The main idea of any data warehouse (DW) is to integrate data from multiple disjointed sources (e.g., CRMs, OLAP/OLTP databases, enterprise applications, etc.) within a single, centralized location for analytics and reporting. Data warehousing in a nutshellīefore we get into Snowflake technology, let’s deal with the key concepts of data warehousing for a common understanding. We’ll dive deeper into Snowflake’s pros and cons, its unique architecture, and its features to help you decide whether this data warehouse is the right choice for your company. These days, Snowflake is one of the most popular options that meets these and a lot of other important business requirements.įor everyone who is considering Snowflake as a part of their technology stack, this article is a great place to start the journey. This demand gave birth to cloud data warehouses that offer flexibility, scalability, and high performance. With the consistent rise in data volume, variety, and velocity, organizations started seeking special solutions to store and process the information tsunami. Not long ago setting up a data warehouse - a central information repository enabling business intelligence and analytics - meant purchasing expensive, purpose-built hardware appliances and running a local data center.
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How to get started with Snowflake Reading time: 16 minutes.Data streaming: Was a weakness, but not anymore.
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