AI/BI Dashboard Skill

Create Databricks AI/BI dashboards (formerly Lakeview dashboards). Follow these guidelines strictly.

CRITICAL: MANDATORY VALIDATION WORKFLOW

You MUST follow this workflow exactly. Skipping validation causes broken dashboards.

┌─────────────────────────────────────────────────────────────────────┐ │ STEP 1: Get table schemas via get_table_details(catalog, schema) │ ├─────────────────────────────────────────────────────────────────────┤ │ STEP 2: Write SQL queries for each dataset │ ├─────────────────────────────────────────────────────────────────────┤ │ STEP 3: TEST EVERY QUERY via execute_sql() ← DO NOT SKIP! │ │ - If query fails, FIX IT before proceeding │ │ - Verify column names match what widgets will reference │ │ - Verify data types are correct (dates, numbers, strings) │ ├─────────────────────────────────────────────────────────────────────┤ │ STEP 4: Build dashboard JSON using ONLY verified queries │ ├─────────────────────────────────────────────────────────────────────┤ │ STEP 5: Deploy via create_or_update_dashboard() │ └─────────────────────────────────────────────────────────────────────┘

WARNING: If you deploy without testing queries, widgets WILL show "Invalid widget definition" errors!

Available MCP Tools

Tool Description

get_table_details

STEP 1: Get table schemas for designing queries

execute_sql

STEP 3: Test SQL queries - MANDATORY before deployment!

get_best_warehouse

Get available warehouse ID

create_or_update_dashboard

STEP 5: Deploy dashboard JSON (only after validation!)

get_dashboard

Get dashboard details by ID, or list all dashboards (omit dashboard_id)

delete_dashboard

Move dashboard to trash

publish_dashboard

Publish (publish=True ) or unpublish (publish=False ) a dashboard

Implementation Guidelines

1. DATASET ARCHITECTURE (STRICT)

• One dataset per domain (e.g., orders, customers, products)

• Exactly ONE valid SQL query per dataset (no multiple queries separated by ; )

• Always use fully-qualified table names: catalog.schema.table_name

• SELECT must include all dimensions needed by widgets and all derived columns via AS aliases

• Put ALL business logic (CASE/WHEN, COALESCE, ratios) into the dataset SELECT with explicit aliases

• Contract rule: Every widget fieldName must exactly match a dataset column or alias

2. WIDGET FIELD EXPRESSIONS

CRITICAL: Field Name Matching Rule The name in query.fields MUST exactly match the fieldName in encodings . If they don't match, the widget shows "no selected fields to visualize" error!

Correct pattern for aggregations:

// In query.fields: {"name": "sum(spend)", "expression": "SUM(spend)"}

// In encodings (must match!): {"fieldName": "sum(spend)", "displayName": "Total Spend"}

WRONG - names don't match:

// In query.fields: {"name": "spend", "expression": "SUM(spend)"} // name is "spend"

// In encodings: {"fieldName": "sum(spend)", ...} // ERROR: "sum(spend)" ≠ "spend"

Allowed expressions in widget queries (you CANNOT use CAST or other SQL in expressions):

For numbers:

{"name": "sum(revenue)", "expression": "SUM(revenue)"} {"name": "avg(price)", "expression": "AVG(price)"} {"name": "count(orders)", "expression": "COUNT(order_id)"} {"name": "countdistinct(customers)", "expression": "COUNT(DISTINCT customer_id)"} {"name": "min(date)", "expression": "MIN(order_date)"} {"name": "max(date)", "expression": "MAX(order_date)"}

For dates (use daily for timeseries, weekly/monthly for grouped comparisons):

{"name": "daily(date)", "expression": "DATE_TRUNC("DAY", date)"} {"name": "weekly(date)", "expression": "DATE_TRUNC("WEEK", date)"} {"name": "monthly(date)", "expression": "DATE_TRUNC("MONTH", date)"}

Simple field reference (for pre-aggregated data):

{"name": "category", "expression": "category"}

If you need conditional logic or multi-field formulas, compute a derived column in the dataset SQL first.

