The 10 Best Data Modeling Courses and Online Training for 2021

The 10 Best Data Modeling Courses and Online Training for 2021

Data modeling is the process of creating a visual representation of information systems in order to communicate connections between different data points and structures. Data models are built to uncover different business needs, with the end goal of bringing to light the types of data used and stored within a system, the relationships among data types, and the ways they can be grouped and organized. Data modeling employs standardized schemas and formal techniques that provide common definitions across an organization.

With this in mind, we’ve compiled this list of the best data modeling courses and online training to consider if you’re looking to grow your data management or analytics skills for work or play. This is not an exhaustive list, but one that features the best data modeling courses and online training from trusted online platforms. We made sure to mention and link to related courses on each platform that may be worth exploring as well. Click Go to training to learn more and register.

Big Data Modeling and Management Systems

Platform: Coursera

Description: In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools. Through guided hands-on tutorials, you will become familiar with techniques using real-time and semi-structured data examples. Systems and tools discussed include AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL.

Modeling with Data in the Tidyverse

Platform: DataCamp

Description: In this course, you will learn to model with data. Models attempt to capture the relationship between an outcome variable of interest and a series of explanatory/predictor variables. Such models can be used for both explanatory purposes. You will leverage your tidyverse skills to construct and interpret such models. This course centers around the use of linear regression, one of the most commonly used and easy-to-understand approaches to modeling.

Databases: Modeling and Theory

Platform: edX

Description: This course is one of five self-paced courses on the topic of Databases, originating as one of Stanford’s three inaugural massive open online courses released in the fall of 2011. This course covers underlying principles and design considerations related to databases; it can be taken either before or after taking other courses in the Databases series.

Predictive Modeling Using Logistic Regression (With SAS)

Platform: Experfy

Description: This course is designed to reduce and/or eliminate these issues. The instructor was introduced to SAS programming during his schooling and the founder of and has designed multiple courses (including best-selling courses) in the area of SAS and statistics.

Data Modeling Training

Platform: Mindmajix

Description: This data modeling training will help you learn how to design a relational data model, dimensional model, incorporate entities from a decomposed JSON document, NoSQL data stores, and more. Also, you’ll understand how data modeling determines and interprets data from experts through step-by-step methods and examples. By the end of this certification course, you will have a firm understanding of what a data model is, data model types, how to apply normalization, how to create both a dimensional and relational data model, and much more.

Applied Statistical Modeling for Data Analysis in R

Platform: Udemy

Description: This course features more than 9 hours of lectures and provides a robust foundation to carry out practical, real-life statistical data analysis tasks in R. It will take you (even if you have no prior statistical modeling/analysis background) from a basic level to performing some of the most common advanced statistical data analysis tasks in R. The module will also equip you to use R for performing the different statistical data analysis and visualization tasks for data modeling.


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