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Program overview
Online
On-site
Hybrid
Snowflake Fundamentals
Build a strong foundation in Snowflake for modern analytics and ELT workflows, from core architecture to performance and cost-aware operations. Learn how to load and transform structured and semi-structured data, apply governance basics, and deliver analytics-ready datasets using safe and scalable patterns.
Duration:
2 days
Level:
Beginner
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1500+ users onboarded
Who will Benefit from this Training?
- Data Engineers
- Analytics Engineers
- Data Analysts moving to Snowflake
- BI Engineers
- Developers working with cloud data warehouses
- DevOps/Platform teams supporting data platforms
Training Objectives
- Understand Snowflake architecture and how it differs from traditional databases.
- Learn core Snowflake concepts including databases, schemas, tables, virtual warehouses, roles, and access control.
- Load data into Snowflake using practical ingestion methods and COPY INTO workflows.
- Write efficient SQL queries for analytics and transformations.
- Understand micro-partitions and Snowflake performance fundamentals.
- Use Time Travel and zero-copy cloning for safe recovery and experimentation.
- Understand data sharing concepts and governance basics (intro).
- Apply cost-awareness practices for compute usage using warehouse scaling and auto-suspend.
- Build an end-to-end workflow from staging to transformed analytics tables.
- Use Snowflake UI (Snowsight) features effectively for development workflows.
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Key training modules
Comprehensive, hands-on modules designed to take you from basics to advanced concepts
- Module 1: Snowflake Architecture (How It Differs from Traditional Databases)
- Snowflake cloud-native architecture overview (storage, compute, services)
- Separation of storage and compute and why it matters
- Virtual warehouses and independent scaling concepts
- How Snowflake supports multi-tenant, secure analytics workloads
- Hands-on: Activity: Compare a traditional database design vs Snowflake architecture for an analytics use case
- Module 2: Core Snowflake Concepts (DBs, Schemas, Warehouses, Roles)
- Databases, schemas, tables, and naming conventions
- Virtual warehouses (sizes, scaling, concurrency basics)
- Roles, grants, and access control model fundamentals
- Best practices for environment separation (dev/test/prod concept)
- Hands-on: Lab: Create a database, schema, warehouse, roles, and assign permissions
- Module 3: Using Snowsight (UI Workflow and Productivity)
- Navigating Snowsight (worksheets, databases, query history)
- Using UI for role switching and context management
- Query profiling basics in Snowsight
- Managing warehouses and monitoring usage from UI
- Hands-on: Lab: Run queries, inspect query history, and use the UI to profile performance
- Module 4: Loading Data into Snowflake (COPY INTO and Practical Ingestion)
- Staging concepts (internal stage vs external stage overview)
- File formats and ingestion readiness (CSV, JSON basics)
- COPY INTO workflows and common options
- Error handling basics (bad records, on_error concepts)
- Hands-on: Lab: Create a stage, define file format, and load raw datasets using COPY INTO
- Module 5: Analytics SQL and Transformations (Efficient Query Patterns)
- Writing efficient analytics queries (filters, joins, aggregations)
- CTEs and reusable transformation patterns
- Window functions for analytics logic (rank, dedup concepts)
- Building transformed tables (CTAS patterns, views overview)
- Hands-on: Lab: Transform raw tables into curated analytics tables using SQL best practices
- Module 6: Performance Fundamentals (Micro-Partitions and Query Behavior)
- Micro-partitions concept and how Snowflake stores data
- Partition pruning and why filtering matters
- Clustering concept and when it becomes relevant
- Using query profile to find bottlenecks and optimize
- Hands-on: Lab: Compare query performance with and without pruning-friendly filters and review query profile
- Module 7: Time Travel and Zero-Copy Cloning (Safe Recovery and Experimentation)
- Time Travel use cases (recover deleted/updated data)
- Querying historical data using Time Travel syntax
- Zero-copy cloning for dev/test experiments
- Rollback and recovery workflows for analytics pipelines
- Hands-on: Lab: Clone a table, run changes safely, and recover data using Time Travel
- Module 8: Governance and Data Sharing (Intro)
- Data sharing concepts and common enterprise scenarios
- Secure access controls with roles and least privilege
- Governance basics (ownership, auditing, usage tracking concepts)
- Sharing readiness checklist (what to expose, what to restrict)
- Hands-on: Activity: Design a role model and sharing policy for analysts vs external consumers
- Module 9: Cost Awareness and Warehouse Management
- Snowflake cost model basics (compute vs storage)
- Warehouse scaling strategy (right size, concurrency handling)
- Auto-suspend and auto-resume best practices
- Monitoring cost drivers with query history and warehouse usage
- Hands-on: Lab: Configure auto-suspend and validate cost impact with different workload patterns
- Module 10: End-to-End Workflow (Staging → Transform → Analytics Tables)
- Designing pipeline layers (raw/staging, cleansed, curated concepts)
- Load raw data into staging tables using COPY INTO
- Transform into analytics-ready tables (facts/dimensions concept)
- Validation checks (row counts, null checks, duplicates concepts)
- Hands-on: Capstone Lab: Build an end-to-end Snowflake workflow and produce final KPI queries
Hands-on Experience with Tools
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Training Delivery Format
Flexible, comprehensive training designed to fit your schedule and learning preferences
Opt-in Certifications
AWS, Scrum.org, DASA & more
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100% Live
on-site/online training
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Hands-on
Labs and capstone projects
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Lifetime Access
to training material and sessions
Skill-Gap Assessment
Analysing skill gap and assessing business requirements to craft a unique program
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Personalisation
Customising curriculum and projects to prepare your team for challenges within your industry
2
Implementation
Supplementing training with consulting support to ensure implementation in real projects
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Why Snowflake Fundamentals for your business?
- Faster analytics scaling: Separate compute and storage to scale workloads efficiently.
- Lower operational overhead: Reduce maintenance compared to traditional data warehouse setups.
- Secure data collaboration: Share data across teams and partners with controlled access.
- Better performance control: Right-size warehouses for predictable query speed and cost.
- Modern data foundation: Enable BI, data science, and AI use cases on a unified platform.
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Frequently Asked Questions
2. Will my team get any practical experience with this training?
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With our focus on experiential learning, we have made the training as hands-on as possible with assignments, quizzes and capstone projects, and a lab where trainees will learn by doing tasks live.
3. What is your mode of delivery - online or on-site?
We conduct both online and on-site training sessions. You can choose any according to the convenience of your team.
4. Will trainees get certified?
Yes, all trainees will get certificates issued by Uptut under the guidance of industry experts.
5. What do we do if we need further support after the training?
We have an incredible team of mentors that are available for consultations in case your team needs further assistance. Our experienced team of mentors is ready to guide your team and resolve their queries to utilize the training in the best possible way. Just book a consultation to get support.