3. SPARK SQL PATTERNS

• Date math: date_sub(current_date(), N) for days, add_months(current_date(), -N) for months

• Date truncation: DATE_TRUNC('DAY'|'WEEK'|'MONTH'|'QUARTER'|'YEAR', column)

• AVOID INTERVAL syntax - use functions instead

4. LAYOUT (6-Column Grid, NO GAPS)

Each widget has a position: {"x": 0, "y": 0, "width": 2, "height": 4}

CRITICAL: Each row must fill width=6 exactly. No gaps allowed.

Recommended widget sizes:

Widget Type Width Height Notes

Text header 6 1 Full width; use SEPARATE widgets for title and subtitle

Counter/KPI 2 3-4 NEVER height=2 - too cramped!

Line/Bar chart 3 5-6 Pair side-by-side to fill row

Pie chart 3 5-6 Needs space for legend

Full-width chart 6 5-7 For detailed time series

Table 6 5-8 Full width for readability

Standard dashboard structure:

y=0: Title (w=6, h=1) - Dashboard title (use separate widget!) y=1: Subtitle (w=6, h=1) - Description (use separate widget!) y=2: KPIs (w=2 each, h=3) - 3 key metrics side-by-side y=5: Section header (w=6, h=1) - "Trends" or similar y=6: Charts (w=3 each, h=5) - Two charts side-by-side y=11: Section header (w=6, h=1) - "Details" y=12: Table (w=6, h=6) - Detailed data

5. CARDINALITY & READABILITY (CRITICAL)

Dashboard readability depends on limiting distinct values:

Dimension Type Max Values Examples

Chart color/groups 3-8 4 regions, 5 product lines, 3 tiers

Filters 4-10 8 countries, 5 channels

High cardinality Table only customer_id, order_id, SKU

Before creating any chart with color/grouping:

• Check column cardinality (use get_table_details to see distinct values)

• If >10 distinct values, aggregate to higher level OR use TOP-N + "Other" bucket

• For high-cardinality dimensions, use a table widget instead of a chart

6. WIDGET SPECIFICATIONS

Widget Naming Convention (CRITICAL):

• widget.name : alphanumeric + hyphens + underscores ONLY (no spaces, parentheses, colons)

• frame.title : human-readable name (any characters allowed)

• widget.queries[0].name : always use "main_query"

CRITICAL VERSION REQUIREMENTS:

Widget Type Version

counter 2

table 2

filter-multi-select 2

filter-single-select 2

filter-date-range-picker 2

bar 3

line 3

pie 3

text N/A (no spec block)

Text (Headers/Descriptions):

• CRITICAL: Text widgets do NOT use a spec block!

• Use multilineTextboxSpec directly on the widget

• Supports markdown: # , ## , ### , bold , italic

• CRITICAL: Multiple items in the lines array are concatenated on a single line, NOT displayed as separate lines!

• For title + subtitle, use separate text widgets at different y positions

// CORRECT: Separate widgets for title and subtitle { "widget": { "name": "title", "multilineTextboxSpec": { "lines": ["## Dashboard Title"] } }, "position": {"x": 0, "y": 0, "width": 6, "height": 1} }, { "widget": { "name": "subtitle", "multilineTextboxSpec": { "lines": ["Description text here"] } }, "position": {"x": 0, "y": 1, "width": 6, "height": 1} }

// WRONG: Multiple lines concatenate into one line! { "widget": { "name": "title-widget", "multilineTextboxSpec": { "lines": ["## Dashboard Title", "Description text here"] // Becomes "## Dashboard TitleDescription text here" } }, "position": {"x": 0, "y": 0, "width": 6, "height": 2} }

Counter (KPI):

• version : 2 (NOT 3!)

• widgetType : "counter"

• Percent values must be 0-1 in the data (not 0-100)

Two patterns for counters:

Pattern 1: Pre-aggregated dataset (1 row, no filters)

• Dataset returns exactly 1 row

• Use "disaggregated": true and simple field reference

• Field name matches dataset column directly

{ "widget": { "name": "total-revenue", "queries": [{ "name": "main_query", "query": { "datasetName": "summary_ds", "fields": [{"name": "revenue", "expression": "revenue"}], "disaggregated": true } }], "spec": { "version": 2, "widgetType": "counter", "encodings": { "value": {"fieldName": "revenue", "displayName": "Total Revenue"} }, "frame": {"showTitle": true, "title": "Total Revenue"} } }, "position": {"x": 0, "y": 0, "width": 2, "height": 3} }

Pattern 2: Aggregating widget (multi-row dataset, supports filters)

