Associate Data Practitioner: Google Cloud renames Looker Studio, Composer and Vertex AI

Associate Data Practitioner is Google Cloud's associate-level certification for people who work with data on the platform: ingestion and cleaning, storage, analysis with SQL and notebooks, Looker dashboards, BigQuery ML models, orchestrated pipelines and data governance. There are no prerequisites; Google recommends 6+ months of experience working with data on Google Cloud.

The notice on the page says two things: the exam will soon be updated to reflect recent branding changes, and you should refer to the exam guide for the product names used on the exam. Google gives no date for that update. The published guide today is v1.0, and it still says Looker Studio, Cloud Composer, Dataproc, Cloud Functions and Analytics Hub.

The format does not change: 2 hours, 50 to 60 multiple choice questions, USD 125 plus applicable tax, in English and Japanese, online with a remote proctor or at a test center. The certification is valid for 3 years and you renew it through Google Skills with the designated courses or skill badges in the renewal learning path.

The weights in guide v1.0 stay put too: Data Preparation and Ingestion ~30%, Data Analysis and Presentation ~27%, Data Pipeline Orchestration ~18% and Data Management ~25%. The announced change is about names, not about the outline.

Most of it landed in April 2026. On 3 April, Dataproc and Google Cloud Serverless for Apache Spark were unified in the console as Managed Service for Apache Spark; Google states that the Dataproc API, client library, gcloud CLI and IAM roles do not change. On 10 April, Dataplex Universal Catalog became Knowledge Catalog, again with the API, CLI and IAM names unchanged. On 15 April, Cloud Composer started evolving into Managed Service for Apache Airflow. On 16 April, Looker Studio was rebranded as Data Studio, and the paid tier now appears in the docs as Data Studio Pro.

On 22 April Google launched Gemini Enterprise Agent Platform as the evolution of Vertex AI. With it, almost everything that carried the Vertex AI prefix changes: Vertex AI Workbench is now Gemini Enterprise Agent Platform Workbench, Vertex AI Pipelines is Agent Platform Pipelines, and AutoML and Model Registry become AutoML and Model Registry on Gemini Enterprise Agent Platform. The Associate Data Practitioner guide names AutoML, Model Registry and Colab Enterprise without the prefix, so in this exam you will barely notice it.

Two older renames are not reflected in guide v1.0 either: Cloud Functions has been Cloud Run functions since 21 August 2024, and Analytics Hub has been BigQuery sharing since 9 April 2025.

The same branding notice appears on the Professional Data Engineer page, whose guide still talks about Cloud Composer (DAGs included), Dataproc, Dataplex and Dataplex Catalog, and writes BigQuery sharing (Analytics Hub). It also appears on Professional Cloud Database Engineer, although that guide uses none of the names in the table.

Other guides are already up to date. The Professional Machine Learning Engineer guide, dated 1 June 2026, refers to Agent Platform AutoML, Agent Platform Workbench, Agent Platform Pipelines and Managed Service for Apache Airflow. Associate Cloud Engineer uses Agent Runtime on Gemini Enterprise Agent Platform and gives the old name in brackets (Vertex AI Agent Engine). Cloud Digital Leader names Managed Service for Apache Spark and AutoML on Agent Platform, and Professional Cloud Architect and Generative AI Leader refer to Agent Platform and Model Garden. None of these pages shows the notice.

Study with the names in the guide, because those are the exam's names until Google updates it, but map each one to its new name. When you open the console or the docs you will see Data Studio, Managed Service for Apache Airflow, Managed Service for Apache Spark and Knowledge Catalog; if you go looking for Looker Studio or Cloud Composer, you will get lost.

What is assessed does not change. You still need to know when to use Looker versus Data Studio, choose between Dataflow, Managed Service for Apache Spark, Cloud Data Fusion, Managed Service for Apache Airflow and Dataform for a given case, schedule queries, build event-driven pipelines with Eventarc and decide when to share data with BigQuery sharing. If you know the use case, the label will not cost you a question.

If your date is close, do not move it because of the notice: the update is about names, and Google has not announced changes to content or weights. Check the exam page before your exam in case the guide changes. On CertifyDeck you have Associate Data Practitioner questions: more than 300, spread across the four sections of guide v1.0 with their weights, using the names the exam uses today, with an explanation for every question and a timed mock exam. Start free.