Data Modeling Course: Learn How to Organize & Structure Data for Maximum Efficiency

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Data Modeling Course Overview


Data Modeling is an essential tool for businesses, as it helps transform raw data into meaningful information. The course provides an introduction to data modeling for business and technical audiences. It covers data concepts, fundamentals of data modeling and modeling techniques, structured and unstructured data, entity-relationship diagrams, and popular data modeling techniques. The course also includes a hands-on project regarding logical to physical data modeling, where participants will gain skills in understanding the data model structure, the relationships between entities and data elements, and the important steps involved in the data modeling process. The course is designed to give an overview of the data modeling process and is suitable for those who need to understand the basics of data modeling and its implications.
Data Modeling
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Start your session at a date of your choice-weekend & evening slots included, and reschedule if necessary.
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You will learn:

Module 1: Introduction to Logical Data Modeling
  • Importance of logical data modeling in requirements
  • When to use logical data models
  • Relationship between logical and physical data model
  • Elements of a logical data model
  • Read a high-level data model
  • Data model prerequisites
  • Data model sources of information
  • Developing a logical data model
  • Importance of well-defined solution scope
  • Functional decomposition diagram
  • Context-level data flow diagram
  • Sources of requirements
  • Types of modeling projects
  • Discovering entities
  • Defining entities
  • Documenting an entity
  • Identifying attributes
  • Distinguishing between entities and attributes
  • Model fundamental relationships
  • Cardinality of relationships
  • Is the relationship mandatory or optional?
  • Naming the relationships
  • Discover attributes for the subject area
  • Assign attributes to the appropriate entity
  • Name attributes using established naming conventions
  • Documenting attributes
  • Modeling many-to-many relationships
  • Model multiple relationships between the same two entities
  • Model self-referencing relationships
  • Model ternary relationships
  • Identify redundant relationships
  • Use supertypes and subtypes to manage complexity
  • Use supertypes and subtypes to represent rules and constraints
  • Normalize a logical data model
  • Reasons for denormalization
  • Transactional vs. business intelligence applications
  • Verify the technical accuracy of a logical data model
  • Use CASE tools to assist in verification
  • Verify the logical data model using other models
Live Online Training (Duration : 24 Hours)
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.

2150 + If you accept merging of other students. Per Participant & excluding VAT/GST
4 Hours
8 Hours
Week Days
Weekend

Start Time : At any time

12 AM
12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Group Training
1900 Per Participant & excluding VAT/GST
Online
05 - 07 Jun 09:00 AM - 05:00 PM CST
(8 Hours/Day)
Online
03 - 05 Jul 09:00 AM - 05:00 PM CST
(8 Hours/Day)
Data Modeling
Course Prerequisites

1. Experience working with a relational database system
2. Working knowledge of data management fundamentals, including database design, query design, and data integrity
3. Understanding of Structured Query Language (SQL)
4. Knowledge of data analysis techniques and concepts
5. Familiarity with data modeling principles, such as entity-relationship modeling and star schemas
6. Knowledge of data warehouses, integrated data models, data marts, and big data architectures
7. Experience utilizing data profiling techniques such as pattern recognition and value range analysis

Target Audience


Data modeling training provides an essential skill for business analysts and data analysts to understand the relationships between data sets for effective data analysis and decision-making
The target audience for data modeling training includes anyone who performs data analysis or utilizes data to make decisions, from data scientists and business analysts to IT professionals in database design roles
The training also appeals to those who are beginning their data analytics career and developing their professional knowledge
Additionally, data modeling training can be beneficial for experienced professionals working in organizations seeking to improve their data analysis and decision-making processes
The training is designed to equip people of any level with the expertise to build structured and dynamic models that drive innovation by allowing the identification of key relationships between data sets
It can also empower stakeholders to have better insights into their performance and the informed decision-making they need to improve their products and services

Learning Objectives of Data Modeling


1. Understand the principles and practice of data modeling.
2. Learn how to model data with UML, Entity-Relationship diagrams, and data dictionaries.
3. Be able to identify the different types of data models and use them to model business requirements.
4. Develop a strategy for creating and managing data models for enterprise applications.
5. Analyze data and create logical models that are conducive to a given implementation.
6. Design physical data models and build a data flow diagram that demonstrate the retrieval and insertion of data.
7. Learn how to incorporate data modeling into the planning and development of applications.
8. Learn best practices for effective data security and data validation.
9. Gain an understanding of how to integrate data modeling with other development processes.
10. Understand how data modeling can optimize user interaction, reporting, and application performance.

FAQ's

Yes, course requiring practical include hands-on labs.
1-on-1 Public - Select your start date. Other students can be merged.
1-on-1 Private - Select your start date. You will be the only student in the class.
You can buy online from the page by clicking on "Buy Now". You can view alternate payment method on payment options page.
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You will receive the digital certificate post training completion via learning enhancement tool after registration.
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Yes, we also offer weekend classes.
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It is recommended but not mandatory. Being acquainted with the basic course material will enable you and the trainer to move at a desired pace during classes.You can access courseware for most vendors.
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Schedule for Group Training is decided by Koenig. Schedule for 1-on-1 is decided by you.
In 1 on 1 Public you can select your own schedule, other students can be merged. Choose 1-on-1 if published schedule doesn't meet your requirement. If you want a private session, opt for 1-on-1 Private.
Duration of Ultra-Fast Track is 50% of the duration of the Standard Track. Yes(course content is same).

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