Advanced Analytics: Performing Analytics Using Snowflake

Snowflake 2022    |    Intermediate
  • 16 Videos | 1h 49m 32s
  • Includes Assessment
  • Earns a Badge
Data analytics is the systematic, computational analysis of data or statistics used to discover and communicate meaningful patterns. In business, analytics can be used to extract insights for a business strategy or identify new business opportunities. Snowflake is a managed data platform for big data storage, processing, and analytics that allows for common SQL operations and additional operations. In this course, explore various types of Snowflake join operations and data sampling. Next, learn how to use common table expressions (CTEs) and construct queries. Finally, work with functions related to partitioning, windowing, and ranks. Upon completion, you'll be able to use joins, perform row-based and block-based sampling, construct CTEs, and perform windowing and partitioning operations in Snowflake.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    recognize Snowflake’s support for big data analytics
    perform inner, left, and right joins
    execute full outer, natural, and cross joins
    use subqueries and set operators
    identify how sampling works in Snowflake
    perform row and block sampling
    use CTEs within queries
  • employ self-joins and recursive CTEs
    use the CONNECT BY clause
    recall how windowing functions work in Snowflake
    utilize the ROW_NUMBER, RANK, and DENSE_RANK functions
    use ranking and windowing functions with partitioned data
    perform windowing operations to create unbounded preceding and unbounded following windows
    utilize sliding windows and access data in partitions
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m
    UP NEXT
  • Playable
    2. 
    Big Data Analytics in Snowflake
    3m 32s
  • Locked
    3. 
    Performing Join Operations in Snowflake
    7m 4s
  • Locked
    4. 
    Executing Additional Joins in Snowflake
    5m 11s
  • Locked
    5. 
    Using Subqueries
    10m 43s
  • Locked
    6. 
    Snowflake Sampling
    3m 54s
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    7. 
    Performing Row and Block Sampling in Snowflake
    8m 30s
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    8. 
    Using CTEs within Queries
    10m 16s
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    9. 
    Employing Self-joins and Recursive CTEs
    9m 22s
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    10. 
    Using the CONNECT BY Clause
    7m 22s
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    11. 
    Snowflake Windowing
    7m 10s
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    12. 
    Utilizing Rank-related Functions
    7m 19s
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    13. 
    Using Ranking and Windowing Functions
    8m 22s
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    14. 
    Performing Windowing Operations
    7m 8s
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    15. 
    Utilizing Sliding Windows
    7m 24s
  • Locked
    16. 
    Course Summary
    5m 15s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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