Add disclaimer for potential Analytics Hub deprecation and remove ref…

…erences elsewhere (#490)

* troubleshooting API

* Revert to gerund

Though the style guide says to just use imperatives, "get started" just sounds weird. Also this is more consistent with "troubleshooting"

* merge

* Merging

* add disclaimer about BQ and remove references from elsewhere

* one more mention

* uncommented xref

bigquery/index.md

@@ -9,10 +9,8 @@ has_children: true
 
 The Data Commons repository is available as BigQuery tables in the [Analytics Hub](https://console.cloud.google.com/bigquery/analytics-hub/exchanges(analyticshub:projects/841968438789/locations/us/dataExchanges/data_commons_17d0b72b0b2/listings/data_commons_1803e67fbc9){: target="_blank"}). If you have a Google Cloud Platform account, you can use Analytics Hub to issue SQL queries against the Data Commons tables. For more information, see the [Analytics Hub introduction](https://cloud.google.com/bigquery/docs/analytics-hub-introduction){: target="_blank"}. 
 
-**Tip:** Before you start, you may find it helpful to review Data Commons [key concepts](/data_model.html).
-
-In these pages are sample SQL queries grouped together by category. You can copy and paste the queries into the BigQuery Studio in the Cloud Console. In addition, all Data Commons visualization tools include a **Get BigQuery SQL** button, so you can also form queries by using the interactive tools on the website. For example:
+> **Note:** Analytics Hub is no longer being updated with Data Commons data, and the Data Commons tables may be turned down. If you want to continue to use this, please fill out [this form](https://docs.google.com/forms/d/1pqliyxlfb4Mle2a77TLdl_LPxRKdQF5uG86pKC9MDu4/edit?resourcekey=0-icbp8ZymR520Rq-r4tEajQ) to tell us about your use case.
 
-![Get BigQuery SQL button]({{site.url}}/assets/images/dc/bq1.png){: width="900"}
+**Tip:** Before you start, you may find it helpful to review Data Commons [key concepts](/data_model.html).
 
-![query]({{site.url}}/assets/images/dc/bq2.png){: width="600"}
+In these pages are sample SQL queries grouped together by category. You can copy and paste the queries into the BigQuery Studio in the Cloud Console. 

custom_dc/index.md

@@ -43,7 +43,6 @@ For the following use cases, a custom Data Commons instance is not necessary:
 | Natural language query interface                            | yes, using Google AI technologies and models  |  yes, using open-source models only<sup>1</sup>  |
 | REST APIs                                                   |  yes | yes, no additional setup needed |
 | Python and Pandas API wrappers                               |  yes  | yes, but requires additional setup<sup>2</sup> |
-| Bigquery interface  | yes | no
 | Google Spreadsheets                                         |  yes |  yes, but requires additional setup<sup>2</sup> |
 | Site access controls | n/a | yes, using any supported Cloud Run mechanisms<sup>3</sup> |
 | Fine-grained data access controls<sup>4</sup> |  no | n/a |

data_model.md

@@ -8,7 +8,7 @@ nav_order: 3
 # Key concepts and common tasks
 
 Whether you're just exploring the data on [datacommons.org](http://datacommons.org), using the programmatic APIs, or contributing data, it's helpful to have a basic understanding of some of the key concepts in Data Commons. Use the following guidance:
-- If you are only using Data Commons interactive tools, Google Sheets, CSV download, or BigQuery, you should at least be familiar with [entities](#entity) and [statistical variables](#statistical-variable). You may wish to just skip directly to those sections.
+- If you are only using Data Commons interactive tools, Google Sheets or CSV download, you should at least be familiar with [entities](#entity) and [statistical variables](#statistical-variable). You may wish to just skip directly to those sections.
 - If you plan to use the programmatic APIs, contribute data, or run your own Data Commons, you should read this entire page. 
 
 {:toc}

how_to_use.md

@@ -38,8 +38,6 @@ There are several options for directly querying the data, without accessing the
 
 - **Google Sheets Add-on**: You can load Data Commons data into Google Sheets for analysis and charting, using a familiar spreadsheet interface. Install and run the Data Commons Google [Sheets add-on](/api/sheets/index.html).
 
-- **BigQuery**: If you want to issue SQL queries, and you have a Google Cloud Platform account, you can use BigQuery Studio on Data Commons data in [Analytics Hub](https://cloud.google.com/analytics-hub){: target="_blank"}. See the [Data Commons in BigQuery](/bigquery/index.html) page for more details.
-
 ## Embed Data Commons visualizations in your website {#embed}
 
 Data Commons provides a [Web components API](/api/web_components/index.html) that makes it a snap to embed various chart elements in your own site, such as scatter plots, maps, pie charts, and many more, using the base Data Commons data.

index.md

@@ -30,9 +30,7 @@ The Data Commons [Knowledge Graph browser](https://datacommons.org/browser/){: t
 
 Importantly, numeric time series data are first-class entities, with "(statistical) variable" being an entity that represents a metric definition, and "observation" being an entity that represents the value of a variable at a specific time. The [Statistical Variable Explorer](https://datacommons.org/tools/statvar){: target="_blank"} allows you to browse existing variables, and the [Visualization tools](https://datacommons.org/tools/visualization){: target="_blank"} provide aggregated views of this data over time, geography, or 2-dimensional space. The APIs also allow you to directly query observations. 
 
-The knowledge graph is also mapped to relational tables that allow for [SQL querying](https://docs.datacommons.org/bigquery/){: target="_blank"} (requiring a [Google Cloud BigQuery](https://cloud.google.com/bigquery) account){: target="_blank"} and easier joining to other datasets outside of Data Commons. 
-
-<!--To learn more about the data model and key concepts, see [Key concepts](). -->
+To learn more about the data model and key concepts, see [Key concepts](data_model.md).
 
 ## An open-source project and website platform