Google introduces Data Clean Rooms in BigQuery

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           <div><h3>How to work with Google Analytics Hub</h3></div>
            <div><p>medium.com</p></div>
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    </div><p id="0476">Users normally share many types of data that also have more stringent regulatory and privacy requirements. Therefore, a Data Clean Room can be a good solution. It is a technology service that helps content platforms keep first person user data private when interacting with partners.</p><figure id="e84d"><img src="https://cdn-images-1.readmedium.com/v2/resize:fit:800/0*CwImr_6m48EyJV59.jpg"><figcaption>Data Clean Rooms in BigQuery — Image by Google[2]</figcaption></figure><p id="d0d2">The concept of a Data Clean Room is to keep user data isolated and private. A Data Clean Room provides aggregated and anonymized user information to protect user privacy, while providing advertisers with non-personally identifiable information to target a specific demographic and for audience measurement [3].</p><p id="e125">Use cases for Data Clean Rooms can be for example:</p><ul><li>Retailers can optimize marketing and promotional activities by combining their data with external advertisers [2][3].</li><li>Financial Service enterprises can improve fraud detection by combining sensitive data from other financial and government agencies [2].</li><li>In the healthcare industry, doctors and pharmaceutical resea

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rchers can share data within a clean room to learn how patients are reacting to treatments [2].</li></ul><p id="af89">In addition to these examples, it should also be interesting for companies that want to exchange data within an organization, for example, but are active in different areas, countries, etc.. Here, too, this technical solution makes it possible to exchange data that was previously not possible in terms of guidelines or laws.</p><div id="7bf5" class="link-block"> <a href="https://readmedium.com/google-launches-cdc-for-bigquery-826e3dcb0d49"> <div> <div> <h2>Google launches CDC for BigQuery</h2> <div><h3>Change Data Capture in Real Time using BigQuery API</h3></div> <div><p>medium.com</p></div> </div> <div> <div style="background-image: url(https://miro.readmedium.com/v2/resize:fit:320/1*F5GbesweLXbZ06wkLeuuMw.jpeg)"></div> </div> </div> </a> </div><h2 id="dda4">Sources and Further Readings</h2><p id="abde">[1] Google, <a href="https://cloud.google.com/bigquery/docs/release-notes">Release Notes</a> (2022)</p><p id="104b">[2] Google, <a href="https://cloud.google.com/blog/products/data-analytics/introducing-bigquery-data-clean-rooms">Secure and privacy-centric sharing with data clean rooms in BigQuery</a> (2023)</p><p id="fcd1">[3] TechTarget, <a href="https://www.techtarget.com/searchcustomerexperience/definition/data-clean-room">data clean room</a> (2023)</p></article></body>

How to share secure and private Data in BigQuery Cleaning Rooms

Last year, Google has launched Analytics Hub built on BigQuery, which lets customers share and exchange data cost-effectively, while helping to minimize data movement challenges [1].

Now, they have announced the launch of Data Clean Rooms for Q3 as an integrated service for their Data Warehouse BigQuery. Google says that Data Clean Rooms will be available in all BigQuery regions through Analytics Hub, and can be created and deployed in minutes. Customers can use Google Cloud console or APIs to create secure clean room environments, and invite partners or other participants to contribute data [2].

Users normally share many types of data that also have more stringent regulatory and privacy requirements. Therefore, a Data Clean Room can be a good solution. It is a technology service that helps content platforms keep first person user data private when interacting with partners.

Data Clean Rooms in BigQuery — Image by Google[2]

The concept of a Data Clean Room is to keep user data isolated and private. A Data Clean Room provides aggregated and anonymized user information to protect user privacy, while providing advertisers with non-personally identifiable information to target a specific demographic and for audience measurement [3].

Use cases for Data Clean Rooms can be for example:

Retailers can optimize marketing and promotional activities by combining their data with external advertisers [2][3].

Financial Service enterprises can improve fraud detection by combining sensitive data from other financial and government agencies [2].

In the healthcare industry, doctors and pharmaceutical researchers can share data within a clean room to learn how patients are reacting to treatments [2].

In addition to these examples, it should also be interesting for companies that want to exchange data within an organization, for example, but are active in different areas, countries, etc.. Here, too, this technical solution makes it possible to exchange data that was previously not possible in terms of guidelines or laws.

Google introduces Data Clean Rooms in BigQuery

How to share secure and private Data in BigQuery Cleaning Rooms

Using BigQuery and Google Analytics Hub

How to work with Google Analytics Hub

Google launches CDC for BigQuery

Change Data Capture in Real Time using BigQuery API

Sources and Further Readings