Description
The Data Modeling for Analytics Engineering course is carefully designed to provide you with a solid foundation in data modeling, from basic and fundamental concepts to step-by-step implementations that can be directly applied in real-world environments. If the core task of analytics engineering is to transform raw, unstructured data into clean, reliable, and standardized datasets, then data modeling is the blueprint for that engineering and architecture. Data modeling is the mechanism that helps you decide what to build, how to structure it, and what precautions to take to ensure that your structure remains stable and efficient over time as your data changes.
We begin this educational journey by introducing the key components and building blocks of data modeling; concepts such as data models, entities, and relationships will be carefully examined, and we will draw a clear and distinct line between the general concepts of data modeling and dimensional modeling as a specialized approach to this field. In the next step, we will move on to a detailed examination of the smallest building block in any data model.
What will you learn in this course?
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Deep understanding of the concept of data model and accurate recognition of the fundamental differences between modeling for OLTP databases and OLAP analytical databases (with a focus on dimensional modeling).
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Complete familiarity with commonly used schema designs such as star and snowflake schemas, along with the disaggregated structure of truth and dimension tables and determining the level of detail in them.
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Employ specialized strategies to manage data changes in the database, with a particular focus on the concept of slowly changing dimensions (SCD) to maintain system stability.
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Step-by-step and operational walkthrough of the modern data modeling process, from the requirements identification stage and project scope determination to implementation and final data transformation.
Who is this course for?
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Aspiring Analytics Engineers who plan to enter this field or change their career path in this direction.
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Data professionals who want to gain a deeper, more coherent, and theory-based understanding of data modeling principles, processes, and standards.
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Anyone interested in learning the fundamentals of organizing and structuring data for advanced analytics in modern data teams.
Data Modeling for Analytics Engineering course details
- Publisher: Udemy
- Instructor: Maven Analytics • 1,500,000 Learners
- Training level: Beginner to advanced
- Training duration: 2 hours
- Number of lessons: 61
Course topics
Prerequisites for the Data Modeling for Analytics Engineering course
- We strongly recommend taking our Analytics Engineering for Beginners course first to get a basic understanding of core analytics engineering concepts (data warehouses, OLTP vs OLAP, etc.)
Course images
Sample course video
Installation Guide
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Quality: 1080p
Download link
Rapidgator link
File(s) password: www.downloadly.ir
File size
455 MB