Until recently, advancements in data warehousing and analytics were largely incremental. Small innovations in database design would herald a new data warehouse every
2-3 years, which would quickly become overwhelmed with rapidly increasing data volumes. Knowledge workers struggled to access those databases with development intensive BI tools designed for reporting, rather than exploration and sharing. Both databases and BI tools were strained in locally hosted environments that were inflexible to growth or change.
Snowflake and Tableau represent a fundamentally different approach. Snowflake’s multi-cluster shared data architecture was designed for the cloud and to handle logarithmically larger data volumes at blazing speed. Tableau was made to foster an interactive approach to analytics, freeing knowledge workers to use the speed of Snowflake to their greatest advantage.
15. DATA SCHEMA
Snowflake Web UI – SQL Editor
3rd Party SQL Editor (DBeaver)
3 ys historical data
~184.000.000 rows
16. DATA ARCHITECTURE
Data Sources
Extract, Load &
Transform Tools
(ELT)
Extract,
Transform &
Load Tools
(ETL)
Database
Migration
Services
Snowflake
DW
Data Flow Tools
Tables, CSV, JSON, XML, Avro, Parquet
Virtual
Warehouses
Corporate
Applications
Databases
Cloud
Services
Web
Devices
Azure Blob
Amazon S3
Snowpipe
Data Lake feeds
Data Feed Options with Snowflake
• Snowpipe processed 'Messages' or files;
structured or semi-structured
• Snowpipe designed for continuous ingest –
typically < 1 min latency
• Potential downstream ELT e.g. hourly
• Time-travel can provide static vs dynamic views
• (Future – Downstream pipe processing, Direct
streaming connectivity)
Data Lake
Live Query
creativecommons.tankerkoenig.de
24. PAY FOR WHAT YOU USE…DOWN TO THE SEC.
ETL and
Processing
Morning Noon Night
WorkloadReporting
Ad-hoc
Analytics
Morning Noon Night
Workload
Morning Noon Night
Workload
Data Scientist
Morning Noon Night
Workload
Snowflake Web UI – Account Billing & Usage
25. Scott Smith‘s Blog incl. Download of Sample Workbook: tableau.com/about/blog/2019/5/monitor-understand-snowflake-account-usage
CONNECT TO SNOWFLAKE DIRECTLY
AND ANALYZE/FORECAST ACCOUNT UTILIZATION
27. LEARN MORE: BEST PRACTICES
E-Paper Download: resources.snowflake.com/ebooks/best-practices-for-using-tableau-with-snowflake
E-Book Content:
• Creating efficient Tableau workbooks
• Connecting to Snowflake
• Working with semi-structured data
• Working with Snowflake Time Travel
• Working with Snowflake Data
Sharing
• Implementing role-based security
• Using custom aggregations
• Scaling Snowflake warehouses
• Caching
• Other performance considerations
• Measuring performance
28. TRY: TABLEAU & SNOWFLAKE QUICK START
This Quick Start deploys Tableau
Server in the Amazon Web
Services (AWS) Cloud and
configures it to work with
Snowflake in about 30 minutes.
More information: aws.amazon.com/quickstart/architecture/tableau-snowflake/
29. SESSION TAKE AWAY
What you don’t have to worry when working with the Snowflake
Cloud Data Warehouse
Installing, provisioning and maintaining
hardware and software:
• Snowflake is a cloud-built DW as a service.
• Just create an account and load some data.
• You can then just connect from Tableau and start
querying.
Working out the capacity of your DW:
• Snowflake is a fully elastic platform, so it can scale
to handle all of your data and all of your users.
• Just size your compute (virtual warehouses) up
and down on the fly to handle peaks and lulls in
your data usage.
• Turn your warehouses completely off to save
money when not used
Learning new tools and a new query language:
• Snowflake is a fully ANSI SQL-compliant DW à all skills
and tools, such as Tableau, will easily connect
• Snowflake provides connectors for ODBC, JDBC, Python,
Spark and Node.js
• Even semi-structured data can be accessed via SQL
Optimizing and maintaining your data:
• Snowflake is a highly-scalable, columnar data platform
allowing users to run analytic queries quickly and easily.
• It is not required to index or distribute data across
partitions, it is all transparently managed by the platform.
• Snowflake also provides inherent data protection
capabilities, there is no need to worry about snapshots,
backups or other administrative tasks.