Dimensional Data Modeling Online Training

Introduction

IQ Technologies is a leading online training provider offering broad range of IT Professional courses. Data modeling stands as a foundation plan for users to communicate information requirements about various business processes as well as for developers to consider these requirements while constructing an effective physical database. Dimensional Data Models are different from Entity Relation data models and stand as preferred option for designing comprehensive databases. The high in demand Dimension Modeling course is easy to practice with IQ Technology’s all-inclusive course curriculum and practical approach. Have a quick look at the course summary below.

COURSE SUMMARY

Course Name Dimensional Data Modeling Online Training
Contents Fundamentals of Dimensional Data Modeling
Duration 30 Hours with Flexible timings
Delivery Instructor Led-Live Online Training
Eligibility Any Graduate
Ideal For Fresher, aspiring  job seekers in the field of BO
Next Batch Please visit the schedule section

Course Objectives

HIGHLIGHTS OF DATA MODELING AT IQ ONLINE

  • Practical guide to create Data Model for Business Intelligence and Data Warehouse applications
  • Focuses on Facts and Dimensions
  • Covers Detailed topics of Data warehouse , Database and Business Intelligence conception
  • Handles SQL framework in relation with Data Modeling
  • Explains the Difference between Entity Relational Modeling and Dimensional Modeling
  • Delivers Knowledge on customizing pre -built data models.
  • Handles Data Modeling course curriculum from a job standpoint

CORE BENEFITS OF LEARNING DIMENSIONAL DATA MODELING

Dimensional Data Models are high in demand due to the discrete characteristics that collate complex data from multiple sources and create a distinct, consistent user view. They are also instrumental in supporting business with informed decision-making capability. Moreover they offer flexibility and scalability to databases and also upgrade end user experience to the next level. All these factors make this skill a much in demand skill and therefore has a good job market.

KEY FOCUS AREAS

Data Modeling Key Concepts, Data Models, Data Architectures, User Requirement Grouping, Entity Relational Data Model Vs Dimensional Data Models, Schemas, Methods, Attributes, Granularity, Keys (Primary, Foreign, Surrogate), Facts, Dimensions, Data Integrity, Normalization.

Course Curriculum

Dimensional Data Model is the basis of well designed data warehouse and is built around Data Integration. This course presents the latest data modeling and database design techniques in a vendor-neutral manner that works for any database management system. It focuses on how to create conceptual, logical, and physical data models and throws insights into handling temporal and analytical data too.

CONTENTS :

DIMENSIONAL MODELING CONCEPT TO PROJECT INITIATION

  • Dimensional Modeling experts on job responsibilities and limitations
  • Role of Dimensional Data Modeling in constructing independent Data Marts.
  • Integrate DW & BI with Business and System Objectives
  • Hybrid Architectures
  • Kimball Life cycle
  • Industry wide best practices for creating low risk enterprise Data Warehouse

REQUIREMENT GROUPING FOR DIMENSIONAL MODELING

  • Gather Requirements and group across business processes
  • Surpass Value for Data Profiling
  • Business Process Decoder Ring
  • Draw Relationship between Strategic Initiatives and business processes data

DATA ARCHITECTURE

  • Decision support System
  • Detailed overview on ER Model malfunction DSS
  • Enterprise Data Warehouse Architectures
  • Matrix Overview with Conquer and Divide operations
  • Integration vs. Centralization
  • Disparity with CIF

DIMENSIONAL MODELING ESSENTIALS

  • Basics of Dimensional Modeling
  • folklore about Dimensional Modeling
  • Design Fact Tables and Dimension Tables
  • Drill up and Drill Down and Drill Across Conceptual implementation
  • Damageable Notions

FACT TABLE CONSTRUCTION

  • Basics of Facts , Fact Tables , Types of Fact Tables
  • Granularity concept , details and in practical implementation
  • Preferable Header/Line Modeling Patterns
  • Fact Table Keys
  • Fact Table Design Patterns
  • Dealing with void in Dimensional Modeling

DIMENSIONAL TABLE CONSTRUCTION

  • Basics of Dimensions , Dimension Tables
  • Time and Date Consideration for Dimension Tables
  • Dimension Categories : Hot Swappable, Abstract Generic, Monster
  • Dimension Table Keys
  • Data Warehouse Role Models
  • Hidden Dimensions
  • De-Clutter with irrelevant Dimension
  • Correlate Dimensions
  • Accelerating Slowly changing Dimensions
  • Scenarios cause damage to Dimensions

DIMENSION PROTOTYPE

  • Manage Schemas : Snow Flakes, Outriggers , and Bridges
  • Keyword Dimension
  • Managing Hierarchies
  • Patterns for better Dimensional Modeling
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