Learn Snowflake Cloud Data Platform

This module explains the entire curriculum and topics which are covered in this entire course. There are total 10 modules in this course.

Below are the modules in the course.

*Time - It is expected time one can take to learn each module with hands-on labs. 

Foundational module that introduces Snowflake as a cloud-native data platform. Following topics will be covered.

Topics Covered

•  What is Snowflake — SaaS, cloud-native, zero infrastructure

•  Snowflake Editions — Standard, Enterprise, Business Critical, VPS

•  Snowsight UI — Worksheets, Dashboards, Data, Marketplace, Activity, Admin

•  Object hierarchy — Account, Database, Schema, Tables, Views

•  Table types — Permanent, Transient, Temporary, External

•  View types — Standard, Secure, Materialized

•  Cloud providers — AWS, Azure, GCP

•  Credits & billing — Warehouse sizes from XS To 6XL

•  Account setup and first SQL queries

Total Scripts Available

• 3 Module Scripts
• 6 Learning Scripts

Topics Covered

•  Three-layer architecture — Storage, Compute, Cloud Services

•  Micro-partitions — 50–500 MB columnar files, AES-256 encrypted, immutable

•  Partition metadata — MIN/MAX values, distinct count, NULL count per column

•  Virtual warehouses — XS to 6XL, T-shirt sizing, auto-suspend/resume

•  Multi-cluster warehouses — Scale UP vs Scale OUT, Standard vs Economy policy

•  Cloud Services layer — Query optimizer, authentication, metadata, transaction management

•  Data clustering & partition pruning — How Snowflake skips irrelevant partitions

•  Query processing lifecycle — Parse → Optimize → Execute → Return

•  Three-tier caching — Result Cache (24 hr), Local Disk Cache, Metadata Cache

•  Warehouse metering and credit consumption tracking

Scripts Available 

• 3 Module Scripts
• 4 Learning Scripts 

Topics Covered

•  Data loading pipeline — Source Files → Stage → COPY INTO → Table

•  Internal stages — User (@~), Table (@%table), Named stages

•  External stages — S3, Azure Blob, GCS with storage integrations

•  COPY INTO — Bulk loading with parallelism and idempotency

•  File formats — CSV, JSON, Parquet, Avro, ORC (named file formats)

•  Semi-structured data — VARIANT column type, dot notation, bracket notation

•  LATERAL FLATTEN — Exploding nested arrays and objects into rows

•  INFER_SCHEMA — Auto-detect schema from Parquet/ORC files

•  Snowpipe — Serverless auto-ingest with S3/Azure/GCS event notifications

•  Snowpipe Streaming — Low-latency row-level ingestion via API

•  Transformation during load — Column mapping, type casting, filtering

•  Error handling — ON_ERROR (CONTINUE, SKIP_FILE, ABORT), VALIDATION_MODE

•  Data unloading — COPY INTO @stage for export to CSV/Parquet/JSON

Available Scripts

• 3 Module Scripts
• 11 Learning Scripts

Topics Covered

DDL extensions — CREATE OR REPLACE, CLONE, CTAS, SWAP, RENAME

•  DML — INSERT, UPDATE, DELETE, TRUNCATE

•  MERGE (Upsert) — Pattern for incremental ETL with MATCHED/NOT MATCHED clauses

•  Window functions — ROW_NUMBER, RANK, DENSE_RANK, NTILE, PERCENT_RANK

•  Offset functions — LAG, LEAD, FIRST_VALUE, LAST_VALUE

•  Window aggregates — Running totals, moving averages, frame specifications (ROWS/RANGE)

•  QUALIFY clause — Filter on window function results without subqueries

•  Common Table Expressions — Standard and recursive CTEs for hierarchical data

•  Semi-structured querying — VARIANT, OBJECT, ARRAY types with dot/bracket notation

•  LATERAL FLATTEN — Deep nested data explosion with multiple joins

•  User-Defined Functions — SQL, JavaScript, Python, Java UDFs and UDTFs

•  Stored Procedures — Snowflake Scripting with variables, loops, exception handling

•  Advanced patterns — GENERATOR (synthetic data), PIVOT/UNPIVOT, OBJECT_CONSTRUCT

Scripts Available

• 3 Module Scripts
• 12 Learning Scripts

Topics Covered

•  Query Profile — Visual execution plan analysis in Snowsight

•  Red flags — Spilling to disk, low partition pruning, exploding joins, queuing

•  EXPLAIN plan — Pre-execution query plan inspection

•  Query History — INFORMATION_SCHEMA vs ACCOUNT_USAGE for different time windows

•  Clustering keys — Selecting columns, measuring depth, automatic re-clustering

•  Partition pruning — Before/after clustering comparison (450/500 vs 3/500 partitions)

•  Three-tier caching — Result Cache (24 hr), Local Disk, Metadata Cache behavior

