What's changed: Created Associate Data Practitioner Chapter 2 (Domain 2 "Analysis and presentation": analysis with BigQuery and notebooks = SQL/Colab Enterprise; dashboards with Looker = Looker/Looker Studio/LookML; using ML models = BigQuery ML/AutoML/LLM via remote connection/standard ML project/Model Registry).
2.2Dashboards with Looker
Understand creating, modifying, and sharing dashboards to answer business questions, choosing between Looker and Looker Studio, and manipulating basic LookML parameters that define the data model.
Analysis becomes valuable when visualized so stakeholders can see it and decide. Google Cloud business intelligence (BI) is Looker.
2.2.1Dashboards and Looker / Looker Studio
Looker is a BI platform to create, modify, and share dashboards to answer business questions. The similarly named Looker Studio is a lighter, more accessible visualization tool for ad-hoc reports and smaller visualizations. Looker, by contrast, suits enterprise use that values governance and consistency via a central LookML data model. Map "lightweight visualization = Looker Studio" and "governed enterprise BI with a central model = Looker."
2.2.2LookML
LookML is the language that defines the data model in Looker. By defining measures and dimensions once, users build dashboards on consistent definitions (everyone’s "revenue" is computed the same way). Associate Data Practitioner asks you to manipulate simple LookML parameters to modify the data model.
Common: requirement → tool. E.g., "answer questions/share via dashboards" = Looker; "lightweight, ad-hoc visualization" = Looker Studio; "consistency/governance via a central data model" = LookML (Looker); "unify metric definitions" = LookML.
Watch the mix-ups: (1) do not confuse Looker (central model, enterprise BI) with Looker Studio (lightweight visualization). (2) LookML is Looker’s data-model language. (3) Visualization is a separate step from analysis (BigQuery).
2.2.3Section summary
- Looker = enterprise BI answering questions via dashboards (central model); Looker Studio = lightweight visualization
- LookML = defines Looker’s data model and keeps metrics consistent
- Choose Looker vs Looker Studio by use case
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Quick check
(just a quick review)Q1. To value governance via a central data model and share dashboards consistently enterprise-wide, which is best?
Q2. Which lightweight, more accessible visualization tool suits ad-hoc reports?
Q3. Which language defines the data model in Looker and keeps metric calculations consistent?
Q4. Which best describes the main purpose of a dashboard?
Q5. Which best describes a key benefit of using LookML?
Q6. Which correctly contrasts Looker and Looker Studio?