Data Modelling Training & Certification Course Online

1. 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, 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 1Data Modeling Online Training | www.iqonlinetraining.com

2. 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 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 2Data Modeling Online Training | www.iqonlinetraining.com

3. 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? Supertypes and Subtypes Generalization Hierarchy Recursive Structures Conceptual and Physical Modeling Time Dimension Categorization Entity Validation Checklist Completeness Correctness 3.Attributes and Identifiers in Detail oAttributes oProperties or Characteristics oAttributes as Data oAttribute Values oNames and Descriptions oAttribute Domains oDefinition of a Domain oDomain Information oAttribute Values and Domains oValue Set oRange oType oNull Values oTypes of Attributes oSingle-Valued and Multivalued Attributes 3Data Modeling Online Training | www.iqonlinetraining.com

4. oSimple and Composite Attributes oAttributes with Stored and Derived Values oIdentifiers or Keys oNeed for Identifiers oDefinitions of Keys oRelationships in Detail oRelationships oAssociations oRelationship: Two-Sided oRelationship Sets oDouble Relationships oRelationship Attributes oDegree of Relationships oUnary Relationship oBinary Relationship oTernary Relationship oQuaternary Relationship oStructural Constraints oCardinality Constraint oParticipation Constraint oDependencies oEntity Existence oRelationship Types oIdentifying Relationship oNonidentifying Relationship oMaximum and Minimum Cardinalities oMandatory Conditions: Both Ends oOptional Condition: One End oOptional Condition: Other End oOptional Conditions: Both Ends oSpecial Cases oGerund oAggregation oAccess Pathways oDesign Issues oRelationship or Entity Type? oTernary Relationship or Aggregation? 4Data Modeling Online Training | www.iqonlinetraining.com

5. oBinary or N-ary Relationship? oOne-to-One Relationships oOne-to-Many Relationships oCircular Structures oRedundant Relationships oMultiple Relationships oRelationship Validation Checklist oCompleteness oCorrectness 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 Review of the Steps Normalization as Verification 5.Modeling for Data warehouse 5Data Modeling Online Training | www.iqonlinetraining.com

6. oDecision-Support Systems oNeed for Strategic Information oHistory of Decision-Support Systems oOperational Versus Informational Systems oSystem Types and Modeling Methods oData Warehouse oData Warehouse Defined oMajor Components oData Warehousing Applications oModeling: Special Requirements oDimensional Modeling oDimensional Modeling Basics oSTAR Schema oSnowflake Schema oFamilies of STARS oTransition to Logical Model oOLAP Systems oFeatures and Functions of OLAP oDimensional Analysis oHypercubes oOLAP Implementation Approaches oData Modeling for OLAP oData Mining Systems oBasic Concepts oData Mining Techniques oData Preparation and Modeling oData Preprocessing oData Modeling 6Data Modeling Online Training | www.iqonlinetraining.com