Change-data capture with streams - SkilBrill

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Snowflake Training Change-data capture with streams

Snowflake Training

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M1 — Snowflake Architecture

Multi-cluster shared data

Storage and compute separation

Cloud services layer

Account and cloud region setup

M2 — Warehouses and Scaling

Virtual warehouse sizes

Auto-suspend and resume

Scaling policies

Resource monitors

M3 — Storage and Micro-Partitioning

Micro-partitions

Clustering keys

Search optimisation

Storage costs and retention

M4 — Zero-Copy Cloning and Time Travel

Clone semantics

Fail-safe and Time Travel

UNDROP and recovery

Clone for dev/test

M5 — Streams and Tasks for CDC

Change-data capture with streams

MERGE-driven incremental loads

Streamlit in Snowflake quickstart

M6 — Security and Governance

Roles and grants

Dynamic data masking

Row-access policies

Object dependencies and future grants

M7 — Snowpark and Developer Experience

Snowpark Python and Java

Anaconda packages

Stored procedures

M8 — Data Sharing and Marketplace

Secure data sharing

Reader accounts

Marketplace listings

Cross-cloud sharing

M9 — dbt with Snowflake

dbt project structure

Snapshots and incremental models

Tests and exposures

M10 — Capstone and SnowPro Mocks

End-to-end Snowflake pipeline

Cost optimisation review

SnowPro Core and Advanced mocks

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