• Dataset returns multiple rows (e.g., grouped by a filter dimension)

• Use "disaggregated": false and aggregation expression

• CRITICAL: Field name MUST match fieldName exactly (e.g., "sum(spend)" )

{ "widget": { "name": "total-spend", "queries": [{ "name": "main_query", "query": { "datasetName": "by_category", "fields": [{"name": "sum(spend)", "expression": "SUM(spend)"}], "disaggregated": false } }], "spec": { "version": 2, "widgetType": "counter", "encodings": { "value": {"fieldName": "sum(spend)", "displayName": "Total Spend"} }, "frame": {"showTitle": true, "title": "Total Spend"} } }, "position": {"x": 0, "y": 0, "width": 2, "height": 3} }

Table:

• version : 2 (NOT 1 or 3!)

• widgetType : "table"

• Columns only need fieldName and displayName

• no other properties!

• Use "disaggregated": true for raw rows

{ "widget": { "name": "details-table", "queries": [{ "name": "main_query", "query": { "datasetName": "details_ds", "fields": [ {"name": "name", "expression": "name"}, {"name": "value", "expression": "value"} ], "disaggregated": true } }], "spec": { "version": 2, "widgetType": "table", "encodings": { "columns": [ {"fieldName": "name", "displayName": "Name"}, {"fieldName": "value", "displayName": "Value"} ] }, "frame": {"showTitle": true, "title": "Details"} } }, "position": {"x": 0, "y": 0, "width": 6, "height": 6} }

Line / Bar Charts:

• version : 3

• widgetType : "line" or "bar"

• Use x , y , optional color encodings

• scale.type : "temporal" (dates), "quantitative" (numbers), "categorical" (strings)

• Use "disaggregated": true with pre-aggregated dataset data

Multiple Lines - Two Approaches:

• Multi-Y Fields (different metrics on same chart):

"y": { "scale": {"type": "quantitative"}, "fields": [ {"fieldName": "sum(orders)", "displayName": "Orders"}, {"fieldName": "sum(returns)", "displayName": "Returns"} ] }

• Color Grouping (same metric split by dimension):

"y": {"fieldName": "sum(revenue)", "scale": {"type": "quantitative"}}, "color": {"fieldName": "region", "scale": {"type": "categorical"}, "displayName": "Region"}

Bar Chart Modes:

• Stacked (default): No mark field - bars stack on top of each other

• Grouped: Add "mark": {"layout": "group"}

• bars side-by-side for comparison

Pie Chart:

• version : 3

• widgetType : "pie"

• angle : quantitative aggregate

• color : categorical dimension

• Limit to 3-8 categories for readability

7. FILTERS (Global vs Page-Level)

CRITICAL: Filter widgets use DIFFERENT widget types than charts!

• Valid types: filter-multi-select , filter-single-select , filter-date-range-picker

• DO NOT use widgetType: "filter"

• this does not exist and will cause errors

• Filters use spec.version: 2

• ALWAYS include frame with showTitle: true for filter widgets

Filter widget types:

• filter-date-range-picker : for DATE/TIMESTAMP fields

• filter-single-select : categorical with single selection

• filter-multi-select : categorical with multiple selections

Global Filters vs Page-Level Filters

Type Placement Scope Use Case

Global Filter Dedicated page with "pageType": "PAGE_TYPE_GLOBAL_FILTERS"

Affects ALL pages that have datasets with the filter field Cross-dashboard filtering (e.g., date range, campaign)

Page-Level Filter Regular page with "pageType": "PAGE_TYPE_CANVAS"

Affects ONLY widgets on that same page Page-specific filtering (e.g., platform filter on breakdown page only)

Key Insight: A filter only affects datasets that contain the filter field. To have a filter affect only specific pages:

• Include the filter dimension in datasets for pages that should be filtered

• Exclude the filter dimension from datasets for pages that should NOT be filtered

Filter Widget Structure

CRITICAL: Do NOT use associative_filter_predicate_group

• it causes SQL errors! Use a simple field expression instead.

