LookML on Associate Data Practitioner — study topic

What you can expect on the exam

Configuring core modeling parameters. You may need to adjust primary LookML parameters, including dimensions, measures, and Explores, to alter data models and modify how Looker queries the underlying database.
Enhancing field presentation and structure. Be ready to apply parameters such as label, description, group_label, and value_format to dimensions and measures to guide end users in the field picker.
LookML dashboard definitions. Know the difference between interface-based dashboards and code-defined LookML dashboards stored alongside the data model in version control.

Where this appears on the exam

2 subdomains in 1 of 4 domains

Section 2
Data Analysis and Presentation
1. 2.2Visualize data and create dashboards in Looker given business requirements
  - Compare Looker and Looker Studio for different analytics use cases
  - Manipulate simple LookML parameters to modify a data model

Practice questions on this topic

2 questions

2.2 Visualize data and create dashboards in Looker given business requirements

Looker Dashboard Filters and Tiles

Compare Looker and Looker Studio for different analytics use cases

Looker vs Looker Studio

Practice this domain

LookMLFeature

Data StudioService BigQueryService LookerService DimensionConcept dimensionsConcept measuresConcept value_formatFeature SQLConcept

Points to what builds on itWorks with or alternative toHover or tap a line to see what connects the two

LookML is part of Looker From the official documentation: “Get the dashboard's LookML content from enterprise Looker.”
Dimension is part of LookML From the official documentation: “The LookML [`dimension`](/looker/docs/reference/param-field-dimension) parameter”
dimensions is part of LookML From the official documentation: “Name [dimensions](/looker/docs/reference/param-field-dimension), [measures](/looker/docs/reference/param-field-measure), and other LookML objects, using all lowercase letters and underscores for spaces.”
LookML configures Looker From the official documentation: “LookML tells Looker how to query data, so everyone in the organization can create easy-to-read reports and dashboards to explore patterns of data.”
measures is part of LookML From the official documentation: “Name [dimensions](/looker/docs/reference/param-field-dimension), [measures](/looker/docs/reference/param-field-measure), and other LookML objects, using all lowercase letters and underscores for spaces.”
SQL is part of LookML From the official documentation: “The LookML [`sql`](/looker/docs/reference/param-field-sql) parameter”
value_format is part of LookML From the official documentation: “Since the value of the `value_format` parameter is already enclosed in double quotes in LookML, any nested double quotes will need to be escaped using the backslash `\` character.”
BigQuery works with Data Studio From the official documentation: “Select the BigQuery [connector](/data-studio/connector).”
BigQuery works with Looker From the official documentation: “Connect Looker to the BigQuery project.”
Data Studio works with Looker From the official documentation: “See the [Connecting to Data Studio](/looker/docs/looker-studio-connector) documentation page to learn more about connecting Looker and Data Studio.”
BigQuery works with SQL From the official documentation: “You can also use Cloud Asset Inventory to transfer this data into BigQuery. This will allow you to query the data using SQL, which is easier to read compared to interpreting JSON-formatted data.”
Data Studio is an alternative to Looker From the official documentation: “You can also [export these recommendations to BigQuery](/recommender/docs/bq-export/export-recommendations-to-bq) and then examine them using [Data Studio](/bigquery/docs/visualize-looker-studio) or [Looker](/bigquery/docs/looker).”
Dimension is part of Data Studio From the official documentation: “There are two types of fields in Data Studio: - **Dimensions** are your categories or labels.”
SQL is part of Dimension From the official documentation: “Define a database table column in a LookML project once using the syntax `${TABLE}.field_name` in the dimension's `sql` parameter.”

LookML

What you can expect on the exam

Where this appears on the exam

Practice questions on this topic

2.2 Visualize data and create dashboards in Looker given business requirements

Compare Looker and Looker Studio for different analytics use cases

How learners score on this topic

LookML

What you can expect on the exam

Where this appears on the exam

Practice questions on this topic

2.2 Visualize data and create dashboards in Looker given business requirements

Compare Looker and Looker Studio for different analytics use cases

How learners score on this topic

What you can expect on the exam

Where this appears on the exam

Practice questions on this topic

2.2 Visualize data and create dashboards in Looker given business requirements

Compare Looker and Looker Studio for different analytics use cases

Related topics

How learners score on this topic

What you can expect on the exam

Where this appears on the exam

Practice questions on this topic

2.2 Visualize data and create dashboards in Looker given business requirements

Compare Looker and Looker Studio for different analytics use cases

Related topics

How learners score on this topic