{"id":18649,"date":"2021-10-08T20:03:20","date_gmt":"2021-10-08T14:33:20","guid":{"rendered":"http:\/\/ismiletechnologies.com\/?p=18649"},"modified":"2021-11-10T17:14:36","modified_gmt":"2021-11-10T11:44:36","slug":"how-can-we-use-bigquery-in-preparing-data-studio","status":"publish","type":"post","link":"https:\/\/ismiletechnologies.com\/en_us\/data-science\/how-can-we-use-bigquery-in-preparing-data-studio\/","title":{"rendered":"How can we use BigQuery in preparing Data studio?"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"18649\" class=\"elementor elementor-18649\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-3ded8eed elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3ded8eed\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-271022e2\" data-id=\"271022e2\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5372299 elementor-widget elementor-widget-text-editor\" data-id=\"5372299\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span class=\"TextRun SCXW153036776 BCX0\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW153036776 BCX0\">Before we dive into the use of BigQuery in preparing Google Data Studio, let\u2019s take a moment to briefly have an idea about what is BigQuery, what is Google Data Studio and Google Data Studio BigQuery connector.\u00a0<\/span><\/span> <span class=\"TextRun SCXW153036776 BCX0\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW153036776 BCX0\">\u00a0<\/span><\/span><span class=\"EOP SCXW153036776 BCX0\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:276}\">\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6220aff elementor-widget elementor-widget-heading\" data-id=\"6220aff\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">What is Big Query?   <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1322f72 elementor-widget elementor-widget-text-editor\" data-id=\"1322f72\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span data-contrast=\"none\">Big Query is an analytics data warehouse that lets users analyze large amounts of data in almost near real-time. Think of it like running a query in SQL, only at a much larger scale. Google Cloud provides it and, therefore, is a <span style=\"color: #333399;\"><a style=\"color: #333399;\" href=\"http:\/\/ismiletechnologies.com\/cloud-services\/\">cloud-based service<\/a><\/span> that doesn\u2019t require the user to set up or manage the infrastructure.\u00a0\u00a0<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/p><p><span data-contrast=\"none\">However, with such a powerful data analytics tool, there comes the issue of interpreting all of that data, which is where Data Studio comes in.\u00a0\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e1d168d elementor-widget elementor-widget-heading\" data-id=\"e1d168d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">What is Data Studio?   <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-77060b3 elementor-widget elementor-widget-text-editor\" data-id=\"77060b3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span class=\"TextRun SCXW92760602 BCX0\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW92760602 BCX0\">Data Studio is another Google service that allows you to <span style=\"color: #333399;\"><a style=\"color: #333399;\" href=\"http:\/\/ismiletechnologies.com\/data-and-analytics\/\">turn data \u00a0<\/a><span style=\"color: #333333;\">into understandable graphs and reports<\/span><\/span>.\u00a0\u00a0<\/span><\/span><span class=\"EOP SCXW92760602 BCX0\" data-ccp-props=\"{\">\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-de2ede9 elementor-widget elementor-widget-heading\" data-id=\"de2ede9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">What is DataStudio BigQuery Connector?  <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f295361 elementor-widget elementor-widget-text-editor\" data-id=\"f295361\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span data-contrast=\"none\">So, the Google data studio BigQuery connector helps access the data from your BigQuery tables within Google data studio.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:276}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"none\">Before we dive into the use of BigQuery, we just have a piece of information that BigQuery is automatically enabled in new projects and a preexisting project; we can activate it using the BigQuery API.\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7ca11f5 elementor-widget elementor-widget-heading\" data-id=\"7ca11f5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">The Steps:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1194018 elementor-widget elementor-widget-text-editor\" data-id=\"1194018\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul>\n<li data-leveltext=\"\u25cf\" data-font=\"Symbol\" data-listid=\"1\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"none\">Creating a Data Source: The first step is to create a data source for the report in Google Data Studio. Here we can define a report as a collection of one or more data sources.\u00a0\u00a0<\/span><\/li>\n<li data-leveltext=\"\u25cf\" data-font=\"Symbol\" data-listid=\"1\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\">Connect to Big Query: After opening a new blank report in Google Data Studio, there will be a \u2018add data to report\u2019 tab, and in that, you can search \u2018BigQuery.\u2019 In the Google connectors section, you will see a BigQuery box, hover over it and select it.\u00a0\u00a0<span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559740&quot;:276}\">\u00a0<\/span><\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4848652 elementor-widget elementor-widget-image\" data-id=\"4848652\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"602\" height=\"318\" src=\"https:\/\/ismiletechnologies.com\/wp-content\/uploads\/2021\/10\/image-23.png\" class=\"attachment-full size-full wp-image-18652\" alt=\"DataStudio BigQuery Connector\" srcset=\"https:\/\/ismiletechnologies.com\/wp-content\/uploads\/2021\/10\/image-23.png 602w, https:\/\/ismiletechnologies.com\/wp-content\/uploads\/2021\/10\/image-23-300x158.png 300w\" sizes=\"(max-width: 602px) 100vw, 602px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6f39563 elementor-widget elementor-widget-text-editor\" data-id=\"6f39563\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span class=\"TextRun SCXW53787736 BCX0\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW53787736 BCX0\">After clicking on it, the configuration panel appears; select \u2018PUBLIC DATASETS,\u2019 then select dataset samples, choose your Billing project, and click on connect. A field panel will appear which contains all the dimensions and metrics from the data set.