{ "widget": { "name": "filter_region", "queries": [{ "name": "ds_data_region", "query": { "datasetName": "ds_data", "fields": [ {"name": "region", "expression": "region"} ], "disaggregated": false } }], "spec": { "version": 2, "widgetType": "filter-multi-select", "encodings": { "fields": [{ "fieldName": "region", "displayName": "Region", "queryName": "ds_data_region" }] }, "frame": {"showTitle": true, "title": "Region"} } }, "position": {"x": 0, "y": 0, "width": 2, "height": 2} }

Global Filter Example

Place on a dedicated filter page:

{ "name": "filters", "displayName": "Filters", "pageType": "PAGE_TYPE_GLOBAL_FILTERS", "layout": [ { "widget": { "name": "filter_campaign", "queries": [{ "name": "ds_campaign", "query": { "datasetName": "overview", "fields": [{"name": "campaign_name", "expression": "campaign_name"}], "disaggregated": false } }], "spec": { "version": 2, "widgetType": "filter-multi-select", "encodings": { "fields": [{ "fieldName": "campaign_name", "displayName": "Campaign", "queryName": "ds_campaign" }] }, "frame": {"showTitle": true, "title": "Campaign"} } }, "position": {"x": 0, "y": 0, "width": 2, "height": 2} } ] }

Page-Level Filter Example

Place directly on a canvas page (affects only that page):

{ "name": "platform_breakdown", "displayName": "Platform Breakdown", "pageType": "PAGE_TYPE_CANVAS", "layout": [ { "widget": { "name": "page-title", "multilineTextboxSpec": {"lines": ["## Platform Breakdown"]} }, "position": {"x": 0, "y": 0, "width": 4, "height": 1} }, { "widget": { "name": "filter_platform", "queries": [{ "name": "ds_platform", "query": { "datasetName": "platform_data", "fields": [{"name": "platform", "expression": "platform"}], "disaggregated": false } }], "spec": { "version": 2, "widgetType": "filter-multi-select", "encodings": { "fields": [{ "fieldName": "platform", "displayName": "Platform", "queryName": "ds_platform" }] }, "frame": {"showTitle": true, "title": "Platform"} } }, "position": {"x": 4, "y": 0, "width": 2, "height": 2} } // ... other widgets on this page ] }

Filter Layout Guidelines:

• Global filters: Position on dedicated filter page, stack vertically at x=0

• Page-level filters: Position in header area of page (e.g., top-right corner)

• Typical sizing: width: 2, height: 2

8. QUALITY CHECKLIST

Before deploying, verify:

• All widget names use only alphanumeric + hyphens + underscores

• All rows sum to width=6 with no gaps

• KPIs use height 3-4, charts use height 5-6

• Chart dimensions have ≤8 distinct values

• All widget fieldNames match dataset columns exactly

• Field name in query.fields matches fieldName in encodings exactly (e.g., both "sum(spend)" )

• Counter datasets: use disaggregated: true for 1-row datasets, disaggregated: false with aggregation for multi-row

• Percent values are 0-1 (not 0-100)

• SQL uses Spark syntax (date_sub, not INTERVAL)

• All SQL queries tested via execute_sql and return expected data

Complete Example

import json

Step 1: Check table schema

table_info = get_table_details(catalog="samples", schema="nyctaxi")

Step 2: Test queries

execute_sql("SELECT COUNT() as trips, AVG(fare_amount) as avg_fare, AVG(trip_distance) as avg_distance FROM samples.nyctaxi.trips") execute_sql(""" SELECT pickup_zip, COUNT() as trip_count FROM samples.nyctaxi.trips GROUP BY pickup_zip ORDER BY trip_count DESC LIMIT 10 """)

