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Introduction to Data Modeling in Snowflake

Step right into the dynamic world of data modeling with Snowflake!

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Course Description

Step right into the dynamic world of data modeling with Snowflake! Begin by uncovering the core concepts of data modeling, where you'll turn data jungles into neat, insightful gardens. You'll learn and apply the theory, witnessing the magical transformation of raw data into actionable insights.

You will engage with the core principles of data modeling, immersing you in hands-on experiences and how to implement them in Snowflake. This course explores several modeling techniques to set up the most efficient cloud data warehouse. Entity-relationship, dimensional modeling, data vault, and others will be part of the learning experience while unraveling the secrets of data normalization. Every lesson is a step closer to mastering the art of transforming raw information into well-organized, easily navigable, and insightful data.

Snowflake is a powerhouse tool you'll harness to optimize data retrieval and analytics. As you move forward, the architecture of Snowflake unfolds, revealing its massively parallel processing prowess and the optimization of data views. It's not just about learning; it's about becoming a strategic asset with the confidence and skills to make data-driven decisions.

By the end of this journey, data modeling won't just be a skill - it'll be an art form you master. Your data modeling adventure awaits!

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  1. 1

    Fundamentals of Data Modeling

    Free

    Embark on a foundational exploration of data modeling with Snowflake and uncover the art of organizing data efficiently. Start with the basics of data modeling concepts, understand its significance in a data-driven world, and learn how to represent and store data effectively. By visualizing data organization on a vast scale, you'll grasp the importance of a well-structured data model in simplifying data querying and analysis.

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    Introduction to Data Modeling
    50 xp
    Components of data modeling
    100 xp
    Describing an entity
    100 xp
    Exploring Conceptual and Logical Data Models
    50 xp
    Steps to build a data model
    100 xp
    Implementing conceptual data model
    100 xp
    Exploring Physical Data Models
    50 xp
    Creating an entity
    100 xp
    Building the physical data model
    100 xp
  2. 2

    Data Relationships and Normalization

    Free

    Unlock the secrets of effective data organization and management, focusing on the critical roles of keys in data relationships and the fundamental principles of data normalization within Snowflake. Delve into the foundational aspects of relational data, emphasizing the importance of primary and foreign keys in structuring and linking data entities. Embark on a journey through the normalization process, starting with 1NF to eliminate duplicate data, advancing to 2NF to address partial dependencies, and culminating in 3NF to remove transitive dependencies.

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  3. 3

    Data Modeling Techniques for Data Warehouse

    Venture deeper into data warehousing strategies with Snowflake, exploring three pivotal data modeling approaches: Entity–Relationship Model, Dimensional Modeling, and Data Vault. Begin by mapping complex relationships within a university system using the Entity–Relationship model, which is perfect for visualizing data interactions. Transition into Dimensional Modeling to simplify data analysis through fact and dimension tables, ideal for insightful reporting. Then, delve into Data Vault modeling for a robust framework that excels in historical data tracking and flexibility.

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  4. 4

    Snowflake Components

    Unlock the potential of Snowflake's architecture to optimize query performance, enhancing the speed and efficiency of your data models. Explore the advantages of columnar storage, Massively Parallel Processing (MPP), and micro-partitions in Snowflake, contrasting them with traditional databases for a clear understanding of Snowflake's superior performance. Delve into Snowflake's data objects—virtual warehouses, tables, views, and more—to smartly organize your data. Master techniques such as query optimization, the use of subqueries, and Common Table Expressions (CTEs) to streamline data processing.

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datasets

ECommerce OnlineRetail.csvHREmployees.csvManufacturingChocBars

collaborators

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George Boorman
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Arne Warnke
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Kat Zahradova
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Amina Edmunds

audio recorded by

Nuno Rafael Rocha's avatar
Nuno Rafael Rocha
Margarita Torres HeadshotMargarita Torres

Data Scientist and Senior Data Engineer

Data Scientist and Senior Data Engineer. Expert in architecting data-driven solutions, with a strong foundation in analytics, big data management, and the application of AI and Machine Learning technologies. Passionate about enhancing data quality and integrity, driving business insights, and fostering innovation for impactful outcomes.
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