1. 1 Cloud-Native Data Warehousing Bob Muglia

2. 2 Scenarios with affinity for cloud Gartner 2016 Predictions: By 2018, six billion connected things will be requesting support. Connecting applications, devices, and “things” Reaching employees, business partners, and consumers Anytime, anywhere mobility On demand, unlimited scale Understanding behavior; generating, retaining, and analyzing data

3. 3 Cloud attributes and requirements DYNAMICEASYFLEXIBLE SECURE Scalable Elastic Adaptive Lower cost Faster implementation Supports many scenarios Trust by design

4. 4 structured Transactional data Relational Fixed schema Dominant in traditional environments Machine-generated Non-relational Varying schema Most common in cloud environments The data has evolved semi-structured

5. 5 Today’s reality Barriers to insight Costly, complex infrastructure Web 3 rd -party IOT Enterprise apps Hadoop & noSQL Data Warehouse(s) Datamarts Data challenges

6. 6 The evolution of data platforms Proprietary and Confidential Data warehouse & platform software Vertica, Greenplum, Paraccel, Hadoop, Redshift Data warehouse appliance Teradata 1990s2000s2010s Cloud-native data warehouse Snowflake 1980s Relational database Oracle, DB2, SQL Server

7. 7 Multiple approaches to scaling Scalability with Concurrency Snowflake Scalability limited by storage contention Oracle Exadata Better scalability but still limited concurrency Teradata, Netezza, Greenplum, Vertica, Hadoop Shared-disk Shared-nothing Multi-cluster, shared data

8. 8 Snowflake’s multi-cluster, shared data architecture Database Storage Where data loaded into Snowflake is stored Cloud Services Management layer that brings everything together Compute Where queries are processed 01010 01101 00011

9. 9 What does Snowflake enable? Cost effective storage and analysis of GBs, TBs, or even PB’s Lightning fast query performance Continuous data loading without impacting query performance Unlimited user concurrency Java >_ Scripting Full SQL relational support of both structured and semi-structured data Support for the tools and languages you already use

10. 10 Building data driven applications that provide secure access to insights to 11000+ pharmacies across the country Possibilities are endless Companies providing easy access to analytics to 80% of their employees Provide ability to flexibly combine semi- structured and structured data in one place, while scaling Driving attendance and fan experience through dynamic analytics

11. 11