By Anuj Tuli, CTO
Organizations that have embarked on the journey to collecting and analyzing data are tasked with three distinct workstreams to achieve their goal – 1) Identifying the right data to capture, 2) Bringing data from various sources into the data warehouse, 3) Performing guided analysis on the captured data so as to derive meaning from it.
A modern data warehouse platform helps bring these activities together, so that you can easily identify, capture and retrieve data from various sources, and provide visibility and reporting capabilities for chosen interpretation. Snowflake is built for data scientists and data engineers, and it supports modern data and applications that use as much unstructured data as structured data.
Snowflake offers SaaS data warehousing services, and have also made available a number of connectors for data retrieval on their github here – https://github.com/snowflakedb. There is also a community page that provides hands-on exposure to the Snowflake platform, and other educational videos. More info here – https://community.snowflake.com/s/education-services
Keyva provides services and offerings around Snowflake data warehousing platform. You can always reach our team at: firstname.lastname@example.org to request additional information.
Anuj is the CTO at Keyva, a services and software IP company based out of Minneapolis. In this role, he specializes in developing and delivering vendor-agnostic solutions that avoid the “rip-and-replace” of existing IT investments. Tuli helps customers chart a prescriptive strategy for Application Containerization, CI/CD Pipeline Implementations, API abstraction, Application Modernization, and Cloud Automation integrations. Prior to Keyva, he was the Director of Automation Solutions at Tech Data and led the development and management of Cloud Automation IP and related professional services. With an application developer background, he provides a hands-on perspective towards various technologies.
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