Description

Join our intensive 3-day workshop, ‘Data Analysis in Snowflake – Python & DataFrames’, designed specifically for Data Analysts. This hands-on training will immerse you in the essential aspects of Snowflake, with a focus on practical data analysis using Python and DataFrames. Engage in real-world scenarios, enhance your skills, and transform your data operations with the power of Snowflake and Python.

Format

Mostly workshops

Duration

3 days

Prerequisites

• Basic understanding of SQL
• Basic familiarity with Python programming
• Experience with data analysis concepts is a plus but not mandatory

Target Audience

• Data Analysts
• Data Engineers
• IT Professionals involved in data analysis
• Anyone interested in enhancing their data analysis skills using Snowflake and Python

Training Program

1. Snowflake Overview
   • Introduction to Snowflake
   • Key features and architecture
2. Client Interfaces
   • Using the Snowflake web interface
   • Connecting through various client tools
   • Setting up Python environment for Snowflake
3. Retrieving Data with Python and DataFrames
   • Loading data into DataFrames
4. Using Built-in Functions for Processing and Formatting Retrieved Data
   • String functions in Python
   • Date and time functions in Python
5. Type Conversion in DataFrames
   • Converting between data types
   • Practical use cases
6. Sorting DataFrames
   • Sorting techniques
7. Filtering Rows in DataFrames
   • Applying conditions and logical operators
8. Aggregate Functions with DataFrames
   • Aggregating data functions like COUNT, SUM, AVG, MIN, MAX
9. Grouping and Filtering Groups in DataFrames
   • GROUP BY operations
   • Filtering groups with HAVING conditions
10. Joining DataFrames
    • Merging DataFrames to simulate SQL JOIN operations
    • Practical examples of data joining
11. Inner and Outer Joins, Cartesian Product with DataFrames
    • Differences between join types
    • When to use each type
12. Subqueries with DataFrames
    • Simulating single-row and multi-row subqueries
13. Set Operations with DataFrames
    • UNION, INTERSECT, EXCEPT
14. Window Functions with DataFrames
    • Windowing operations like ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD, FIRST_VALUE, LAST_VALUE
15. DML Operations with DataFrames
    • INSERT, UPDATE, and DELETE operations
16. Working with Semi-Structured Data
    • Loading and querying JSON, Avro, and other formats
17. Database Objects
    • Understanding tables, views, sequences in the context of Snowflake
    • Managing database objects through Python
18. DDL – Creating Tables and Data Types in Snowflake
    • Using Python to execute CREATE TABLE statements
    • Defining data types and constraints
19. Time Travel & Cloning in Snowflake
    • Accessing historical data and performing data recovery
    • Using cloning for data replication
20. Views – Creating and Retrieving Data
    • Creating and managing views in Snowflake through Python
    • Practical use cases for views

Acquired skills

By the end of this workshop, participants will be well-equipped with the knowledge and hands-on experience needed to leverage Snowflake for data analysis using Python and DataFrames.