Creating and editing Explores

When you need to answer business questions, uncover trends, or validate hypotheses, you can explore and analyze your data in Looker without writing SQL. Explores provide an intuitive workspace where you can create queries, tailor fields, and format results to share insights with your team.

You can start your analysis from a blank Explore, choose from curated or AI-generated starter questions, or ask questions in natural language. As you refine your query, you can add fields, sort and pivot data, and calculate custom metrics to uncover the insights that matter most to you.

Whether you start with a blank Explore or use starter questions to run prebuilt or AI-generated queries, you can use the Configure panel to manage your query by adding or removing fields. You can further customize your results by sorting, pivoting, or reordering columns, as well as displaying totals. You can also monitor query progress with the Explore query tracker or access specific features for developers.

For more information about the components of an Explore, see the Viewing and interacting with Explores documentation page.

Required roles

You must have specific roles and permissions to perform the following functions in Explores:

Starting with a blank Explore

When you open a blank Explore in Looker or clear an existing Explore, you have several options for getting started:

Using starter questions

Once you have opened an Explore, you can use starter questions to create a starting point for quickly running and building analyses. Starter questions can be modeled queries or can be generated by Gemini.

Starter questions are displayed in the Starter Questions panel in the Configure tab, and in the Starter Questions menu in a blank Explore. You can open the Starter Questions panel by clicking the Show starter questions button.

Each starter question displays the name of the question and, when available, a description.

If generated starter questions are enabled for your instance, when you select an Explore from the Explore menu that doesn't already have defined starter questions, Gemini in Looker will give you an option to Try AI Starter Questions. Click Add, and Gemini will analyze the Explore and generate starter questions.

You can open a starter question from a blank Explore or once an Explore has already been run .

Choosing a starter question from a blank Explore

To run a starter question, click the Starter Questions menu, and choose the starter question that you want to explore. The query will automatically run and display results, including the visualization.

You can modify a starter question query once it has run by adding fields or removing fields from the All Fields tab, from Search results, or from the Fields in use tab in the Configure panel.

Choosing a starter question once an Explore has run

Once an Explore has finished running, you can select a new starter question by clicking the Show starter questions button to open the Starter Questions panel, which displays the available starter questions.

Clicking a starter question from the panel runs the query and replaces all the previous Explore results, except for any existing filters.

Starter question filter behavior

Filters are additive. This means that, when run, starter question queries will include any existing Explore filters. If a selected starter question has a filter that conflicts with an existing Explore filter, you will be prompted to select which filter value to use in the Explore query.

When you choose a starter question with a conflicting filter configuration, the Choose filter set dialog will open and prompt you to resolve the conflict by selecting either the Keep current filters option, which lists the existing filter configuration, or the Replace with new filters option, which lists the configured filter values of the starter question query.

To resolve the conflict in the Choose filter set dialog, follow these steps:

  1. Choose an option.
    • Choose Keep current filters to run the new query with the existing filter configuration.
    • Choose Replace with new filters to run the new query with its configured filter condition.
  2. Click Apply to confirm the filter selection and run the query.

The Explore will run with the selected filter configuration.

Once you have opened an Explore, you can use the Configure panel to create, edit, and configure Explore queries and visualizations. The Configure panel includes the following elements:

  1. The Close button: When clicked, closes the Configure panel. Alternatively, use the Configure button to display or hide the Configure panel.
  2. The All Fields tab: Displays all available fields for an Explore.
  3. The Fields in use tab: Displays all the Explore fields that are selected in the query.
  4. The Style tab: Displays the options for configuring the query visualization. Learn more about using the Style tab to configure visualizations.
  5. The name of the Explore.
  6. The number of fields that are selected in the Explore query.
  7. The Explore Summary info button: When clicked, displays a description of the Explore that was either added by a developer, or generated by Gemini in Looker.
  8. The search bar: Lets users search for fields that match specific terms and criteria.
  9. The Explore views: Displays the views that are included in the Explore, and the number of fields from that view that are in the Explore query. Click the name of the view to expand or collapse the view details. When expanded, each view lists the fields that are available to use in the Explore, organized under field type headers: Dimensions, Measures, and Filter-Only Fields. Custom fields and table calculations will appear under the Custom Fields view label.
  10. The field-specific information and actions icons: Display a field's current and potential functions in an Explore query, as well as more details about a field.
  11. The Clear all and Clear fields keep filters options: When clicked, Clear all clears all of the Explore fields, and Clear fields keep filters clears the Explore fields but keeps any filters that are applied.
  12. The Merge queries (join data) button: Opens the Join data page. Learn more about joining data.
  13. The Explore summary: Displays the total number of fields in an Explore (including custom fields and table calculations when permissions allow), and the Go to LookML link. The Go to LookML link directs users to the explore definition in its LookML project. This link is visible only to users with the see_lookml permission.

