Snowflake + Power BI: Cloud Analytics for Everyone
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This document discusses architectures for using Snowflake and Power BI together. It begins by describing the benefits of each technology. It then outlines several architectural scenarios for connecting Snowflake to Power BI, including using a Power BI gateway, without a gateway, and connecting to Analysis Services. The document also provides examples of usage scenarios and developer best practices. It concludes with a section on data governance considerations for architectures with and without a Power BI gateway.
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Snowflake + Power BI: Cloud Analytics for Everyone
- 1. SNOWFLAKE AND POWER BI ANGEL ABUNDEZ VP SOLUTIONS ARCHITECTURE, DESIGNMIND 2/18/2020
- 2. AGENDA Benefits of each technology Architectural Scenarios Usage scenarios Developer Best Practices Data Governance
- 3. © 2018 Snowflake Computing Inc. All Rights Reserved
- 4. © 2018 Snowflake Computing Inc. All Rights Reserved A NEW ARCHITECTURE FOR DATA WAREHOUSING Multi-cluster, shared data, in the cloud 4 Traditional Architectures Snowflake Shared storage Single cluster Shared-disk Decentralized, local storage Single cluster Shared-nothing Multi-cluster, shared data • Centralized, scale-out storage • Multiple, independent compute clusters
- 5. © 2018 Snowflake Computing Inc. All Rights Reserved SEPARATE COMPUTE, SAME DATA 5 Data science ETL Dev/QA BI/Visualization (Auto scaling) Elastic scaling for storage Low-cost cloud storage, fully replicated and resilient Elastic scaling for compute Virtual warehouses scale up & down instantly without downtime to support workload needs Dedicated performance SLAs Each warehouse can access the same tables at the same time without performance penalty (including ETL) Test/Dev/Staging/QA Reference objects in multiple databases with one SQL statement Elastic scaling for concurrency Auto-scaling maintains constant query performance
- 6. © 2018 Snowflake Computing Inc. All Rights Reserved 6 SECURE BY DESIGN Authentication Access control Data encryption External validation • Embedded multi- factor authentication • Federated authentication available • Role-based access control model • Granular privileges on all objects & actions • All data encrypted, always, end-to-end • Encryption keys managed automatically • Certified against enterprise-class requirements
- 7. © 2018 Snowflake Computing Inc. All Rights Reserved
- 8. Any data, any way, anywhere Power BI © 2017 MICROSOFT. ALL RIGHTS RESERVED.
- 9. CREATE COLLABORATE DISTRIBUTE App Workspaces Co-owned Dashboards Co-owned Reports Co-owned Datasets Co-owned Apps Distribute Sharing App Workspaces / Apps Mobile apps Embedding in apps Static: PPT, Email Other: Cortana, Publish to web, Static (Alerts, Print) Development Production App Workspaces Co-owned Dashboards Co-owned Reports Co-owned Datasets Co-owned Apps
- 10. IT Pro Existing Data LOB Applications FilesData Marts End Users Power BI/Excel Power Tools Power BI/SharePoint Analysis Cubes Data Warehouse A balanced approach…
- 11. Power BI Delivery Approaches Business-Led Self-Service BI Bottom-Up Approach IT-Managed Self-Service BI Blended Approach Corporate BI Top-Down Approach Analysis using any type of data source; emphasis on data exploration and freedom to innovate Ownership: Business supports all elements of the solution Scope of Power BI use by business users: Data preparation, data modeling, report creation & execution Governed by: Business A “managed” approach wherein reporting utilizes only predefined/governed data sources Ownership: IT: data + semantic layer Business: reports Scope of Power BI use by business users: Creation of reports and dashboards Governed by: IT: data + semantic layer Business: reports Utilization of reports and dashboards published by IT for business users to consume Ownership: IT supports all elements of the solution Scope of Power BI use by business users: Execution of published reports Governed by: IT Ownership Transfer Over time, certain self-service solutions deemed as critical to the business may transfer ownership and maintenance to IT. It’s also possible for business users to adopt a prototype created by IT.
- 13. USAGE SCENARIO DEMOS TRADITIONAL STAR SCHEMA, DENORMALIZED DATASETS, SHARED DATASETS/DATAFLOWS
- 15. ANALYTICS ARCH W/ GATEWAY Pros Better governance on service accounts used Dedicated resources for scheduled refresh or direct query Control refresh or direct query performance Low cost per node Cons Additional maintenance of Gateway Cluster Workspace contributors or higher need access to Gateway Data Sources
- 16. NOW THINGS ARE SIMPLER… OR ARE THEY?
- 17. ANALYTICS ARCH WITHOUT GATEWAY Pros No infrastructure dependency Less steps to deploy new datasets Zero resource cost to integrate Share datasets across workspaces Cons Cannot enforce credentials used by datasets Can introduce inconsistent deployments leading to: Dataset sprawl Unauthorized access Varying Terminology for the same metrics
- 18. WANT EVEN BETTER PERFORMANCE?
- 19. ANALYTICS ARCH W/ ANALYSIS SERVICES Pros Best performance possible Shared dataset across any workspaces Gets around the 1GB / file limitation Cons Relies on AAD and/or AD Need to learn Visual Studio Different UI Different deployment process Need to learn Analysis Services Performance best practices Processing options Monitoring and Maintenance
- 20. DEVELOPER BEST PRACTICES Make sure you are Query Folding (pushing down Native queries) Create DATE dimension in Snowflake with Fiscal Calendar If report is in Direct Query, double-check the Scheduled Cache Refresh Setting is set to Weekly or Monthly. Otherwise YOU WILL GET CHARGED! Use Certification process in Power BI for Certified Datasets
- 21. DATA GOVERNANCE w/ Gateway w/o Gateway