Product update: Data connectors, insights visualizations, and data tooling

Data Connectors: Import from Amazon S3 and Snowflake, export to Meta Ads and S3

It’s now even easier to integrate Decentriq into your existing advertising workflows. This quarter, we added built-in connectors to Amazon S3, Snowflake, and Meta Ads Manager to make it simpler to import encrypted datasets and export encrypted audiences and insights directly to these platforms.

Users can now directly import datasets from Amazon S3 and Snowflake, and use those datasets in multiple DCRs. You can also export any dataset or computation result to Amazon S3 or Meta Ads Manager. Export to Amazon S3 gives publishers a straightforward way to push audiences directly from the clean room to their S3-compatible supply-side platform (SSP).

For further analysis, you can also download the results as a CSV.

Microsoft Azure and Google Cloud are next on the agenda, so if these are strategic platforms for you, watch our release notes page for more frequent product updates!

Media clean rooms: Agency seat, visualizations, multiple participants

The no-code interface in our media & advertising clean rooms also saw improvements this quarter. The biggest change is the addition of an Agency role. This allows an agency that manages media and advertising campaigns for a brand to build audience segments, see insights on the match rate, reach, and affinity, and choose on behalf of the advertiser which audiences to activate.

We have enhanced the clarity of the top affinity segment insights, emphasizing the best affinity ratios, and introduced new visualizations in the form of interactive charts.

We now also support multiple participants: Previously, only one main user on the publisher-side and one user advertiser-side could participate in a clean room. Now, many users from both sides can join, making it possible for the whole team to participate in and manage the data collaboration.

The new test mode helps you query with confidence

Test modes for both new and published clean rooms help users test new scripts and queries and verify that they perform as expected before applying them to a live clean room.

In draft Data Clean Rooms, users can upload test data and run computations even before publishing. Published DCRs now have a “test mode” that allows you to provide test data to all tables and run all computations on these data before requesting changes.

Auto-fixing and column matching for higher dataset quality, faster

To take the pain out of uploads and dataset matching, we introduced new features that automate parts of the process of preparing datasets for use in a clean room. After upload, customers can re-map columns by selecting from dropdowns in the table header. Data is automatically flagged for validation issues, and typical errors are flagged and fixed automatically. This improves match rates, gives users more confidence in data quality, and offers more flexibility in which datasets they can use.

Reuse datasets and computation results across multiple DCRs

For all datasets, organizations can now store encryption keys securely in their Decentriq Keychain. This makes it possible to reuse that same dataset in other DCRs without needing to upload it again.

Computation results can also be stored as a dataset and used in other DCRs. For advertising use cases, this gives clean room participants the ability to re-use audiences they built in one clean room, for example across multiple publishers.

We release new features on a rolling basis — you can stay up-to-date on all our product updates by following our release notes.