training www.iqonlinetraining.com
Review of the Steps Normalization as Verification 5. Modeling for Data warehouse Decision-Support Systems Need for Strategic Information History of Decision-Support Systems Operational Versus Informational Systems System Types and Modeling Methods Data Warehouse Data Warehouse Defined Major Components Data Warehousing Applications Modeling: Special Requirements Dimensional Modeling Dimensional Modeling Basics STAR Schema Snowflake Schema Families of STARS Transition to Logical Model OLAP Systems Features and Functions of OLAP Dimensional Analysis Hypercube OLAP Implementation Approaches Data Modeling for OLAP Data Mining Systems Basic Concepts Data Mining Techniques Data Preparation and Modeling Data Preprocessing Data Modeling 5 Data Modeling Online Training www.iqonlinetraining.com