Migrating Looker Dashboards to Holistics

High-level Overview

Looker Dashboard Types vs Holistics Dashboard

Looker has two types of dashboards:

• LookML Dashboard: Version-controlled dashboards defined in code, managed by LookML developers
• User-defined Dashboard: UI-based dashboards created via drag-and-drop in Personal or Shared folders

Holistics takes a unified approach with a single dashboard type that supports both UI and code editing modes. This eliminates the need to convert between different dashboard types - users can build visually and the code is automatically generated.

Component Mapping

Looker Component	Holistics Equivalent	Notes
Query Tile	Visualization Block	Created from explores/datasets
Look-linked Tile	N/A	Holistics doesn't have standalone reports
Text Tile	Text Block	For adding text, markdown content
Extension Tile	N/A	For custom extensions
Dashboard Filters	Filter Block	For filtering dashboard data

Dashboard Settings Comparison

Feature	Looker	Holistics	Notes
Timezone Adjustment	✅	✅	Both platforms support
Run on Load	✅	✅	Load data automatically on dashboard open
Full-screen Mode	✅	✅	Expand visualizations to full screen
Auto-refresh	✅	Coming soon	Automatic data refresh intervals
Default Filter View	✅	N/A	Holistics uses inline filters
Filter Panel Location	Fixed positions	Flexible	Place filters anywhere in layout

Visualization Type Mapping

When migrating from Looker to Holistics, you'll need to map your existing visualizations to their Holistics equivalents. This table provides a comprehensive mapping between Looker visualization types and their Holistics counterparts:

Looker Visualization	Holistics Equivalent	Notes
Column Chart	Column Chart	Standard vertical bar visualization for category comparison
Bar Chart	Bar Chart	Horizontal bar visualization for category comparison
Line Chart	Line Chart	Ideal for time series and trend analysis
Area Chart	Area Chart	Shows volume and cumulative values over time
Pie Chart	Pie/Donut Chart	Visualizes part-to-whole relationships
Scatter Plot	Scatter Chart	Shows correlation between two numeric variables
Table	Table	Tabular data presentation with formatting options
Single Value	KPI Metric	Displays a single metric with optional comparison
Box Plot	❌ Not natively supported yet	Available through Holistics Custom Chart
Waterfall Chart	Custom Waterfall Chart	Shows sequential contribution to a final value
Funnel Chart	Funnel Chart	Visualizes sequential process or conversion rates
Word Cloud	Word Cloud	Text visualization with size indicating frequency

Additional Holistics Visualizations

Holistics offers several visualization types that aren't available in Looker:

• Metric Sheet - Compact display of multiple KPIs in a grid layout
• Pivot Table - Advanced table with nested rows and columns for complex data analysis
• Gauge Chart - Visual representation of a metric within a defined range
• Bubble Chart - Enhanced scatter plot with third dimension shown by bubble size
• Radar Chart - Multi-variable data visualization on axes starting from the same point

When migrating dashboards, you'll typically map most Looker visualizations directly to their Holistics equivalents, while potentially enhancing your dashboards with these additional visualization types.

Step-by-Step Migration Tutorial

Step 1: Preparation

1. Open your source Looker dashboard
2. Create a new dashboard in Holistics
3. List all components to migrate:
   • Visualization tiles
   • Text content
   • Filters
   • Dashboard settings

Step 2: Migrate Visualizations

1. For each query tile:

    Dashboard your_dashboard {
       title: 'Dashboard Title'
   
       block block_name: VizBlock {
           label: 'Visualization Label'
           viz: ChartType {  // ChartType can be BarChart, DataTable, LineChart, PieChart, ScatterPlot, Table, etc.
               dataset: dataset_name
               // other visualization settings
           }
       }
   
    }

2. For each text tile:

   Dashboard your_dashboard {
       title: 'Dashboard Title'
   
       block t5: TextBlock {
           content: @md Your markdown content here;;
       }       
   
    }

Step 3: Set Up Filters

Dashboard your_dashboard {
    title: 'Dashboard Title'

    block block_name: VizBlock { }
    
    block block_name: FilterBlock {
        label: 'Filter Label'
        type: 'field'
        source: FieldFilterSource {
            dataset: dataset_name
            field: ref('model_name', 'field_name')
        }
        default {
            operator: 'is'
            value: []
        }
    }

