SQL Server to Snowflake – Transferring Database

Considering the volumes of data generated by any organization, trained administrators have to operate technologically advanced systems, even in remote locations, for data processing. 
One of the methods that are frequently followed by enterprises for optimized data management is migrating SQL server data to Snowflake.

Microsoft SQL Server is one of the leading database technologies. It supports multiple business and analytics operations and processing of transactions in a corporate IT environment. Snowflake is a data warehouse exclusively designed for the cloud with separate storage and computing resources. It can handle both structured and non-structured data without any drop in performance even when several workgroups are working concurrently with data on multiple workloads.
Certain specified steps have to be followed for migrating SQL server data to Snowflake.

Preparing data
It is not necessary to define a schema in advance when loading JSON or XML data into Snowflake. However, it is crucial to prepare data before loading to ensure that the data mappings are correct. Verifying supported data types for Snowflake is therefore critical.

Loading data
Check the Overview of Data Loading Page. It gives the required facets of data loading such as Bulk vs. Continuous loading options, COPY for bulk loading and PUT for staging. For migrating SQL server data to Snowflake, query for extraction is the most used method for getting data out of the SQL server.

Custom Scripting
When Performance is critical and S3 or Azure Blog storage is not applicable, custom scripts like Panda and Python may be used. These are useful for breaking up large datasets into smaller ones. 
These are the basic steps for migrating SQL server data to Snowflake.

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