Step 3: Build dashboard JSON

dashboard = { "datasets": [ { "name": "summary", "displayName": "Summary Stats", "queryLines": [ "SELECT COUNT() as trips, AVG(fare_amount) as avg_fare, ", "AVG(trip_distance) as avg_distance ", "FROM samples.nyctaxi.trips " ] }, { "name": "by_zip", "displayName": "Trips by ZIP", "queryLines": [ "SELECT pickup_zip, COUNT() as trip_count ", "FROM samples.nyctaxi.trips ", "GROUP BY pickup_zip ", "ORDER BY trip_count DESC ", "LIMIT 10 " ] } ], "pages": [{ "name": "overview", "displayName": "NYC Taxi Overview", "pageType": "PAGE_TYPE_CANVAS", "layout": [ # Text header - NO spec block! Use SEPARATE widgets for title and subtitle! { "widget": { "name": "title", "multilineTextboxSpec": { "lines": ["## NYC Taxi Dashboard"] } }, "position": {"x": 0, "y": 0, "width": 6, "height": 1} }, { "widget": { "name": "subtitle", "multilineTextboxSpec": { "lines": ["Trip statistics and analysis"] } }, "position": {"x": 0, "y": 1, "width": 6, "height": 1} }, # Counter - version 2, width 2! { "widget": { "name": "total-trips", "queries": [{ "name": "main_query", "query": { "datasetName": "summary", "fields": [{"name": "trips", "expression": "trips"}], "disaggregated": True } }], "spec": { "version": 2, "widgetType": "counter", "encodings": { "value": {"fieldName": "trips", "displayName": "Total Trips"} }, "frame": {"title": "Total Trips", "showTitle": True} } }, "position": {"x": 0, "y": 2, "width": 2, "height": 3} }, { "widget": { "name": "avg-fare", "queries": [{ "name": "main_query", "query": { "datasetName": "summary", "fields": [{"name": "avg_fare", "expression": "avg_fare"}], "disaggregated": True } }], "spec": { "version": 2, "widgetType": "counter", "encodings": { "value": {"fieldName": "avg_fare", "displayName": "Avg Fare"} }, "frame": {"title": "Average Fare", "showTitle": True} } }, "position": {"x": 2, "y": 2, "width": 2, "height": 3} }, { "widget": { "name": "total-distance", "queries": [{ "name": "main_query", "query": { "datasetName": "summary", "fields": [{"name": "avg_distance", "expression": "avg_distance"}], "disaggregated": True } }], "spec": { "version": 2, "widgetType": "counter", "encodings": { "value": {"fieldName": "avg_distance", "displayName": "Avg Distance"} }, "frame": {"title": "Average Distance", "showTitle": True} } }, "position": {"x": 4, "y": 2, "width": 2, "height": 3} }, # Bar chart - version 3 { "widget": { "name": "trips-by-zip", "queries": [{ "name": "main_query", "query": { "datasetName": "by_zip", "fields": [ {"name": "pickup_zip", "expression": "pickup_zip"}, {"name": "trip_count", "expression": "trip_count"} ], "disaggregated": True } }], "spec": { "version": 3, "widgetType": "bar", "encodings": { "x": {"fieldName": "pickup_zip", "scale": {"type": "categorical"}, "displayName": "ZIP"}, "y": {"fieldName": "trip_count", "scale": {"type": "quantitative"}, "displayName": "Trips"} }, "frame": {"title": "Trips by Pickup ZIP", "showTitle": True} } }, "position": {"x": 0, "y": 5, "width": 6, "height": 5} }, # Table - version 2, minimal column props! { "widget": { "name": "zip-table", "queries": [{ "name": "main_query", "query": { "datasetName": "by_zip", "fields": [ {"name": "pickup_zip", "expression": "pickup_zip"}, {"name": "trip_count", "expression": "trip_count"} ], "disaggregated": True } }], "spec": { "version": 2, "widgetType": "table", "encodings": { "columns": [ {"fieldName": "pickup_zip", "displayName": "ZIP Code"}, {"fieldName": "trip_count", "displayName": "Trip Count"} ] }, "frame": {"title": "Top ZIP Codes", "showTitle": True} } }, "position": {"x": 0, "y": 10, "width": 6, "height": 5} } ] }] }

Step 4: Deploy

result = create_or_update_dashboard( display_name="NYC Taxi Dashboard", parent_path="/Workspace/Users/me/dashboards", serialized_dashboard=json.dumps(dashboard), warehouse_id=get_best_warehouse(), ) print(result["url"])