}

Step 4: Configure Dashboard Settings

Dashboard your_dashboard {
    title: "Your Dashboard Title"
    description: "Dashboard description"

    settings {
        timezone: 'America/Los_Angeles'
        autorun: false
        cache_duration: 10
    }

}

Step 5: Test and Validate

1. Compare visualization outputs
2. Verify filter functionality
3. Test dashboard loading performance
4. Check mobile responsiveness
5. Validate user permissions

Common Migration Patterns

This section demonstrates how to migrate common dashboard components from Looker to Holistics.

1. Basic Dashboard Structure

Looker Dashboard Structure

- dashboard: sales_overview
  title: "Sales Overview"
  description: "Sales performance metrics and trends"
  enable_viz_full_screen: true
  layout: tile | static | grid | newspaper
  refresh: "1 hour"
  auto_run: true
  width: 1500  # For layout: static dashboards

Holistics Dashboard Structure

Dashboard sales_overview {
  title: "Sales Overview"
  description: "Sales performance metrics and trends"

  settings {
    autorun: true
  }

  view: CanvasLayout {
    width: 1560    // Dashboard width in pixels
    height: 1080   // Dashboard height in pixels
  }
}

Note:

• Holistics uses a simpler dashboard configuration model with Canvas layout by default. While Looker supports multiple layout types (tile, static, grid, newspaper), Holistics provides a flexible canvas where blocks can be freely positioned.
• Features like refresh intervals are not currently supported.

2. Filter Configuration

Looker Filter Configuration

- dashboard: sales_overview
  crossfilter_enabled: true 
  filters:
    - name: order_status
      title: "Order Status"
      type: field_filter
      model: sales
      explore: orders
      field: orders.status
      default_value: "completed"
      allow_multiple_values: true
      ui_config:
        type: dropdown_menu
        display: popover

Holistics Filter Configuration

Dashboard your_dashboard {
  block status_filter: FilterBlock {
    label: "Order Status"
    type: "field"
    source: FieldFilterSource {
      dataset: orders
      field: ref('orders', 'status')
    }
    settings {
      input_type: 'multiple'
    }
    default {
      operator: "is"
      value: 'completed'
    }
  }
}

Note:

• Holistics filter configuration is more streamlined and has cross-filtering ability by default.
• But currently doesn't support advanced UI configurations available in Looker.

3. Visualization Elements (Cartesian Chart)

Looker Visualization Elements (Cartesian Chart)

- dashboard: sales_overview
  tile_size: 100
  
  elements:
    - name: monthly_sales
      title: "Monthly Sales"
      type: looker_column # Looker Column Chart 
      height: 4  # sets an element to be 400 pixels in height (when tile_size is 100)
      width: 5  # sets an element to be 500 pixels in width (when tile_size is 100)
      top: 7  # position the element 700 pixels from the top of the dashboard
      left: 8  # position the element 800 pixels from the left of the dashboard

      ## QUERY PARAMETERS
      model: sales
      explore: orders
      fields: [orders.created_month, orders.total_revenue]
      fill_fields: [orders.created_month]
      sorts: [orders.created_month desc]
      limit: 500

Holistics Visualization Elements (Cartesian Chart)

Dashboard your_dashboard {

    block block_name: FilterBlock { }

    block monthly_sales: VizBlock {
        label: "Monthly Sales"
        viz: ColumnChart {
            dataset: orders
            x_axis {
                field: VizFieldFull {
                    ref: ref('orders', 'created_month')
                    transformation: 'datetrunc month'
                }
            }
            y_axis {
                series {
                    field: VizFieldFull {
                        ref: ref('orders', 'total_revenue')
                    }
                }
            }
            settings {
                row_limit: 500
                sort {
                    field_index: 0
                    direction: 'desc'
                }
            }
        }
    }

    view: CanvasLayout {
        block monthly_sales {
            position: pos(800, 700, 500, 400)  // position the element 800 pixels from the left of the dashboard, 700 pixels from the top, 500 pixels wide, and 400 pixels tall
        }
    }

}

Note: While both platforms support similar visualization capabilities, Holistics uses a more structured approach to defining chart components`.

