New Google Sheets Data Connector<\/h3>\n
Google has recently launched a new data connector for BigQuery and Google Sheets users! This is great news for data analysts who want to improve and automate the ease in which they manage data. This solution is designed for big data practitioners who want to use Sheets to crunch big numbers\u2014with this connector you can scan up to 1TB of BigQuery data to extract up to 10,000 rows of data into one sheet through standard SQL. This allows huge amounts of information to be analyzed in an intuitive and collaborative environment.<\/p>\n
Limitations<\/h3>\n
As with all newly released tools, there are some limitations. Although we can be patient while Google improves this tool, it is good to be aware of what we can and cannot do.<\/p>\n
Mobile:<\/b>\u00a0<\/span>Currently, this tool is not mobile friendly. Although, you can view your results in mobile. So, you will need to run your queries on a computer but can shared results can be viewed by and commented on team members on mobile devices.<\/p>\n Automation:\u00a0<\/span><\/b>There are not currently automation features with this tool. We hope that this changes soon, but in the meantime, one of our Sheetgo engineers has created a\u00a0<\/span>free Google Apps Script that you can use<\/a>\u00a0to automate your process.<\/p>\n High-volumes:\u00a0<\/span><\/b>As mentioned before, although this connector supports HUGE data queries at a remarkably fast speed, if you want more than 10,000 rows in a single spreadsheet, you will have to use another method:\u00a0<\/span>getting data from BigQuery to Google Sheets automatically.<\/a>.<\/p>[\/et_pb_text][et_pb_text _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”] To run the Data Connector click\u00a0<\/span>Data\u00a0\u2192 Data connectors\u00a0\u2192 BigQuery<\/strong>.<\/p>[\/et_pb_text][et_pb_image src=”https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/01-opening-1024×836-1.webp” alt=”Navigation to BigQuery in Google Sheets” title_text=”bigquery-navigation” _builder_version=”4.23.1″ width=”100%” global_colors_info=”{}” theme_builder_area=”post_content”][\/et_pb_image][et_pb_text _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”] A window will open up in your Sheet. Select the billing project you want to work on and click\u00a0Write Query.<\/strong><\/p>[\/et_pb_text][et_pb_image src=”https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/02-selecting-billing-project-1024×836-1.webp” alt=”Selecting Billing Project and Writing Query” title_text=”write-query” align=”center” _builder_version=”4.22.2″ width=”100%” global_colors_info=”{}” theme_builder_area=”post_content”][\/et_pb_image][et_pb_text _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”] Using the parameter is not a required step, but comes in handy if you need to add spreadsheet value to the query. Click on Add<\/strong>\u00a0to add Parameters.<\/p>[\/et_pb_text][et_pb_image src=”https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/03-window-overview-1024×836-1.webp” _builder_version=”4.22.2″ width=”100%” global_colors_info=”{}” theme_builder_area=”post_content”][\/et_pb_image][et_pb_text _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”] The parameter name (which is used as a reference) is related to the cell address in the spreadsheet. Give your parameter a unique name for you to remember it easily and choose a cell for reference.<\/p>[\/et_pb_text][et_pb_image src=”https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/04-adding-a-parameter-1024×836-1.webp” alt=”Snapshot of Query Parameter Naming Window” title_text=”query-parameter” _builder_version=”4.22.2″ width=”100%” global_colors_info=”{}” theme_builder_area=”post_content”][\/et_pb_image][et_pb_text _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”] In this example, \u201c In the following screenshot, you can find the list of all tables and structures of each table that you have in your BigQuery account. Think of it as your Table of Content.<\/p>[\/et_pb_text][et_pb_image src=”https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/06-schema-guide.webp” alt=”Table of Content in Bigquery in Google Sheets ” title_text=”table-of-content” align=”center” _builder_version=”4.22.2″ width=”100%” global_colors_info=”{}” theme_builder_area=”post_content”][\/et_pb_image][et_pb_text _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”] In case of writing a Query with an error, the BigQuery query editor<\/strong>\u00a0automatically detects the errors. This is an example of how it detects the spelling error \u201c Once the query is valid, Google tells you so at the bottom. So, make sure that the query is valid before clicking on INSERT RESULTS<\/strong>.