Post by account_disabled on Dec 5, 2023 4:47:40 GMT
Solution components and the requirements set by the client hence I have sometimes worked with architectures composed of several components. Fortunately with the development of cloud services we can more effectively select components that will allow us to achieve the expected effect with as few services as possible. What's more thanks to cloud solutions we can also easily select services from different providers to combine them into one system. As a certified Microsoft BI expert I should be writing about Azure Synapse at this point but in this article I would like to describe the Snowflake service. What is Snowflake.
Snowflake is primarily a service that provides a database engine dedicated to data warehouse solutions and processing large volumes of data. It is very important to pay attention to this aspect from the very beginning because using Snowflake as an application database Email Marketing List where we operate on single records will not work at all. Snowflake capabilities Snowflake data and tools Snowflake can accept data from a variety of sources ranging from classic databases to IoT data streams.
Collecting the data itself is not the end and the most important thing is to analyze and use the data as quickly as possible in order to derive tangible benefits from them either in the form of reports or results prepared by sophisticated algorithms in the field of Data Science. All the magic of course happens in the middle i.e. in the Snowflake engine. We can store huge amounts of data here creating a Data Lake layer. Just like in the classic Data Lake data does not have to be reduced to a structured format and we can store information in various forms including messages written in XML or JSON. What is very interesting the data will be available from SQL and it will not be necessary to transform it outside the service.
Snowflake is primarily a service that provides a database engine dedicated to data warehouse solutions and processing large volumes of data. It is very important to pay attention to this aspect from the very beginning because using Snowflake as an application database Email Marketing List where we operate on single records will not work at all. Snowflake capabilities Snowflake data and tools Snowflake can accept data from a variety of sources ranging from classic databases to IoT data streams.
Collecting the data itself is not the end and the most important thing is to analyze and use the data as quickly as possible in order to derive tangible benefits from them either in the form of reports or results prepared by sophisticated algorithms in the field of Data Science. All the magic of course happens in the middle i.e. in the Snowflake engine. We can store huge amounts of data here creating a Data Lake layer. Just like in the classic Data Lake data does not have to be reduced to a structured format and we can store information in various forms including messages written in XML or JSON. What is very interesting the data will be available from SQL and it will not be necessary to transform it outside the service.