4. Visualization Elements (Data Table)

Looker Visualization Elements (Data Table)

- dashboard: sales_overview
  tile_size: 100
  
  elements:
    - name: monthly_sales
      title: "Monthly Sales"
      type: looker_grid # Looker Data Table 
      height: 4  # sets an element to be 400 pixels in height (when tile_size is 100)
      width: 5  # sets an element to be 500 pixels in width (when tile_size is 100)
      top: 7  # position the element 700 pixels from the top of the dashboard
      left: 8  # position the element 800 pixels from the left of the dashboard

      ## QUERY PARAMETERS
      model: ecommerce
      explore: orders
      fields: [products.name, orders.total_orders_count, orders.gmv, orders.aov]

Holistics Visualization Elements (Data Table)

Dashboard your_dashboard {

    block block_name: FilterBlock { }
    
    block product_performance: VizBlock {
    label: 'Product Performance'
    viz: DataTable {
      dataset: demo_ecommerce
      fields: [
        VizFieldFull {
          ref: ref('products', 'name')
          format { } // Viz Field Format Configuration 
        },
        VizFieldFull {
          label: 'Total Orders'
          ref: ref('orders', 'total_orders_count')
          format { } // Viz Field Format Configuration 
        },
        VizFieldFull {
          label: 'GMV'
          ref: ref('orders', 'gmv')
          format { } // Viz Field Format Configuration 
        },
        VizFieldFull {
          label: 'AOV'
          ref: ref('orders', 'aov')
          format { } // Viz Field Format Configuration 
        }
      ]
      settings { } // Viz Settings Configuration 
    }
  }

    view: CanvasLayout {
        block product_performance {
            position: pos(800, 700, 500, 400)  // position the element 800 pixels from the left of the dashboard, 700 pixels from the top, 500 pixels wide, and 400 pixels tall
        }
    }   

}

5. Visualization Elements (Pivot Table)

Looker Visualization Elements (Pivot Table)

- dashboard: sales_overview
  tile_size: 100
  
  elements:
    - name: order_by_country_and_status
      title: "Total Orders by Countries & Order Status"
      type: looker_grid # Looker Data Table 
      height: 4  # sets an element to be 400 pixels in height (when tile_size is 100)
      width: 5  # sets an element to be 500 pixels in width (when tile_size is 100)
      top: 7  # position the element 700 pixels from the top of the dashboard
      left: 8  # position the element 800 pixels from the left of the dashboard
    
    ## QUERY PARAMETERS
    model: ecommerce
    explore: orders
    fields: [countries.name, orders.status, orders.total_orders_count]
    pivots: [orders.status]

Holistics Visualization Elements (Pivot Table)

Dashboard your_dashboard {

    block block_name: FilterBlock { }
    
    block order_by_country_and_status: VizBlock {
    label: 'Total Orders by Countries & Order Status'
    viz: PivotTable {
      dataset: demo_ecommerce
      rows: [
        VizFieldFull {
          ref: ref('countries', 'name')
          format { } // Viz Field Format Configuration 
        }
      ]
      columns: [
        VizFieldFull {
          ref: ref('orders', 'status')
          format { } // Viz Field Format Configuration 
        }
      ]
      values: [
        VizFieldFull {
          ref: ref('orders', 'total_orders_count')
          format { } // Viz Field Format Configuration 
        }
      ]
      settings { } // Viz Settings Configuration 
    }
  }

    view: CanvasLayout {
        block order_by_country_and_status {
            position: pos(800, 700, 500, 400)  // position the element 800 pixels from the left of the dashboard, 700 pixels from the top, 500 pixels wide, and 400 pixels tall
        }
    }
    
}

Note: Looker doesn't support pivot type explicitly, but it can be achieved by using looker_grid type with pivots parameters.

