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Understanding the BigQuery platform





If you are new to BigQuery or if you have doubts about some of the fields or icons of our product, in this article we will explain everything you need to know!



Once logged in to our website, click on BigQuery on the top menu.



Depending on whether you have previously made a transfer or not, you will see one of the following screens.

When you do not have transfers created

When you have already created some transfers



Understanding the actions and buttons on BigQuery





Help button: You will be redirected to our help section for frequently asked questions and tutorials about BigQuery.

New Transfer: It will take you to the menu to create a new transfer.

Filters: To help you find an already created transfer.

Active Off/On: You can activate or deactivate the schedule without having to enter the transfer menu. This is only available for Scheduled transfers.

Actions:

Edit: You will be redirected to the transfer menu for editing.

Duplicate: It will create a new transfer with the same parameters.

Delete: Will delete the transfer.

Refresh: Will refresh the transfer saving the updates on your Big Query Dataset. This is only available for Manually transfers.

Having understood the index, let's explain the transfer menu.


Understanding the Transfer Menu



When you click on the New Transfer button or the Edit button, you will see the following screen:



This page is divided in two: the Origin menu, and the Destination menu.

Origin Menu


Located on the left side, is where you can create the query you want to enter in Big Query.

Select the data source, accounts, date range, metrics, dimensions, and even filters and options! Everything you need to ensure that the information that matters most to you is stored correctly.

You can also load a template or create your own templates! Learn how to do it here.

Destination Menu


Here you have different fields:

Transfer Name: This will be the name of the transfer in Dataslayer. This name is only visible to you and is not transferred to BigQuery.

Timezone: Select your timezone.

Project: You have to previously create a Project in Big Query, once done you can select it in this field.

Dataset or New Dataset Name: You can select a Dataset that you have already created or create a new dataset. These two options are mutually exclusive.

Database Table: This will be the name of the table on BigQuery. It is not necessary that the table is previously created, the name you put here will create a new table in BQ.

Write Mode: We have three write modes: Append, Replace, and Upsert.

Write Modes
Append: It will add the new data to the end of the table. This is the most used and recommended mode
Replace: It DELETES all the data previously imported to the table and adds all the new data in the same table.
Upsert: It updates the old data and adds the new data at the end of the table. Note that this option takes longer to complete as it must update all the data previously imported.


Frequency mode: You can choose between a schedule, manually or manually splitted. We explain how they work here.

Depending on the frequency mode you choose, you will have different options:

Schedule option


Schedule option

You can select when to refresh the query, hourly, daily, weekly, … Set it up and click on Confirm changes.

Manually option


Manually Option

Confirm changes to save the query on Dataslayer and Save & Refresh to upload your data on BigQuery.

Manually Splitted option


Note that you need a date dimension to select this option

Manually Splitted option

Confirm changes to save the query on Dataslayer and it will start uploading your data in stages so that no errors occur.

You can also cancel the upload, we explain how to do it here.

Cancel Manually Splitted option


Preview



If you want to see how the table you have created will look like, you can click on the Preview button to see it.

Note that this preview is limited to 200 rows.

This way you can make modifications, if you have detected any errors or if you want to change the order of the columns, before uploading the table into BigQuery.

The preview won't consume your monthly row limit.

Preview


As always, please contact us via our live chat on our website or via email if you still have doubts or questions. We are happy to help!

Updated on: 01/09/2023

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