<\/p>[\/et_pb_text][et_pb_image src=”https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/08-writing-a-good-query.webp” alt=”Snapshot of Query Validation in Google Sheets” title_text=”valid-query” _builder_version=”4.22.2″ width=”100%” global_colors_info=”{}” theme_builder_area=”post_content”][\/et_pb_image][et_pb_text _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”] If you look at the screenshot, you will notice a couple of things:<\/p>\n \u2013\u00a0The icon in the tab indicates that this is not your regular Google Sheets tab. This tab is different as its sole purpose is to show the BigQuery results -which you cannot edit!<\/p>\n \u2013 The special menu at the bottom, inside the three dots, allows you to control and edit your BiqQuery connection.<\/p>\n \u2013 This connection cannot be automated. However, for you to have updated data, open the spreadsheet, and in this tab, press Refresh.<\/p>\n \u2013 To learn how you can automate this with Google Apps Script, click to read about it in our blog post How to Automatically Get Data From BigQuery to Google Sheets<\/a>.<\/p>[\/et_pb_text][et_pb_image src=”https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/09-results-and-options.webp” alt=”BigQuery Connection Edit Options in Google Sheets” title_text=”edit-bigquery-connection” _builder_version=”4.22.2″ width=”100%” global_colors_info=”{}” theme_builder_area=”post_content”][\/et_pb_image][et_pb_text _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”] Now that you have successfully created links between BigQuery and your Google Sheets, it\u2019s time to put that data to work!\u00a0Make sure to learn more about Google’s BigQuery in the following blog post: When does it make sense to use Google BigQuery?<\/a>.<\/p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]\n","protected":false},"excerpt":{"rendered":" What is BigQuery? BigQuery\u00a0is Google\u2019s solution to enterprise-level data storage. It is a cloud-based service that offers rapid SQL querying for big data at an affordable price. Because it is a Google product it is reliable, secure, and always improving. With BigQuery, large companies no longer have to manage their data warehouses with expensive, on-site […]<\/p>\n","protected":false},"author":40,"featured_media":10186,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"Get Started Using The BigQuery Data Connector<\/h3>\n
Step 1.<\/h4>\n
Step 2.<\/h4>\n
Step 3.<\/h4>\n
Step 4.<\/h4>\n
Step 5.<\/h4>\n
Step 6.<\/h4>\n
Step 7.<\/h4>\n
Step 8.<\/h4>\n
Step 9.<\/h4>\n
What is BigQuery?<\/h4>\nBigQuery is Google's solution to enterprise-level data storage. It is a cloud-based service that offers rapid SQL querying for big data at an affordable price. Because it is a Google product it is reliable, secure, and always improving. With BigQuery, large companies no longer have to manage their data warehouses with expensive, on-site hardware. BigQuery runs and backs up on Google's infrastructure. Google BigQuery allows users to take full advantage of Google product infrastructure. Today we are breaking down Google's new BigQuery connector for Google Sheets, and how you can use the free tool we developed specifically for automating the data transfer!<\/span>\n
<\/h4>\n
The New Google Sheets Data Connector<\/h4>\nGoogle has recently launched a new data connector for BigQuery and Google Sheets users! This is great news for data analysts who want to improve and automate the ease in which they manage data. This solution is designed for big data practitioners who want to use Sheets to crunch big numbers\u2014with this connector you can scan up to 1TB of BigQuery data to extract up to 10,000 rows of data into one sheet. This allows huge amounts of information to be analyzed in an intuitive and collaborative environment. Users who need to process even more data into a spreadsheet can follow our tutorial on how to get more than 10,000 rows using Sheetgo<\/a>.<\/span>\n
Main Features of The Connector<\/h4>\n
Limitations<\/h4>\nAs with all newly released tools, there are some limitations. Although we can be patient while Google improves this tool, it is good to be aware of what we can and cannot do.<\/span>\n\nMobile:<\/b> Currently, this tool is not mobile friendly. Although, you can view your results in mobile. So, you will need to run your queries on a computer but can shared results can be viewed by and commented on team members on mobile devices.<\/span>\n\nAutomation: <\/b>There are not currently automation features with this tool. We hope that this changes soon, but in the meantime, one of our Sheetgo engineers has created a free Google Apps Script that you can use<\/a> to automate your process. <\/span>\n\nHigh-volumes: <\/b>As mentioned before, although this connector supports HUGE data queries at a remarkably fast speed, if you want more than 10,000 rows in a single spreadsheet, you will have to use another tool<\/a>.<\/span>\n