•  Materialized Views — Auto-refreshing pre-computed aggregations

•  Search Optimization Service — EQUALITY, SUBSTRING, GEO access patterns

•  Query Acceleration Service — Serverless compute for large scan queries

•  Scale UP vs Scale OUT — Decision matrix for warehouse sizing

Scripts Available

• 3 Module Scripts
• 6 Learning Scripts

Topics Covered

Authentication — Password + MFA, SSO/SAML 2.0, Key-Pair, OAuth 2.0

•  RBAC — Role hierarchy, system roles (ACCOUNTADMIN, SECURITYADMIN, SYSADMIN, USERADMIN, PUBLIC)

•  DAC — GRANT, REVOKE, FUTURE GRANTS for automated privilege management

•  Dynamic Data Masking — Role-based column masking policies (email, SSN, phone, salary)

•  Row Access Policies — Multi-tenant row filtering based on role-to-data mappings

•  Network Policies — IP allowlisting/blocklisting at account and user level

•  Encryption — Always-on AES-256, Tri-Secret Secure (customer-managed keys)

•  Data Classification — Automatic PII detection with EXTRACT_SEMANTIC_CATEGORIES

•  Object Tagging — Custom tags (sensitivity, cost_center, data_owner) with allowed values

•  Access History — LOGIN_HISTORY, ACCESS_HISTORY, QUERY_HISTORY for audit trails

•  Security best practices — Least privilege, MFA enforcement, regular access reviews

Scripts Available

• 3 Module Scripts
• 7 Learning Scripts

Topics Covered

•  Streams — Change Data Capture with METADATA$ACTION, METADATA$ISUPDATE, METADATA$ROW_ID

•  Stream types — Standard, Append-Only, Insert-Only

•  Tasks — CRON and interval scheduling with WHEN predicates

•  Task DAGs — Multi-step pipelines with AFTER dependencies

•  Time Travel — AT(TIMESTAMP), AT(OFFSET), BEFORE(STATEMENT) syntax

•  Fail-safe — 7-day recovery window beyond Time Travel retention

•  UNDROP — Instantly restore dropped tables, schemas, and databases

•  Zero-Copy Cloning — Instant database/schema/table clones with copy-on-write

•  Secure Data Sharing — Cross-account data access without data movement

•  Snowflake Marketplace — Publishing and consuming shared datasets

•  Dynamic Tables — Declarative, auto-refreshing transformations with TARGET_LAG

•  Pipeline patterns — Streams+Tasks (imperative) vs Dynamic Tables (declarative)

Scripts Available

• 3 Module Scripts
• 9 Learning Scripts

Topics Covered

•  Cortex AI — COMPLETE (chat with LLMs), SENTIMENT (score text -1 to 1)

•  Cortex AI — SUMMARIZE, TRANSLATE (30+ languages), EXTRACT_ANSWER

•  Cortex AI — EMBED_TEXT_768 for vector embeddings and semantic search

•  Cortex AI — Batch processing patterns on table data

•  Snowpark — Python/Scala/Java DataFrame API with server-side execution

•  Snowpark ML — Preprocessing, model training, and Model Registry

•  Document AI — OCR and structured extraction from PDFs

•  Iceberg Tables — Open table format for cross-engine compatibility

•  Snowflake Notebooks — Collaborative Python + SQL development environment

•  Streamlit in Snowflake — Build interactive data apps without leaving Snowflake

•  Native Applications Framework — Package and monetize data products

Scripts Available

• 3 Module Scripts
• 8 Learning Scripts

Topic Covered

•  Account administration — ORGADMIN role, multi-account organizations

•  Resource Monitors — Credit quotas, NOTIFY/SUSPEND/SUSPEND_IMMEDIATE triggers

•  Warehouse tuning — AUTO_SUSPEND optimization by workload type (ETL, BI, Dev)

•  ACCOUNT_USAGE views — 365-day retention, 45-minute latency (vs INFORMATION_SCHEMA)

•  Credit tracking — WAREHOUSE_METERING_HISTORY, daily trends, per-warehouse breakdown

•  Storage tracking — STORAGE_USAGE, active/Time Travel/Fail-safe/stage breakdown

•  Query analysis — Top slow queries, spilling detection, queuing identification

•  Database replication — Cross-region, cross-cloud data replication

•  Failover groups — Automated DR with configurable replication schedules

•  Cost optimization — Transient tables, zero-retention, tag-based cost attribution

•  Cost center tags — Team-level cost tracking with allowed values and reporting

Scripts Available

• 3 Module Scripts
• 9 Learning Scripts

The culmination of the entire course. Build a complete end-to-end data pipeline (RAW → CURATED → ANALYTICS) that integrates every concept from the previous 9 modules. Followed by comprehensive SnowPro Core Certification preparation including exam domains, practice questions, a 6-week study plan, and career guidance.

Topics Covered

•  SnowPro Core Certification — 115 min, 100 questions, 750/1000 passing score, $175

•  Exam domains — Cloud Platform (25%), Security (20%), Performance (15%), Data Loading (10%), Transformations (15%), Protection & Sharing (15%)

•  SnowPro Advanced — Data Engineer, Architect, Administrator tracks ($375 each)

•  6-week study plan — Mapped to course modules with review milestones

•  Common exam pitfalls — Time Travel limits, edition features, caching behavior

•  Career path — Community resources, continuing education, certification roadmap

Scripts Available

• 3 Module Scripts
• 3 Learning Scripts