Ch 1: Introduction to Snowflake

• Database, DWH Introduction
• Cloud Data Warehouse
• Cloud DWH Implementations
• Snowflake Cloud Intro
• Snowflake: SaaS Platform

Ch 2: Snowflake Concepts

• Snowflake Account (Cloud)
• Snowflake Components
• Snowflake Editions, Credits
• Snowflake Editions
• Virtual Private Edition (VPS)
• Snowflake Pricing

Ch 3: Architecture, Warehouse

• Compute Architecture
• Shared Disk Architecture
• CPU & Memory in Clusters
• Database Query & Data Cycle
• ColumnStore, Virtual Warehouse
• Classic UI with Snowflake
• Massively Parallel Processing

Ch 4: SQL Concepts – 1

• SQL Concepts & Basics
• Snowflake Databases
• Snowflake Tables
• DDL Operations
• DML Operations
• Select Operations

Ch 5: SQL Concepts – 2

• Snowflake Databases
• Snowflake Tables
• Data Imports
• SQL Operators
• Important Functions

Ch 6: SQL Concepts – 3

• Snowflake Data Types
• Snowflake Date Vaues
• Snowflake Text Data
• Snowflake Numeric Data
• Snowflake Type Conversions

Ch 7: Snowflake Databases & Tables

• Snowflake Database Types
• Snowflake Table Types
• Retention Time, Connections
• Permanent, Transient Types
• CREATE TABLE AS SELECT (CTAS)

Ch 8: Time Travel, Recovery

• Time Travel in Snowflake
• Invoking Time Travel Feature
• Timestamp, Offset, Query ID
• Data Recovery, TIMESTAMP
• Fail Safe and UNDROP, OFFSET
• Transient Tables, Real-time

Ch 9: Schemas and Session Context

• Schema Creation Usage
• Permanent, Transient Schemas
• Managed Schemas in Snowflake
• Invoking Schemas & Cloning
• Session Context & Schema
• Data Loading with GUI

Ch 10: Snowflake Cloning

• Cloning with Snowflake
• Zero Copy, Schema Cloning
• Snapshot, Metadata
• Accessing, Clone
• Storage & Metadata Layer
• Real-time Considerations

Ch 11: Snowflake Procedures

• Procedures and Functions
• SQL and JavaScript & CALL
• Transactions & Injection
• sqlText:command
• Cursoring Data and Operations
• Dynamic DML with SPs
• RETURN, RETURNS Statements

Ch 12: Security Management

• Security with Snowflake
• Users & Roles in Snowflake
• Privileges and Groups
• Organization, Account, Users
• Creating, Using Roles, Users
• System Defined Roles Usage
• Role Hierarchy, Dependency
• RBAC & DAC in Real-time

Ch 13: Snowflake Transactions

• Transaction ACID Properties
• Implicit, Explicit and Auto
• Durability and Data Storage
• current transaction() Usage
• to_timestamp_ltz and Usage
• Failed Transactions with SPs
• Transactions and SPs
• Scoped & INNER Transactions

Ch 14: Snowflake Streams & Audits

• Snowflake Streams & Usage
• Streams and DML Auditing
• Snapshot Creation, Offset
• METADATA Options & Streams
• Auditing DML Operations
• Data Flow & Snowflake Streams
• Streams on Transient Tables
• Time Travel with Stream Tables

Ch 15: Snowflake Tasks

• Tasks, Serverless Compute
• Tasks Tree: Root and DAG
• Tasks Schedules and RESUME
• User & Snowflake Managed
• CRON Syntax with Tasks
• Virtual Warehouse Concepts
• Multi Cluster Warehouse
• Auto Scale Options, Billing

Ch 16: SnowSQL and Variables

• SnowSQL Configurations
• DDL, DML & SELECT
• SnowSQL Command Line
• Variables and Batch Process
• DECLARE, LET, BEGIN & END
• EXECUTE IMMEDIATE, FOR
• Creating Virtual Warehouse
• Writing Output to Files

Ch 17: Snowflake Partitions, Stages

• Snowflake Partitions, Use
• Micro Partition with DML, CDC
• Cluster Key, Depth and Overlap
• Internal Partition Types & Usage
• List, Range and Hash Partitions
• Snowflake Stages, Types
• Internal and External Stages
• COPY Command, Bulk Loads

Ch 18: Azure / AWS External Stages

• Azure Storage Account, BLOB
• SAS: Shared Access Signature
• Using SAS Key and FILE PATH
• Azure Storage with BLOB
• COPY INTO Command Usage
• Snowflake Patterns & RegEx
• File Formats: Creation, Usage

Ch 19: Snow Pipes & Incr Loads

• SnowPipe Incremental Loads
• Azure Queues & Integrations
• Azure Active Directory
• External Stage, Enterprise AD
• Snow Pipes and Data Loads
• Incremental Data Loads
• File Format with Reg Expr

Ch 20: Power BI with Snowflake

• Power BI: Big Data Analytics
• Snowflake Data Access
• Datawarehouse Access
• Server URL & Options
• Connection Parameters
• Data Analytics (Report Test)

Ch 1: DBT Fundamentals

• What is Data Build Tool?
• DBT as a data transformation tool
• Importance of DBT in ELT workflows
• DBT Cloud for data transformations

Ch 2: DBT Models and Materializations

• Building models in DBT
• Types of materializations
• Table, view, incremental materializations
• Model configurations