Using the field-specific information and actions icons

The icons next to each field provide more information about the field and indicate the available options for that field. The icons are visible when you hold your cursor over a field.

You can click an icon to make changes to a query by using a field, depending on the field's data type, including filtering or pivoting by a field. You can also use icons to view information about a field, or — when permissions allow — to create a custom field that is based on the field.

These icons appear on the All Fields and Fields in use tabs.

The available icons and functions include the following:

  1. The Pivot data icon: Click this icon to pivot or unpivot a field in an Explore. This icon will persist next to a field name when a field is pivoted. Click the persisted icon to remove the pivot. Learn more about pivoting data.

  2. The Filter by field icon: Click this icon to filter the query results by a field. This icon will persist next to a field name when a field is filtered. Click the persisted icon to remove the filter.

  3. The Info icon: Click this icon to display more information about a field:

    • The information includes the field's data type, description (when available), and LookML field name (in view_name.field_name syntax) for all users.
    • For users with the see_lookml permission, the information will include the definition of the LookML field's sql parameter, as well as a link to navigate to that field in the LookML project.

  4. The More menu: Click this icon to create a custom field or to switch a timeframe for a dimension group. This icon is available only to users in certain cases:

    • When a user has the create_custom_fields permission. Users with the create_custom_fields permission can use the More menu to quickly create custom fields, depending on a field's type.
    • When a dimension group is selected in the Explore query. The Switch to option will appear for dimension groups on the Fields in use tab, in addition to custom fields options.

Using the data column More menu

In addition to the field-specific information and action icons, you can edit a query and visualization with the options in the data column More menu.

The options that are displayed depend on the field type and a user's permissions.

For dimensions and measures, the data column More menu options can include the following:

  • Remove: Removes the column field from the Explore query.
  • Filter: Filters the Explore query by the column field. Learn more about filtering data.
  • Remove Filter: Removes a filter field. This option is available when an Explore is filtered by the field.
  • Pivot: Pivots a field in an Explore query. Learn more about pivoting data.
  • Unpivot: Unpivots a field in an Explore query. This option is available when a field is pivoted, and in the pivot row More menu.
  • Switch to: Displays a list of timeframes for dimension groups that users can switch between in a query.
  • Hide from visualization: Hides the column field from the visualization. If a field is hidden from the visualization, this option appears as Show in visualization. Learn more about hiding fields from visualizations.
  • Hide "No"s from visualization: For yesno type fields, hides the rows that correspond to "No"s from the visualization. If "No"s are hidden from the visualization, this option appears as Show "No"s in visualization. Learn more about yesno type fields.
  • Calculations: Displays a list of shortcut calculations to let users who have the create_table_calculations permission create a table calculation that is based on the column field. This option is available only for non-string-based data types.
  • Copy values: Copies all the values from a table column to paste into a document or a tool like Excel or Google Sheets.
  • Bin: Opens the Bin dialog to let users who have the create_custom_fields permission create custom bins that are based on the column field. Custom bins are available only for certain field types.
  • Group: Opens the Group By dialog to let users who have the create_custom_fields permission create a custom group that is based on the column field. Custom groups are available only for certain field types.
  • Sort: Sorts the query by the column field in either Ascending or Descending order. Learn more about sorting data.
  • Add additional sort: Sorts the query by a secondary column field in either Ascending or Descending order. Learn more about sorting data. This option is only available if an Explore is already sorted by a different field.

In addition to the previous options, data column More menu options for table calculations and custom fields can include the following:

  • Duplicate: Duplicates the table calculation or the custom field in the query.
  • Edit or Edit Calculation: Opens a dialog for editing a table calculation or editing a custom field.
  • Delete: Permanently deletes a custom field or table calculation from an Explore query and the Configure panel. To remove a custom field or a table calculation from the Explore query, but not from the Configure panel, use the Remove option.

Using the All Fields tab

When you open an existing Explore, the All Fields tab is displayed by default. This tab is the starting place for building an Explore and displays all the available fields that you can select for a query. Fields are organized alphanumerically by type (dimensions, followed by measures) under the name of the view or view label in which they are defined. Each field will show field-specific information and actions, such as a field's current and potential functions in an Explore query.

Click the name of the view to expand or collapse the view details. When expanded, each view lists the fields that are available to use in the Explore, organized under field type headers: Dimensions, Measures, and Filter-Only Fields. Custom fields and table calculations will appear under the Custom Fields view label. Users with the create_table_calculations permission can create and edit table calculations, and users with the create_custom_fields permission can create and edit custom fields by clicking + Add, or by choosing a custom field option from a field's More menu.

