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Overview
This two-day, role-specific course introduces data analysts to how the Snowflake AI Data Cloud enables them to deliver actionable insights and reports to their organization to drive business value. The course is structured around a data analysis lifecycle placing each capability Snowflake provides in the data analyst’s context. The course begins with how to connect to the Snowflake Data Cloud. It then covers how to analyze, ingest, enrich, report, and diagnose data insights with Snowflake. The course consists of lectures, labs, demonstrations, and discussions.
Outline the unique and differentiated architecture of the Snowflake AI Data Cloud. Exploit the options provided to connect and interact with the Snowflake AI Data Cloud. Describe how to use BI tools for data analysis in Snowflake. Summarize query constructs, Data Definition Language (DDL), Data Manipulation Language (DML), and Data Query Language (DQL) operations. Use Snowflake’s extensive SQL capabilities and the built-in table, scalar, window, and estimation functions to support data analysis. Apply Snowflake best practices when working with semi-structured data. Load and transform data. Visualize data outside of Snowflake. Employ Snowflake features in the reporting process and activities performed by the data analyst to create analytic visualizations. Explain Snowflake’s unique approach to caching and the benefits to query performance. Perform query evaluation, pre- and post-execution, using Snowflake’s Explain, Query History, and Query Profile.
Data Analysts Business Intelligence users
Coming Soon...
Module 1: Data Analysis with Snowflake Snowflake Overview Why Snowflake? Snowflake Functional Architecture Platform Features GettingStarted with Snowflake Snowflake Architecture Snowflake Architecture Layers Snowflake Structure Account Usage and More Information Schema and Account Usage Using Parameters to Control Snowflake Query Tags Sample Data Sets Client Interfaces Client Interface Overview Authentication Snowsight SnowSQL Connecting Tools to Snowflake SQL Support in Snowflake Data Definition Language (DDL) Data Manipulation Language (DML) Data Query Language (DQL) Set Operations and Joins Subqueries and Common Table Expressions Dynamic Pivot Queries Constructing Efficient Queries Copilot Functions in Snowflake Function Overview Estimation Functions User-defined Functions Stored Procedures Snowflake Scripting Other Snowflake Features Collation Sampling Snowflake Tasks Alerts Creating More Complex Queries Window Functions, Syntax, and Usage Group By and Grouping Sets Recursive With and Connect By Semi-structured Data Semi-structured Data Overview Query Semi-structured Data Continuous Data Protection Time Travel Cloning Module 2: Collaboration Data Loading Data Loading Concepts Examples of Data Loading Module 3: Snowflake Data Lake Support Reporting Using Snowflake Explore Data Prepare Data Analyze Data Visualize Data Integrate BI Tools Caching and Query Pruning Metadata and Caching Overview Metadata Query Result Cache Data Cache Query Pruning Visualizing Query Execution with Query Profile Using Explain Using Query Profile Performance Tips and Troubleshooting SQL Performance Tips Performance Bottlenecks
Module 1: Data Analysis with Snowflake
Snowflake Overview
Snowflake Architecture
Account Usage and More
Client Interfaces
SQL Support in Snowflake
Functions in Snowflake
Other Snowflake Features
Creating More Complex Queries
Semi-structured Data
Continuous Data Protection
Module 2: Collaboration
Data Loading
Module 3: Snowflake Data Lake Support
Reporting Using Snowflake
Caching and Query Pruning
Visualizing Query Execution with Query Profile
Performance Tips and Troubleshooting
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