6. Text and Markdown Content

Looker Text Elements

- dashboard: sales_overview
    layout: tile
    tile_size: 100
    
    elements:
    - name: dashboard_intro
      type: text
      height: 4  # sets an element to be 400 pixels in height (when tile_size is 100)
      width: 5  # sets an element to be 500 pixels in width (when tile_size is 100)
      top: 7  # position the element 700 pixels from the top of the dashboard
      left: 8  # position the element 800 pixels from the left of the dashboard

      ## TEXT PARAMETERS
      title_text: "Welcome"
      subtitle_text: "Overview"
      body_text: "
        This dashboard shows:
         • Daily revenue trends
         • Order status breakdown
      "

Holistics Text Elements

Dashboard your_dashboard {

    block block_name: FilterBlock { }
    block block_name: VizBlock { }

    block dashboard_intro: TextBlock {
    content: @md
      # Welcome
      ## Overview
      
      This dashboard shows:
      
      * Daily revenue trends
      * Order status breakdown
    ;;
  }

    view: CanvasLayout {
        block dashboard_intro {
            position: pos(800, 700, 500, 400)  // position the element 800 pixels from the left of the dashboard, 700 pixels from the top, 500 pixels wide, and 400 pixels tall
        }
    }
}

Note: Holistics uses Markdown syntax for text formatting, providing a more familiar editing experience for developers.

