Data Modeling Certification Training Course

Why select this training course?

The purpose of data modeling is to present the data requirements and define how users should manage and access it. It helps in understanding the business processes of an organization, which then leads to understanding the data requirements for that particular process. The data models are created for storing this data. Data Modeling also analyses relationships between different objects to categorize them into various groups. It is an activity of defining a logical structure of relational data in an organized manner. It helps to understand the various entities in one table with their combination and relationships.

Why are business organizations using data modeling?

Data modeling gives business users real-time visibility into large volumes of complex, multi-structured and semi-structured data, streamlining business processes with intuitive visual tools to analyze, visualize and manipulate data. Data Modeling enables you to build an efficient, sustainable and scalable architecture by following the best practices of data modeling components. With data modeling, you have a blueprint visually defining the interrelationship between business and technical data requirements

How are businesses using data modeling as a tool for growth?

Data modeling transforms data from one format into another to improve an organization’s understanding of how its business functions. The information collected can help companies gain insight into customer buying habits, which can translate into better products and services or marketing strategies. This can ultimately result in growth for a business. Data modeling is a tool that can be used to identify customer attributes, which will lead to a clear understanding of customers and, in turn, customer relationships. With the information received, customer engagement can be increased. You can bring clarity to your systems, processes and teams through data modeling. With the right data, you can identify growth areas, improve customer satisfaction and provide a clear view of your customers.
Data modeling is a very sought-after skill. The IT departments of most organizations need data specialists that can properly analyze, model and process the data to be stored. If you are looking for a career with prospects, Rcademy’s Data Modeling Certification Training Course can help you reach your goal. Data modeling is an important process in data analysis and management. This course will teach you the necessary skills that you need to take your career to the next level, as well as help you to understand the importance of data models.
The course takes you from the very basics of Data Modeling to advanced modeling techniques. This course will help you to become a more effective data modeler who can build better Data Models with less effort and time. Rcademy’s course has been designed to guide you through the entire process from start to end and offer you the knowledge necessary to professionally present your Data Modeling skills.

Who should attend?

Rcademy’s training course is ideal for data-oriented individuals as well as enthusiasts such as:

•  Data Managers
•  Business Analysts
•  Managers and professionals from different walks of life
•  Financial analysts/financial statement analysts
•  Quantitative analysts
•  Business architects
•  Project manager
•  IT professionals
•  Graduates and Scholars
•  Entrepreneurs

What are the course objectives?

Rcademy’s Data Modeling Certification Training Course is aimed at the following objectives:

•  To learn to create high-quality and consistent data for business applications
•  To learn to use fundamental concepts of data modeling in practical scenarios
•  To understand the situations that call for data modeling
•  To recognize data modeling as a key tool for organizations to enhance the value of their data
•  To learn to use data models as a visual description of data requirements of the business
•  To understand different types of data models and the process of creating them
•  To learn to use data models to articulate business processes and thereby gain a better understanding of them
•  To learn to identify data requirements for business processes through data modeling
•  To use data models to uncover data and identify hidden patterns as well as relationships
•  To build an efficient data modeling strategy to gain better control over data
•  To develop skills for presenting necessary data findings to the project team for feedback and review

How will this course be presented?

• Interactive sessions
• Use of case studies
• Management games
• Learning preparation of reports, charts, graphs
• Real-time exercises
• Problem-solving and Group discussion sessions

What are the topics covered in this course?

Module 1: Introduction to Data Modeling

•  What is the data model
•  Database design
•  Outputs of the data model
•  Importance of data modeling
•  Applications of data modeling

Module 2: Entity-Relationship Model

•  Constructs of the entity-relationship model
•  Entities and their types
•  Attributes
•  Relationships
•  Database design process

Module 3: Building Data Model

•  Requirement analysis
•  Identification of data objects
•  Drafting E-R diagram
•  Key attributes and non-key attributes
•  Generalization hierarchies
•  Integrity rules

Module 4: Modeling Structural Database Objects

•  Schemas
•  Tables
•  Indexes
•  References
•  Materialized views

Module 5: Conceptual Data Model

•  Characteristics of the conceptual data model
•  Scope of the model
•  Examples of the conceptual data model
•  When to use the conceptual data model
•  Elements

Module 6: Logical Data Model

•  Logical data model examples
•  Components of the logical data model
•  Advantages of the logical data model

Module 7: Physical Data Model

•  Understanding the physical data model
•  Data normalization
•  Steps in physical data design
•  Task flow for modeling
•  Working with multiple physical data models

Module 8: Data Modeling Techniques

•  Hierarchical technique
•  Object-oriented model
•  Network technique
•  Relational technique

Module 9: Classifying Relationships

•  Degree of relationships
•  Connectivity of relationships
•  Cardinality of Relationships
•  Direction of relationships
•  Generalization hierarchy

Module 10: Data Integrity

•  Entity integrity
•  Referential integrity
•  Insert rules
•  Delete rules

Module 11: Maintenance of Data Model

•  Metadata
•  Repository
•  Comparing data model