\u00a0\u00a0<\/span><\/span><span class=\"EOP SCXW53787736 BCX0\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:276}\">\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-07ae81e elementor-widget elementor-widget-text-editor\" data-id=\"07ae81e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul>\n<li data-leveltext=\"\u25cf\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"none\">Visualizing the data: After we have a data source for Data Studio, we can now focus on visualization. To create a chart of any kind, simply click on the dataset in your report and click \u201cInsert.\u201d From there, you can see an enormous drop-down list of charts to choose from. Here is an example from a pre-set dataset from Google of different populations of countries.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559740&quot;:276}\">\u00a0<\/span><\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cbabbba elementor-widget elementor-widget-image\" data-id=\"cbabbba\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"602\" height=\"274\" src=\"https:\/\/ismiletechnologies.com\/wp-content\/uploads\/2021\/10\/image-25.png\" class=\"attachment-full size-full wp-image-18653\" alt=\"Visualizing the data\" srcset=\"https:\/\/ismiletechnologies.com\/wp-content\/uploads\/2021\/10\/image-25.png 602w, https:\/\/ismiletechnologies.com\/wp-content\/uploads\/2021\/10\/image-25-300x137.png 300w\" sizes=\"(max-width: 602px) 100vw, 602px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b92dd97 elementor-widget elementor-widget-text-editor\" data-id=\"b92dd97\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span class=\"TextRun Highlight  BCX0 SCXW215198640\" data-contrast=\"none\"><span class=\"NormalTextRun  BCX0 SCXW215198640\">As we can see, there are lots of different charts available to use from Data Studio. Even more, once we select a particular chart, on the right side, there will be two types of editing tools, one for data and one for design. Let\u2019s look a the pie chart as an example:<\/span><\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0e2ad77 elementor-widget elementor-widget-image\" data-id=\"0e2ad77\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"602\" height=\"415\" src=\"https:\/\/ismiletechnologies.com\/wp-content\/uploads\/2021\/10\/image-26.png\" class=\"attachment-full size-full wp-image-18654\" alt=\"Visualizing the data 2\" srcset=\"https:\/\/ismiletechnologies.com\/wp-content\/uploads\/2021\/10\/image-26.png 602w, https:\/\/ismiletechnologies.com\/wp-content\/uploads\/2021\/10\/image-26-300x207.png 300w\" sizes=\"(max-width: 602px) 100vw, 602px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-98a38dc elementor-widget elementor-widget-text-editor\" data-id=\"98a38dc\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span data-contrast=\"none\">We can see the dimensions by which the populations are measured, change the data metrics, and sort the countries into different orders. From the style side, we can decide how many slices the chart has, the colors, the font and size of the legend, and much more.\u00a0\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:276}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"none\">This way, we can use BigQuery to add a database to Google Data Studio and use it for visualization purposes.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:276}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"none\">So, if you are interested in more detail of these steps, here\u2019s the link of the source that I have used for the blog\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:276}\">\u00a0<\/span><\/p>\n<p><a href=\"https:\/\/cloud.google.com\/bigquery\/docs\/visualize-data-studio\"><span data-contrast=\"none\"><span style=\"color: #333399;\">https:\/\/cloud.google.com\/bigquery\/docs\/visualize-data-studio<\/span><\/span><\/a><span style=\"color: #333399;\">\u00a0\u00a0<br \/><a style=\"color: #333399;\" href=\"https:\/\/support.google.com\/datastudio\/answer\/6295968?hl=en#zippy=%2Cin-this-article\">https:\/\/support.google.com\/datastudio\/answer\/6295968?hl=en#zippy=%2Cin-this-article<\/a>\u00a0\u00a0<\/span><\/p>\n<p><span data-contrast=\"none\"><br \/><\/span><span data-contrast=\"none\">This is <span style=\"color: #000000;\">Harshit Dave<\/span>, Data Science Intern at iSmile Technologies. Thanks for reading.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Before we dive into the use of BigQuery in preparing Google Data Studio, let\u2019s take a moment to briefly have an idea about what is BigQuery, what is Google Data Studio and Google Data Studio BigQuery connector.&nbsp; &nbsp;&nbsp; What is Big Query? Big Query is an analytics data warehouse that lets users analyze large amounts [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":20492,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[74],"tags":[],"class_list":["post-18649","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-science"],"_links":{"self":[{"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/posts\/18649","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/comments?post=18649"}],"version-history":[{"count":16,"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/posts\/18649\/revisions"}],"predecessor-version":[{"id":20493,"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/posts\/18649\/revisions\/20493"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/media\/20492"}],"wp:attachment":[{"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/media?parent=18649"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/categories?post=18649"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/tags?post=18649"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}