Detailed Feature Comparison

LookML Parameter	Purpose	Support	Holistics Equivalent & Implementation
Dashboard Parameters
dashboard	Create a dashboard.	✅	Using Holistics Dashboard syntax Dashboard your_dashboard { }
title (for dashboard)	Change the way a dashboard name appears to users.	✅	Using title: 'Dashboard Title'
description (for dashboard)	Add a description to a dashboard.	✅	Using description: 'Dashboard description'
enable_viz_full_screen	Define whether dashboard viewers can see dashboard tiles in full-screen and expanded views.	❌	Users can see full-screen VizBlock by default and admins/analysts cannot control this
extends	Base the LookML dashboard on another LookML dashboard.	✅	Using Holistics AML Extend
extension	Require that the dashboard is extended by another dashboard.	✔️ (partial)	No direct equivalent, but can create AML Func for a Dashboard
layout	Start a section of LookML to define the elements that should go into each row of a layout: grid dashboard.	❌	Not supported yet, but default, our dashboard will be layout as canvas.
elements (for rows)	Define the elements that should go into a row of a layout: grid dashboard.	❌	Holistics doesn't support grid layout.
height (for rows)	Define the height of a row for a layout: grid dashboard.	❌	Holistics doesn't support grid layout.
tile_size	Define the size of a tile for a layout: tile dashboard.	❌	Not supported yet.
width (for dashboard)	Define the width of the dashboard for a layout: static dashboard.	✅	Can change both width and height of a Dashboard via view: CanvasLayout { width: 1560 height: 1080 }
refresh (for dashboard)	Set the interval on which dashboard elements will automatically refresh. Note that the dashboard must be open in a browser window for this parameter to have an effect. This setting does not run in the background to "pre-warm" the dashboard cache.	❌	Not suppported yet.
auto_run	Determine whether dashboards run automatically when initially opened or reloaded.	✅	By default, the Dashboard is auto-run, but users can disable it by using settings { autorun: false }
Filter Parameters
crossfilter_enabled	Enable or disable cross-filtering for a dashboard.	✅	Holistics support cross-filtering by default
filters_bar_collapsed	Set the dashboard filter bar as default collapsed or expanded for a dashboard.	❌	Holistics doesn't have dedicated filter bar as filters can place anywhere in the dashboard
filters_location_top	Set the dashboard filter bar location as top or right for a dashboard.	✅	Users can position filters anywhere in the dashboard
filters (for dashboard)	Start a section of LookML to define dashboard filters.	✅	Using block block_name: FilterBlock { }
name (for filters)	Create a filter.	✅	Using block block_name: FilterBlock { }
title (for filters)	Change the way a filter name appears to users.	✅	Using label: 'Filter Label'
type (for filters)	Determine the type of filter to be used.	✅	Using type: 'field'
default_value	Set a default value for a filter, if desired.	✅	Using default { operator: 'is', value: ['value1', 'value2'] }
allow_multiple_values	Limit users to a single filter value.	✅	Using settings { input_type: 'single' }
required	Require that a filter is selected.	❌	Not supported yet.
ui_config	Configure the filter controls that are available when users view a LookML dashboard. Has subparameters type, display, and options.	❌	Not supported yet.
model (for filters)	Specify the model that contains the underlying field of a type: field_filter filter.	✅	No equivalent in Holistics
explore (for filters)	Specify the Explore that contains the underlying field of a type: field_filter filter.	✅	Using dataset: dataset_name
field	Specify the underlying field of a type: field_filter filter.	✅	Using field: ref('model_name', 'field_name')
listens_to_filters	Narrow suggestions for dashboard filters of field_filter based on what the user enters for another dashboard filters of type: field_filter.	✅	Holistics Parrent-child filter
Common Chart Parameters
name (for elements)	Creates a new dashboard element and assigns it a name.	✅	Using block block_name: VizBlock { }
title (for elements)	Changes how an element's name will appear to users.	✅	Using label: 'Element Label'
type (for elements)	Determines the type of visualization to be used in the element.	✅	Using viz: ChartType { }
height (for elements)	Defines the height of an element in units of tile_size.	✅	specify height in position: pos(left, top, width, height) inside view: CanvasLayout { }
width (for elements)	Defines the width of an element in units of tile_size.	✅	specify width in position: pos(left, top, width, height) inside view: CanvasLayout { }
top	Defines the top-to-bottom position of an element in units of tile_size.	✅	specify top in position: pos(left, top, width, height) inside view: CanvasLayout { }
left	Defines the left-to-right position of an element in units of tile_size.	✅	specify left in position: pos(left, top, width, height) inside view: CanvasLayout { }
row	Defines the top-to-bottom position of an element in units of rows for layout: newspaper dashboards	❌	Holistics doesn't support newspaper layout yet
col	Defines the left-to-right position of an element in units of columns for layout: newspaper dashboards	❌	Holist ics doesn't support newspaper layout yet
refresh (for elements)	Sets the interval at which the element will automatically refresh.	❌	Not supported yet
note	Starts a section of LookML to define a note for an element.	✅	Using description: 'your block description or note'
Query Parameters
model	Defines the model to be used for the element's query.	✅	Using dataset: dataset_name
explore (for elements)	Defines the Explore to be used for the element's query.	✅	Using dataset: dataset_name
dimensions	Defines the dimensions to be used for the element's query.	✅	Use - x_axis with LineChart, BarChart of ColumnChart - fields: [] with DataTable - rows: [] with Pivot Table
measures	Defines the measures to be used for the element's query.	✅	Use - y_axis with LineChart, BarChart of ColumnChart - fields: [] with DataTable - values: [] with Pivot Table