Fields that are selected in a query will appear highlighted by a background, and any applied field action icons (pivot, filter) will appear in bold.

You can click Clear all to remove all of the fields from the Explore, or click Clear fields keep filters to clear the Explore fields but keep any filters that are applied.

Using the Fields in use tab

The Fields in use tab provides a snapshot of the Explore, including the chart type that is selected in the Visualization pane, and all of the fields that are active in an Explore, organized alphanumerically by view or view label, and under the corresponding field type headers (Dimensions, Measures, and Filter-Only Fields).

The Fields in use tab also displays the total number of active fields in an Explore in the Explore summary. A Go to LookML link is also available to users with the see_lookml permission. Go to LookML directs users to the explore definition in its LookML project.

You can click fields to remove them from an Explore, click Clear all to remove all of the fields from the Explore, or click Clear fields keep filters to clear the Explore fields but keep any filters that are applied.

The search bar lets you quickly find the specific fields that you need to build Explores. To perform a search, enter a term into the search bar.

To refine the scope of your search, click Search Options. You can limit your search to field labels, field descriptions, group labels, or view labels.

Adding fields

You can add fields to queries in one of several ways:

Once you have added all of the fields that you want in the Explore query, click Run to update.

To perform more advanced analyses on your data, users with the create_table_calculations permission can add table calculations, and users with the create_custom_fields permission can add custom fields to the Explore query.

Removing fields

You can remove fields from queries in several ways:

  • By clicking an individual field name in the All Fields tab, or in the Fields in use tab.
  • By clicking Clear all in the Fields in use tab to remove all of the fields in an Explore query.
  • By clicking Clear fields keep filters in the Fields in use tab to remove all of the fields in the Explore query, but keep any filters that are applied to the Explore query.
  • By clicking Remove from the data column More menu.
  • For custom fields and table calculations, by clicking Delete from the data column More menu. Learn more about removing and deleting table calculations and removing and deleting custom fields.

Once you have removed all of the fields that you want to remove from the Explore query, click Run to update.

Sorting data

Unpivoted data is sorted by default according to the following prioritization:

  1. By the first date dimension, descending
  2. If no date dimension exists, by the first measure, descending
  3. If no measure exists, by the first added dimension, ascending

For information on sorting pivoted data, see the Pivots and sorting section.

A field's sort order is indicated in the data table in several ways:

  • With a number and an ^ upward-facing or ⌄ downward-facing arrow next to the field name that distinguishes its sort-by order and sort direction, as compared to other fields
  • With an arrow next to the field name that indicates the sorting direction (^ pointed up for ascending or ⌄ down for descending)
  • With a tooltip that appears when you hold the pointer over a field name

You may want to sort data differently than the default order. You can sort by clicking a field's column header in the data table to sort the query by that field:

  • Click a field's column header once to sort by that field in descending order.
  • Click a field's column header twice to sort that field in ascending order.

Alternatively, you can click the Sort option in the field's data column More menu.

To sort multiple fields, hold down the Shift key and then click the column headers in the order that you want them sorted. Alternatively, you can click the Add additional sort option in the field's data column More menu.

Things to know about sorting

  • Some sorting in Explores is performed on the client side (in the user's browser) to reduce the number of round-trip calls to databases, which can be both costly and time consuming. However, this behavior can lead to inconsistencies between Explore results and other Looker content, as sorting between client and database can produce different results — especially if system locales differ.
  • If you reach a row limit, you won't be able to sort row totals or table calculations.
  • Any sorting that is applied in the Visualization pane (and not in the Data pane) is a temporary client-side operation and won't persist when an Explore is saved as a Look or as a dashboard tile.

Pivoting data

Multiple dimensions are often easier to look at when you pivot one of the dimensions horizontally. Each value in the dimension will become a column in your query. This makes the information easier to consume visually and reduces the need to scroll to find data. Looker supports up to 200 pivoted values.

To pivot results by a dimension, follow these steps:

  1. In the All Fields or Fields in use tab, position your cursor over the dimension name and click the Pivot data icon.

    Alternatively, click the Pivot option in a field's data row More menu.

  2. Click Run to update to re-run the query.

You can add an additional field to the pivot table by dragging the field from the All Fields tab and dropping it into the Data pane, and then specifying if the new field should be a column or row (for dimensions), or a value (for measures and table calculations).

You can unpivot a field by clicking the dimension's Pivot data icon from either the All Fields tab or the Fields in use tab. Alternatively, you can click the Unpivot option from a field's data row More menu.