Complete Example with Filters

import json

Dashboard with a global filter for region

dashboard_with_filters = { "datasets": [ { "name": "sales", "displayName": "Sales Data", "queryLines": [ "SELECT region, SUM(revenue) as total_revenue ", "FROM catalog.schema.sales ", "GROUP BY region" ] } ], "pages": [ { "name": "overview", "displayName": "Sales Overview", "pageType": "PAGE_TYPE_CANVAS", "layout": [ { "widget": { "name": "total-revenue", "queries": [{ "name": "main_query", "query": { "datasetName": "sales", "fields": [{"name": "total_revenue", "expression": "total_revenue"}], "disaggregated": True } }], "spec": { "version": 2, # Version 2 for counters! "widgetType": "counter", "encodings": { "value": {"fieldName": "total_revenue", "displayName": "Total Revenue"} }, "frame": {"title": "Total Revenue", "showTitle": True} } }, "position": {"x": 0, "y": 0, "width": 6, "height": 3} } ] }, { "name": "filters", "displayName": "Filters", "pageType": "PAGE_TYPE_GLOBAL_FILTERS", # Required for global filter page! "layout": [ { "widget": { "name": "filter_region", "queries": [{ "name": "ds_sales_region", "query": { "datasetName": "sales", "fields": [ {"name": "region", "expression": "region"} # DO NOT use associative_filter_predicate_group - causes SQL errors! ], "disaggregated": False # False for filters! } }], "spec": { "version": 2, # Version 2 for filters! "widgetType": "filter-multi-select", # NOT "filter"! "encodings": { "fields": [{ "fieldName": "region", "displayName": "Region", "queryName": "ds_sales_region" # Must match query name! }] }, "frame": {"showTitle": True, "title": "Region"} # Always show title! } }, "position": {"x": 0, "y": 0, "width": 2, "height": 2} } ] } ] }

Deploy with filters

result = create_or_update_dashboard( display_name="Sales Dashboard with Filters", parent_path="/Workspace/Users/me/dashboards", serialized_dashboard=json.dumps(dashboard_with_filters), warehouse_id=get_best_warehouse(), ) print(result["url"])

Troubleshooting

Widget shows "no selected fields to visualize"

This is a field name mismatch error. The name in query.fields must exactly match the fieldName in encodings .

Fix: Ensure names match exactly:

// WRONG - names don't match "fields": [{"name": "spend", "expression": "SUM(spend)"}] "encodings": {"value": {"fieldName": "sum(spend)", ...}} // ERROR!

// CORRECT - names match "fields": [{"name": "sum(spend)", "expression": "SUM(spend)"}] "encodings": {"value": {"fieldName": "sum(spend)", ...}} // OK!

Widget shows "Invalid widget definition"

Check version numbers:

• Counters: version: 2

• Tables: version: 2

• Filters: version: 2

• Bar/Line/Pie charts: version: 3

Text widget errors:

• Text widgets must NOT have a spec block

• Use multilineTextboxSpec directly on the widget object

• Do NOT use widgetType: "text"

• this is invalid

Table widget errors:

• Use version: 2 (NOT 1 or 3)

• Column objects only need fieldName and displayName

• Do NOT add type , numberFormat , or other column properties

Counter widget errors:

• Use version: 2 (NOT 3)

• Ensure dataset returns exactly 1 row

Dashboard shows empty widgets

• Run the dataset SQL query directly to check data exists

• Verify column aliases match widget field expressions

• Check disaggregated flag (should be true for pre-aggregated data)

Layout has gaps

• Ensure each row sums to width=6

• Check that y positions don't skip values

Filter shows "Invalid widget definition"

• Check widgetType is one of: filter-multi-select , filter-single-select , filter-date-range-picker

• DO NOT use widgetType: "filter"

• this is invalid

• Verify spec.version is 2

• Ensure queryName in encodings matches the query name

• Confirm disaggregated: false in filter queries

• Ensure frame with showTitle: true is included

Filter not affecting expected pages

• Global filters (on PAGE_TYPE_GLOBAL_FILTERS page) affect all datasets containing the filter field

• Page-level filters (on PAGE_TYPE_CANVAS page) only affect widgets on that same page

• A filter only works on datasets that include the filter dimension column

Filter shows "UNRESOLVED_COLUMN" error for associative_filter_predicate_group

• DO NOT use COUNT_IF(
  associative_filter_predicate_group) in filter queries

• This internal expression causes SQL errors when the dashboard executes queries

• Use a simple field expression instead: {"name": "field", "expression": "
  field"}

Text widget shows title and description on same line

• Multiple items in the lines array are concatenated, not displayed on separate lines

• Use separate text widgets for title and subtitle at different y positions

• Example: title at y=0 with height=1, subtitle at y=1 with height=1

Related Skills

• databricks-unity-catalog - for querying the underlying data and system tables

• databricks-spark-declarative-pipelines - for building the data pipelines that feed dashboards

• databricks-jobs - for scheduling dashboard data refreshes