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Intro to Snowflake for Devs, Data Scientists, Data Engineers

Semi-Structured Data Manipulation

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Este ejercicio forma parte del curso

Intro to Snowflake for Devs, Data Scientists, Data Engineers

PrincipianteNivel de habilidad

5.0+

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After a very brief intro to the course, learners will create a free trial, open a worksheet, and query sample data. They’ll learn about scaling virtual warehouses and create a virtual warehouse to ingest Tasty Bytes data. They’ll learn about stages, databases, schemas, and tables. They’ll manipulate semi-structured data. They’ll also learn about the different Snowflake architectural layers.

Exercise 1: Intro and Course Overview Exercise 2: Course Components and Resources Exercise 3: Worksheets and a Simple Example - Part I Exercise 4: Worksheets and a Simple Example - Part II Exercise 5: Code to Run Before Hands-on Assignment — Worksheets Exercise 6: Worksheets and a Simple Example — Question 1 Exercise 7: Worksheets and a Simple Example — Question 2 Exercise 8: Virtual Warehouses Overview Exercise 9: Virtual Warehouses Overview - What's Changed Exercise 10: Virtual Warehouses Scaling - Part I Exercise 11: Virtual Warehouses Scaling - Part II Exercise 12: Virtual Warehouses Scaling - What's Changed Exercise 13: Virtual Warehouses — Question 1 Exercise 14: Virtual Warehouses — Question 2 Exercise 15: Virtual Warehouses — Question 3 Exercise 16: Stages and Basic Ingestion - Part I Exercise 17: Stages and Basic Ingestion - Part II Exercise 18: Stages & Basic Ingestion - What's Changed Exercise 19: Code to Run Before Hands-on Assignment — Stages Exercise 20: Stages and Basic Ingestion — Question 1 Exercise 21: Stages and Basic Ingestion — Question 2 Exercise 22: Stages and Basic Ingestion — Question 3 Exercise 23: Databases and Schemas - Part I Exercise 24: Databases and Schemas - Part II Exercise 25: Database Explorer Exercise 26: Databases and Schemas — Question 1 Exercise 27: Databases and Schemas — Question 2 Exercise 28: Databases and Schemas — Question 3 Exercise 29: Tables - Part I Exercise 30: Tables - Part II Exercise 31: Dynamic Tables Exercise 32: Code to Run Before Hands-on Assignment — Tables Exercise 33: Tables — Question 1 Exercise 34: Tables — Question 2 Exercise 35: Tables — Question 3 Exercise 36: Views - Part I Exercise 37: Views - Part II Exercise 38: Views — Question 1 Exercise 39: Views — Question 2 Exercise 40: Views — Question 3 Exercise 41: Semi-Structured Data Types Exercise 42: Semi-Structured Data Manipulation

Ejercicio actual

Exercise 43: Semi-Structured Data — Question 1 Exercise 44: Semi-Structured Data — Question 2 Exercise 45: Semi-Structured Data — Question 3 Exercise 46: Snowflake Architecture Overview Exercise 47: Snowflake Architecture Overview - What's Changed Exercise 48: Wrap-up of Snowflake’s Core Objects and Architecture Exercise 49: Chapter 1 review - Question 1 Exercise 50: Chapter 1 review - Question 2 Exercise 51: Chapter 1 review - Question 3 Exercise 52: Chapter 1 review - Question 4 Exercise 53: Chapter 1 review - Question 5

Learners will identify a recently introduced “error” in the data and use time travel to correct it. They’ll learn about permanent, transient, and temporary tables, and cloning. They’ll create resource monitors. They’ll create UDFs, a UDTF, and a SQL stored procedure. They’ll learn about role-based access, the VS Code extension, Snowpark DataFrames, and the Snowflake CLI.

