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SQL Server To Snowflake

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SQL Server To Snowflake

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  1. Loading Data to Snowflake from Microsoft SQL Server

  2. Microsoft is a Relational Database Management System (RDMS) used to store and retrieve data. It supports all applications either on the web or a local area network on a single machine and matches seamlessly with the Microsoft ecosystem.  Snowflake is a recently-introduced cloud-based data warehousing solution with a host of benefits. It is based on a technologically-advanced platform and is the reason why businesses want to migrate data fromSQL Server to Snowflake. 

  3. On Snowflake, you can load both structured and unstructured data that includes JSON, AVRO, XML, and PARQUET data. It is a high-performing platform and multiple users can execute intricate queries simultaneously without facing any drop in speeds. Further, unlike Microsoft SQL Server, Snowflake provides completely independent computing and storage facilities. Users can scale up and down in either of them and pay only for the resources used. Snowflake also supports a large range of cloud vendors, enabling users to work on any of them with the same tools.  Given these benefits, most businesses now want to migrate data from SQL Server to Snowflake. 

  4. Loading database to Snowflake from Microsoft SQL Server There are several steps in this process. · Extracting data from SQL Server – The first step is to mine data from SQL Server through queries for extraction. The data is sorted and filtered during extraction through select statements. For mining large databases, Microsoft SQL Server Management Studio is used for exporting databases in SQL queries, text, or CSV format. · Extracted data processing – The data that is extracted has to be processed and formatted before it can be loaded into Snowflake. This is because the Snowflake architecture supports specified data types only and the data being loaded has to match the type accepted by Snowflake. It is not necessary to specify a schema before JSON or XML data is migrated.

  5. · Staging data to a temporary location – Even the data that has been formatted and processed cannot be migrated directly from SQL Server to Snowflakebut has to be kept in an internal or external temporary storage location. An internal location is created with SQL statements and has high flexibility with users allotting file formats and names to the stage. The external staging area is where the data can be uploaded through a specific Snowflake interface. Presently, Snowflake matches with Microsoft Azure and Amazon S3 external locations, and more are in the pipeline.  · Loading data into Snowflake – Now, the data is ready to be loaded from the staging area to Snowflake. For loading small databases, the Snowflake data loading wizard is applied. For large databases, the COPY command migrates data from the staging area into Snowflake.   Once the database is loaded to Snowflake, provision should be made to only load changes and incremental data and not execute lengthy full data refreshes.  These are the steps for loading data from SQL Server to Snowflake. 

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