sorts	Defines the sorts to be used for the element's query.	✅	Using sort { field_index: 0, direction: 'desc' }
pivots	Defines the dimensions that should be pivoted for the element's query.	✅	Using - legend: with Cartesian Charts - columns: [] with Pivot Table
limit	Defines the row limit to be used for the element's query.	✅	Using settings { row_limit: 10000 }
column_limit	Defines the column limit to be used for the element's query.	❌	Not supported yet
filters (for elements)	Defines the filters that cannot be changed for the element's query.	✅	Use filter { }
listen	Defines the filters that can be changed for the element's query.	✅	Support via interactions: [ FilterInteraction {} ]
query_timezone	Defines the time zone that should be used when the query is run.	❌	Follow Dashboard Timezone
merged_queries	Defines a merged results query.	❌	Not supported yet
hidden_fields	Specifies any fields to use in the query but hide in the chart.	✅	Use hidden: true inside VizFieldFull {}
Plot Parameters for Cartesian Charts
stacking	Specifies how series are stacked in the visualization.	✅	Using - settings { stack_series_by: 'value' } - settings { stack_series_by: 'percentage' }
show_dropoff	Shows a dropoff marker for column charts.	❌	Not supported yet
ordering	Specifies how bars or columns are ordered within groups.	✅	Use sort {} inside setting of a VizBlock
column_spacing_ratio	Sets the spacing between columns.	❌	Not supported yet
column_group_spacing_ratio	Sets the spacing between column groups.	❌	Not supported yet
hide_legend	Hides the chart legend.
legend_position	Specifies the position of the legend.
limit_displayed_rows	Shows or hides rows in a visualization based on position.
swap_axes	Swaps the x and y axes.
interpolation	Specifies how points are connected in line and area charts.
show_null_points	Shows null values in the visualization.
discontinuous_nulls	Breaks the line or area at null values.
cluster_points	Groups points that are close together in scatter charts.
Plot Parameters for Pie and Donut Charts
value_labels	Changes how individual sections of a pie chart are labeled.
label_type	Customizes the format of labels that mark sections of a pie chart.
inner_radius	Determines the inner radius of a pie chart (donut chart).
charts_across	Specifies the number of donut charts per row.
Plot Parameters for Progression Charts
smoothedBars	Connects the outer edge of each bar in funnel charts.
isStepped	Displays the funnel chart in stepped funnel style.
orientation	Specifies whether data is drawn from rows or columns.
labelScale	Specifies the size of labels on chart bars and sides.
Value Parameters
show_value_labels	Shows labels next to data points.
show_null_labels	Shows labels for null values.
label_color	Specifies the color for value labels.
font_size	Sets the font size of value labels.
label_rotation	Sets the rotation of value labels.
label_value_format	Specifies the number format for value labels.
show_totals_labels	Shows total values for stacked visualizations.
hidden_series	Hides specific series from the visualization.
show_silhouette	Shows a silhouette of the entire chart.
totals_color	Specifies the color for total labels.
Series Parameters
colors	Sets the colors of chart series based on order.
series_colors	Sets the colors of chart series based on series name.
series_labels	Changes the way a series name appears to users.
series_types	Assigns different chart types to individual series.
show_view_names	Shows view names in chart labels.
point_style	Specifies the style of points in line and scatter charts.
series_point_styles	Sets point styles for specific series.
size_by_field	Specifies a field to determine point size in scatter charts.
plot_size_by_field	Enables sizing points by a field value.
X-Axis Parameters
x_axis_scale	Specifies the scale type for the x-axis.
x_axis_reversed	Reverses the direction of the x-axis.
show_x_axis_label	Shows a label on the x-axis.
x_axis_label	Specifies a label for the x-axis.
show_x_axis_ticks	Shows value labels on the x-axis.
x_axis_gridlines	Shows gridlines from the x-axis.
x_axis_label_rotation	Sets the rotation of x-axis labels.
x_axis_datetime_label	Specifies a format for datetime x-axis labels.
x_axis_zoom	Enables zooming on the x-axis.
Y-Axis Parameters
y_axis_gridlines	Shows gridlines from the y-axis.
y_axis_reversed	Reverses the direction of the y-axis.
reference_lines	Adds reference lines or regions to the chart.
y_axis_zoom	Enables zooming on the y-axis.
leftAxisLabelVisible	Shows a label on the left axis.
leftAxisLabel	Specifies a label for the left axis.
rightAxisLabelVisible	Shows a label on the right axis.
rightAxisLabel	Specifies a label for the right axis.
Text Tile Parameters
title_text	Specifies a title for a text element.
subtitle_text	Specifies a subtitle for a text element.
body_text	Specifies body text for a text element.
Single Value Parameters
custom_color_enabled	Enables custom color for single value visualization.
custom_color	Specifies a custom color for text in single value visualization.
show_single_value_title	Shows a title with the query's value.
single_value_title	Specifies a title to display with the query's value.
valueFormat	Specifies the number format for the value.
show_comparison	Adds comparison information to a single value element.
comparison_type	Specifies how the comparison field is used.
show_comparison_label	Shows a label with the comparison field.
comparison_label	Specifies the label for the comparison field.
comparison_reverse_colors	Reverses colors for negative/positive comparisons.
Quadrant Parameters for Scatter Charts
quadrants_enabled	Enables quadrant divisions in scatter charts.
quadrant_properties	Configures properties for each quadrant.
custom_quadrant_point_x	Sets the x-coordinate for quadrant division.
custom_quadrant_point_y	Sets the y-coordinate for quadrant division.
custom_quadrant_value_x	Sets the x-value for quadrant division.
custom_quadrant_value_y	Sets the y-value for quadrant division.