This post will help you with export your Google Sheets to MS SQL Server. If you think this needs time, you may use the Google Sheets Connector for MS SQL Server from Blendo. With a few clicks, you will start collecting analytics-ready data, consistently into your MS SQL Server instance. No need for scripts or engineering effort and resources, just replicate your data and focus on what matters – the analysis of your data.
Access your data on Google Sheets
The first step in loading your Google Sheets data to any kind of data warehouse solution, is to access them and start extracting it.
Google Sheets offers a REST API that can be used to programmingly interact with your account. Due to the nature of the application there is no specific set of tables that are being extract but instead each sheet of each spreadsheet is represented as a separate table.
In addition to the above, the things that you have to keep in mind when dealing with the Google Sheets API, are:
- Rate limits. Depending on the API version that is being used, Google Sheets API has rate limits per project and per user.
- Authentication. You authenticate on Google Sheets using either OAuth or the application’s API key.
- Paging and dealing with big amount of data. Platforms like Google Sheets that are dealing with clickstream data tend to generate a lot of data, like events on your web properties.
About Google Sheets
Google Sheets is a free web-based spreadsheet software that is offered by Google as part of the Google Drive services.
Google Sheets allows users to create and modify spreadsheet files online while collaborating with others in real-time. For this it is widely used among various businesses in order to maintain data consistency across departments and to ensure that every member of their team is on the same page.
As with any other spreadsheet app, the data included in the sheets can be of various types, from raw data to aggregated reports.
Transform and prepare your Google Sheets Data for MS SQL Server Replication
After you have accessed data on Google Sheets, you will have to transform it based on two main factors,
- The limitations of the database that is going to be used
- The type of analysis that you plan to perform
Each system has specific limitations on the data types and data structures that it supports. If for example you want to push data into Google BigQuery, then you can send nested data like JSON directly, but keep in mind that any data you get from Google Sheets are in the form of a tabular report just like a CSV.
Of course, when you are dealing with tabular data stores, like Microsoft SQL Server, this is not an option. Instead, you will have to flatten out all data, just as in the case of JSON, before loading into the database.
Also, you have to choose the right data types. Again, depending on the system that you will send the data to and data types that the API exposes to you, you will have to make the right choices. These choices are important because they can limit the expressivity of your queries and limit your analysts on what they can do directly out of the database. Google Sheets has a very limited set of available data types which means that your work to do these mappings is much easier and straight forward, but nonetheless equally important with any other case of a data source.
Export data from Google Sheets to MS SQL Server
So, after you have managed to access data on Google Sheets and you have also figured out the structure that data will have on your database, you need to load data to the database, in our case into a Microsoft SQL Server.
As a feature-rich and mature product, MS SQL offers a large and diverse set of methods for loading data into a database. One way of importing data to your database is by using the SQL Server Import and Export Wizard. With it and through a visual interface you will be able to bulk load data from a number of data sources that are supported.
Another way for importing bulk data into an SQL Server, both on Azure and on premises, is by using the bcp utility. This is a command line tool that is built specifically for bulk loading and unloading of data from an MS SQL database.
Finally and for compatibility reasons, especially if you are managing databases from different vendors, you can you BULK INSERT SQL statements.
In a similar way and as it happens with the rest of the databases, you can also use the standard INSERT statements, where you will be adding data row-by-row directly to a table. It is the most basic and straightforward way of adding data in a table but it doesn’t scale very well with larger datasets.
Updating your Google Sheets data on MS SQL Server
As you will be generating more data on Google Sheets, you will need to update your older data on an MS SQL database. This includes new records, together with updates to older records that for any reason have been updated on Google Sheets.
You will need to periodically check Google Sheets for new data and repeat the process that has been described previously while updating your currently available data if needed. Updating an already existing row on a SQL Server table is achieved by creating UPDATE statements.
Another issue that you need to take care of is the identification and removal of any duplicate records on your database. Either because Google Sheets does not have a mechanism to identify new and updated records or because of errors on any data pipelines, duplicate records might be introduced to your database.
In general, ensuring the quality of data that is inserted in your database is a big and difficult issue and MS SQL features like TRANSACTIONS can help tremendously, although they do not solve the problem in the general case.
The best way to load data from Google Sheets to MS SQL Server
So far we just scraped the surface of what can be done with MS SQL Server and how to ingest data into it. The way to proceed relies heavily on the data you want to load, from which service they are coming from and the requirements of your use case. Things can get even more complicated if you want to integrate data coming from different sources.
A possible alternative, instead of writing, hosting and maintaining a flexible data infrastructure, is to use a product like Blendo that can handle this kind of problems automatically for you.
Easily use the Google Sheets connector from Blendo, along with multiple sources or services like databases, CRM, email campaigns, analytics and more. Quickly and safely ingest Sheets data into MS SQL Server and start generating insights from your data.