Ch 3: DBT Jinja Templating

• Introduction to Jinja
• Using Jinja with DBT
• Macros and reusable code
• Implementing dynamic SQL

Ch 4: DBT Testing and Documentation

• Writing and executing tests
• Data quality checks
• DBT documentation and lineage graphs
• Generating DBT docs

Ch 5: DBT Seeds and Sources

• Using seeds for static data
• Defining and using sources
• Source freshness checks
• Integrating external data

Ch 7: DBT Deployment and CI/CD

• Deployment strategies for DBT
• Continuous integration and deployment
• Automating DBT workflows
• Version control with Git

Ch 7: DBT Best Practices

• Project structure recommendations
• Coding standards and guidelines
• DBT project optimization
• Performance tuning tips

Ch 8: Hooks in DBT

• Custom scripts to run at specific points
• Adding additional logic to streamline Snowflake
• Analyses and exploratory data workflows
• Ad-hoc analyses that do not get materialized

Ch 9: DBT Snapshots

• Managing historical data
• Implementing DBT snapshots
• Snapshot configuration
• Strategies for handling changes

Ch 10: DBT Packages and Extensions

• Leveraging DBT packages
• Using community packages
• Extending DBT functionality
• Integrations with other data tools

Ch 11: DBT Advanced Topics

• Advanced Jinja usage, Snowpark
• Handling complex data scenarios
• Custom materializations, Snowpark
• Troubleshooting and debugging techniques

• E-Commerce Domain
• Defining project requirements
• Dataset Understanding
• Initial project setup and DBT configuration
• Model planning and development
• Initial testing and validation
• Project deployment and monitoring
• Implementing advanced DBT features
• Comprehensive testing and documentation
• Real-world deployment considerations
• Solution Explanation
• Resume Points
• Interview FAQs and Answers

Ch 1: Cortex AI Fundaments

• AI Fundamentals
• Snowflake Data Engineering
• Snowflake ETL Operations
• Snowflake DWH Operations
• Need for AI Extensions

Ch 2: Cortex AI Fundaments

• AI Fundamentals
• Snowflake Data Engineering
• Snowflake ETL Operations
• Snowflake DWH Operations
• Need for AI Extensions

Ch 3: Introduction to Cortex AI

• What is Cortex AI?
• Why Cortex AI in Snowflake?
• Benefits of AI inside Data Cloud
• Cortex AI Architecture
• AI Use Cases in Modern Organizations
• Cortex AI Components Overview
• Snowflake AI Ecosystem

Ch 4: Cortex AI Concepts

• Cortex AI Setup and Configuration
• Security & Access Management
• Required Roles and Privileges
• Understanding AI Compute Resources
• Creating Sample AI Environment
• Cost Considerations and Best Practices

Ch 5: Snowflake Cortex Functions

• Introduction to Cortex Functions
• AI-Powered SQL Queries
• Text Analysis Functions
• Language Translation Functions
• Text Summarization
• Sentiment Analysis
• Classification Functions
• Information Extraction
• Named Entity Recognition (NER)

Ch 6: Large Language Models (LLMs) in Cortex

• Understanding LLM Concepts
• Foundation Models Supported by Snowflake
• Prompt Engineering Fundamentals
• Effective Prompt Design
• Zero-shot Learning
• Few-shot Learning
• Chain-of-Thought Prompting
• AI Response Optimization

Ch 7: Cortex Complete

• Introduction to Cortex Complete
• Text Generation with SQL
• Generating Summaries
• Content Creation
• Email Generation
• Ticket Resolution Suggestions
• Business Intelligence Narratives

Ch 8: Cortex Analyst

• What is Cortex Analyst?
• Natural Language to SQL
• Conversational Analytics
• Semantic Models
• Business Question Answering
• Dashboard Integration
• AI-Powered Self-Service Analytics

Ch 9: Cortex Search Service

• Introduction to Vector Search
• Semantic Search Concepts
• Search Service Architecture
• Creating Search Indexes
• Query Optimization
• Similarity Search
• Enterprise Knowledge Search

Ch 10: Cortex Agents

• Introduction to AI Agents
• Agent Architecture
• Multi-Step Reasoning
• Tool Calling
• Workflow Automation
• Building Intelligent Agents
• Enterprise AI Assistants

Ch 11: Document AI

• Introduction to Document AI
• OCR Processing
• PDF Data Extraction
• Invoice Processing
• Resume Parsing
• Contract Analysis
• Form Data Extraction

Ch 12: Vector Embeddings & RAG

• Understanding Embeddings
• Vector Databases
• Semantic Similarity
• Retrieval Augmented Generation (RAG)
• Building Knowledge Assistants
• Enterprise Chatbots
• Search Optimization

Ch 13: AI Integration with Azure & AWS

• Azure Integration
• Azure OpenAI
• Azure Data Factory
• Azure Storage Integration
• Power BI Integration
• AWS Integration
• Amazon S3
• AWS Lambda
• AWS Bedrock
• Event-Driven AI Workflows

• Finance / Accounting / HealthCare Domain
• Defining project requirements
• Dataset Understanding
• Initial project setup and DBT configuration
• Model planning and development
• Initial testing and validation
• Project deployment and monitoring
• Implementing advanced DBT features
• Comprehensive testing and documentation
• Real-world deployment considerations
• Solution Explanation
• Resume Points
• Interview FAQs and Answers