Snowflake to Sponsor our October Meeting

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Snowflake is the only data warehouse built for the cloud. Snowflake delivers the performance, concurrency and simplicity to store and analyze all of an organization’s data in one location. Snowflake’s technology combines the power of data warehousing, the flexibility of big data platforms and the elasticity of the cloud at a fraction of the cost of traditional solutions. Snowflake: Your data, no limits. Find out more at snowflake.net. See below for a sneak peak at what we can look forward to at the next meeting.

Speaker: Kent Graziano, Senior Technical Evangelist
Presentation: Agile Methods and Data Warehousing: How to Deliver Faster
Abstract: Most people will agree that data warehousing and business intelligence projects take too long to deliver tangible results. Often by the time a solution is in place, the business needs have changed. With all the talk about Agile development methods like SCRUM and Extreme Programming, the question arises as to how these approaches can be used to deliver data warehouse and business intelligence projects faster. This presentation will look at the 12 principles behind the Agile Manifesto and see how they might be applied in the context of a data warehouse project. The goal is to determine a method or methods to get a more rapid (2-4 weeks) delivery of portions of an enterprise data warehouse architecture. Real world examples with metrics will be discussed.

Speaker: Brad Ganas, Solution Architect
Presentation: Snowflake Best Practices in Cloud Data Warehousing
Abstract: The Cloud and Internet of Things (IoT) are producing a variety of data at an unprecedented rate. Organizations struggle capturing, transforming, and analyzing these complex data structures mixed with traditional relational style datasets using conventional MPP and/or Hadoop infrastructures. Snowflake has taken a new approach to these challenges by building a brand new database that is architected for the Cloud (SaaS, elastic on all dimensions, etc) and is capable of handling both structured and semi-structured data at Petabyte scale.

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