<\/h4>\n \n
Get Started Using The BigQuery Data Connector<\/h4>\n \n\n <\/span><\/i>1. To run the Data Connector click Data \u2192 Data connectors \u2192 BigQuery<\/strong>.<\/span>\n\n
![\"\"](\"https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/01-opening-1024x836-1-1024x836.png\")
\n\n \n\n \n\n2. A window will open up in your Sheet. Select the billing project you want to work on and click Write Query.<\/strong><\/span><\/i>\n\n![\"\"](\"https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/02-selecting-billing-project-1024x836-1-1024x836.png\")
\n\n \n\n3. Now it is time to add some parameters to your query. Click Add<\/strong>.<\/span><\/i>\n\n![\"\"](\"https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/03-window-overview-1024x836-1-1024x836.png\")
\n\n \n\n \n\n4. Name your parameter something unique that you will remember, and choose a cell for reference.\n\n![\"\"](\"https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/04-adding-a-parameter-1024x836-1-1024x836.png\")
\n\n \n\n5. Great! You have added your first parameter. Now in the editor box type @ and the name of your parameter<\/strong>. In our example it is @MYPARAMETER.\n\n![\"\"](\"https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/05-parameter-added-1024x836-1-1024x836.png\")
\n\n \n\n6. I do not understand this screenshot. Can someone help out with this one? Thanks! I am just not familiar at all with these kinds of tools. <\/strong><\/i>\n\n![\"\"](\"https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/06-schema-guide-1024x836.webp\")
\n\n \n\n7. I do not understand this screenshot. Can someone help out with this one? Thanks! I am just not familiar at all with these kinds of tools. Maybe something needs to be explained between the differences in screenshot #7 and #8 - one has a syntax error?<\/strong>\n\n<\/i>![\"\"](\"https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/07-writing-a-bad-query-1024x836.webp\")
\n\n \n\n8. Click Insert Results<\/strong><\/span>\n\n![\"\"](\"https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/08-writing-a-good-query-1024x836.webp\")
\n\n \n\n \n\n9. The BigQuery Data Connector will automatically create a new tab in your spreadsheet with the results\n\n![\"\"](\"https:\/\/static.sheetgo.com\/wp-content\/uploads\/2018\/10\/09-results-and-options-1024x836.png\")
\n\n \n\n \nTime to Start Analyzing BigQuery Data<\/h4>\nNow that you have successfully created links between BigQuery and your Google Sheets, it's time to put that data to work! We are all about automating your data extraction processes so that you can use your valuable time on tasks that are important; like making data-driven business decisions that will make an impact. Depending on the kind of data you are processing, you might need to create reports, or run your numbers through more rigorous analytical tools.<\/span>\n\nThe great thing about using Google Sheets is that it is a super flexible tool, with tons of great ways to enhance its use. If you are not a data expert, don't worry, Google add-ons are here to help. (add a link to a previous blog about)<\/span>","_et_gb_content_width":"","footnotes":""},"categories":[37],"tags":[39,28],"class_list":["post-10172","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-google-sheets-features","tag-connections-t","tag-spreadsheets"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.sheetgo.com\/es\/wp-json\/wp\/v2\/posts\/10172","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.sheetgo.com\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.sheetgo.com\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.sheetgo.com\/es\/wp-json\/wp\/v2\/users\/40"}],"replies":[{"embeddable":true,"href":"https:\/\/www.sheetgo.com\/es\/wp-json\/wp\/v2\/comments?post=10172"}],"version-history":[{"count":0,"href":"https:\/\/www.sheetgo.com\/es\/wp-json\/wp\/v2\/posts\/10172\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.sheetgo.com\/es\/wp-json\/wp\/v2\/media?parent=10172"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.sheetgo.com\/es\/wp-json\/wp\/v2\/categories?post=10172"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.sheetgo.com\/es\/wp-json\/wp\/v2\/tags?post=10172"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}