Exercise 1: Collaborative Development Exercise 2: Collaborative Development — Question 1 Exercise 3: Collaborative Development — Question 2 Exercise 4: Collaborative Development — Question 3 Exercise 5: Intro to Snowflake Feature Overview Exercise 6: Time Travel - Part I Exercise 7: Time Travel - Part II Exercise 8: Code to Run Before Hands-on Assignment Exercise 9: Time Travel — Question 1 Exercise 10: Time Travel — Question 2 Exercise 11: Time Travel — Question 3 Exercise 12: Permanent, Transient, and Temporary Tables Exercise 13: Permanent, Transient, and Temporary Tables — Question 1 Exercise 14: Permanent, Transient, and Temporary Tables — Question 2 Exercise 15: Permanent, Transient, and Temporary Tables — Question 3 Exercise 16: Cloning Exercise 17: Cloning - What's Changed Exercise 18: Cloning — Question 1 Exercise 19: Cloning — Question 2 Exercise 20: Cloning — Question 3 Exercise 21: Resource Monitors Exercise 22: Resource Monitors — Question 1 Exercise 23: Resource Monitors — Question 2 Exercise 24: Resource Monitors — Question 3 Exercise 25: User-Defined Functions (UDFs) - Part I Exercise 26: User-Defined Functions (UDFs) - Part II Exercise 27: User-Defined Table Functions (UDTFs)Exercise 28: UDFs - What's Changed Exercise 29: UDFs and UDTFs — Question 1 Exercise 30: UDFs and UDTFs — Question 2 Exercise 31: UDFs and UDTFs — Question 3 Exercise 32: Stored Procedures - Part I Exercise 33: Stored Procedures - Part II Exercise 34: Stored Procedures — Question 1 Exercise 35: Stored Procedures — Question 2 Exercise 36: Stored Procedures — Question 3 Exercise 37: Role-based Access Control (RBAC) - Part I Exercise 38: Role-based Access Control (RBAC) - Part II Exercise 39: Role-based Access Control — Question 1 Exercise 40: Role-based Access Control — Question 2 Exercise 41: Role-based Access Control — Question 3 Exercise 42: VS Code Extension Exercise 43: Snowpark Dataframes - Part I Exercise 44: Snowpark Dataframes - Part II Exercise 45: Snowpark DataFrames — Question 1 Exercise 46: Snowpark DataFrames — Question 2 Exercise 47: Snowpark DataFrames — Question 3 Exercise 48: Snowflake CLI Exercise 49: Wrap-up of Snowflake Feature Overview Exercise 50: Chapter 2 review - Question 1 Exercise 51: Chapter 2 review - Question 2 Exercise 52: Chapter 2 review - Question 3 Exercise 53: Chapter 2 review - Question 4 Exercise 54: Chapter 2 review - Question 5

Learners will explore four Snowflake workloads: Data Engineering, Generative AI, Machine Learning, and Applications. After reviewing each workload, they’ll see one aspect of that workload in practice: for DE, ingesting streaming data with Snowpipe; for GenAI, using the Snowflake Cortex LLM function “Complete”; for ML, using Snowpark ML to create an XGBoost model and make predictions about a food truck’s location; and for apps, running a Streamlit app that shows us Tasty Bytes’ daily revenue. They will then learn about the Snowflake Data Cloud.

Exercise 1: Intro to Overview of Builder Workloads Exercise 2: DE - Snowflake Data Engineering Overview - Part I Exercise 3: DE - Snowflake Data Engineering Overview - Part II Exercise 4: Snowflake DE Overview — Question 1 Exercise 5: Snowflake DE Overview — Question 2 Exercise 6: Snowflake DE Overview — Question 3 Exercise 7: DE - Snowpipe - Part I Exercise 8: DE - Snowpipe - Part II Exercise 9: Snowpipe - What's Changed Exercise 10: Snowpipe — Question 1 Exercise 11: Snowpipe — Question 2 Exercise 12: Snowpipe — Question 3 Exercise 13: GenAI - Snowflake GenAI Overview - Part I Exercise 14: GenAI - Snowflake GenAI Overview - Part II Exercise 15: Snowflake Cortex via CLI Exercise 16: Snowflake GenAI Overview — Question 1 Exercise 17: Snowflake GenAI Overview — Question 2 Exercise 18: Snowflake GenAI Overview — Question 3 Exercise 19: GenAI - Snowflake Cortex LLM Functions - Part I Exercise 20: GenAI - Snowflake Cortex LLM Functions - Part II Exercise 21: Cortex LLM Functions - What's Changed Exercise 22: Snowflake Cortex LLM Functions — Question 1 Exercise 23: Snowflake Cortex LLM Functions — Question 2 Exercise 24: ML - Snowflake ML Overview - Part I Exercise 25: ML - Snowflake ML Overview - Part II Exercise 26: Snowflake ML Overview - What's Changed Exercise 27: Snowflake ML Overview — Question 1 Exercise 28: Snowflake ML Overview — Question 2 Exercise 29: Snowflake ML Overview — Question 3 Exercise 30: ML - Snowpark ML Modeling - Part I Exercise 31: ML - Snowpark ML Modeling - Part II Exercise 32: ML - Snowpark ML Modeling - Part III Exercise 33: Snowpark ML Modeling — Question 1 Exercise 34: Snowpark ML Modeling — Question 2 Exercise 35: Apps - Snowflake Applications Overview - Part I Exercise 36: Apps - Snowflake Applications Overview - Part II Exercise 37: Snowflake Applications Overview - What's Changed Exercise 38: Snowflake Applications Overview — Question 1 Exercise 39: Snowflake Applications Overview — Question 2 Exercise 40: Snowflake Applications Overview — Question 3 Exercise 41: Apps - Streamlit in Snowflake - Part I Exercise 42: Apps - Streamlit in Snowflake - Part II Exercise 43: Code to Run Before Hands-on Assignment Exercise 44: Streamlit in Snowflake — Question 1 Exercise 45: Streamlit in Snowflake — Question 2 Exercise 46: Streamlit in Snowflake — Question 3 Exercise 47: The Data Cloud Exercise 48: Wrap-up of Overview of Builder Workloads Exercise 49: Chapter 3 review - Question 1 Exercise 50: Chapter 3 review - Question 2 Exercise 51: Chapter 3 review - Question 3 Exercise 52: Chapter 3 review - Question 4 Exercise 53: Chapter 3 review - Question 5 Exercise 54: Course Conclusion Exercise 55: Acknowledgements