Pivots and sorting

You can also sort pivoted dimensions by clicking the field name header of the dimension in the data table, or by clicking the Sort option in the field's data row More menu menu.

To sort by multiple pivoted dimensions, hold down the Shift key and then click the row headers in the order that you want them sorted. Alternatively, you can click the Add additional sort option in the field's data row More menu. When you're sorting a pivoted measure, any rows with values in that column are sorted first, followed by rows without data in that column (indicated by the ∅ null value symbol).

Reordering columns

You can reorder columns in the data table in the Data pane by clicking a column header and dragging and dropping the column to its new position. The visualization will reflect the new column order after you click the Run to update button.

The order of columns in the data table is based on field type:

  1. Dimensions (including custom fields)
  2. Dimension table calculations
  3. Measures (including custom fields)
  4. Measure table calculations
  5. Row totals

For the most part, columns can be reordered within each field type but cannot be moved out of their field type section.

For example, dimension table calculations can be rearranged among themselves, but you cannot place a dimension table calculation in between two measures.

Columns under a pivoted dimension can be reordered, but the order of pivoted dimensions can be changed only by changing the sort order, not by manual reordering.

Displaying totals

Sometimes a summary of your data is useful. You can add column or row totals to a query by clicking the Totals or Subtotals switch in the data table and then rerunning the query.

If you've added row totals, and your query exceeds any row limit that you've set, you won't be able to sort the Row Totals column (although you can sort dimension and measure columns as normal). This is because you might be missing rows in your data that should be included in your totals. If you run into this issue, you can try increasing the query's row limit to 5,000 rows (or up to 50,000 rows if a higher limit is specified by your admin).

When totals aren't available

There are some cases when totals won't be available:

  • Column totals are available only for measures and table calculations that exclusively reference measures, not for dimensions or table calculations that reference dimensions.
  • Row totals are available only for measures, not for dimensions or table calculations that are based on dimensions.
  • Certain types of columns won't be totaled, because of database limitations or because the value wouldn't make sense as a total. For example, you can't add together a list of words.

Things to consider with totals

Additionally, there are some things to keep in mind about how totals work in certain situations:

  • Columns that count unique items might not add up as you expect, since the same item might show up in several categories but be counted as only one unique item in the totals. See the Why don't my totals match the values in my table? Best Practices page for more details.
  • The Row Totals feature creates an additional query, and this query has a limit of 30,000 rows. If your Explore query has more than 30,000 rows, row totals will be shown for the first 30,000 rows only. Furthermore, if the data is pivoted, the row totals limit is further reduced by the number of options in your pivot.
  • Some table calculations that perform aggregations, such as calculations that use percentile or median, might not add up as you expect. This is because table calculations calculate totals by using the values in the Total row, not the values in the data column. See the Display potentially confusing table calculation totals as nulls Best Practices page for troubleshooting tips.
  • If you've filtered your query by a measure, totals may appear to be too high. However, in actuality, what you're seeing is a total for your data before the measure filter is applied. In other words, the measure filter may be hiding some data from your query results, even though that data is included in the total.
  • If you've used totals with merged results, Looker calculates totals on each of the component queries and uses those totals in the merged result. Therefore, totals may appear too high, because what you are seeing are totals calculated before the results were merged. One way to avoid this is to align the filters on each query.
  • Similarly, if you've placed row or column limits on your query, and your query results exceed that limit, totals may also appear to be too high. However, what you're seeing is a total for your data before the limits are applied. In other words, the limits may be hiding some data from your query results, even though that data is included in the total.

In the situations involving merged results, it is possible to calculate totals only for the data that you can see. To do so, you'll need to use a table calculation. For a column total, use sum(${view_name.field_name}). For a row total, use sum(pivot_row(${view_name.field_name})).

Explore query tracker

If either the Explore Visualization pane or the Data pane is open, the Explore query tracker, which lets you view the query's progress, appears while an Explore query is running.

Features for developers

Depending on your permissions, you may see several features that are designed for Looker developers in the Configure panel:

  • The Go to LookML option on the All Fields and Fields in use tabs lets developers navigate to the Explore LookML.
  • The Go to LookML option in a field's Filter actions menu in the Filters pane lets developers navigate to the field's LookML.
  • The sql parameter definition in a field's Info icon menu lets developers see a field's sql definition without needing to navigate to the field's LookML.
  • The Go to LookML option in a field's Info icon menu lets developers see the field's LookML.
  • The SQL query button in the Data pane lets Looker developers see the SQL query that Looker sends to the database to retrieve the data.
  • The Explore query tracker lets Looker developers track the performance and execution of the Explore query.

Now that you know how to create and edit Explores, you can learn about other features in Looker: