Provo UT 311
Public data
Provo 311 requests with coordinates and submission times for each call. Ingest delivers this data to a data warehouse you own as 2 tables, and updates it on the schedule you choose. There is no code to write and nothing to install.
What people use it for
- Locate problem neighborhoodsPlot request coordinates to map which parts of the city have the most calls.
- Analyze request flowExamine when requests arrive to understand demand patterns.
- Group by request typeSort requests by code to see what categories need the most attention.
What you get
| Table | Each row is |
|---|---|
Service requestsservice_requests | One service request |
Service typesservices | One service type |
Good to know
- Service requests: The first run loads the last 30 days. After that, each run keeps the last 30 days current, re-reading older days after one day. Days older than 30 days keep the values they had when last read.
- Service types: Re-read at most once a day. Service types that change are updated, and types the city removes stay in your table.
How it works
- Choose Provo UT 311. The data is public, so there is nothing to sign in to.
- Pick where it goes. BigQuery, Snowflake, Databricks, Redshift and 10 more, in an account you own.
- Pick a schedule. Daily is the default, and weekly and monthly are there too.
- Ingest runs it from then on. If a run fails, your dashboard shows which table and why.
Questions
- What does the Provo UT 311 data include?
- 2 tables: service requests (one row per service request) and service types (one row per service type).
- Do I need an account with Provo UT 311?
- No. The data is public, so there is nothing to sign up for and nothing to paste in.
- Which warehouses can Provo UT 311 data go to?
- Amazon S3, Google Cloud Storage, Azure Blob Storage, Apache Iceberg, Ingest Managed Lakehouse, MotherDuck, Postgres, Amazon Athena, Databricks, Redshift, BigQuery, ClickHouse, MySQL / generic SQL and Snowflake, in an account you own.
- How fresh is the data?
- As fresh as your schedule: daily by default, or weekly or monthly. Schedules as often as every 15 minutes are on the Enterprise plan.
- Will running it again create duplicate rows?
- No. Each row is stored once, by its key: when a run reads a row that is already there, it replaces that copy instead of adding a second one.
- Do I need to write code?
- No. Ingest builds, runs and maintains the connector. Someone with access to your warehouse connects it once, following a short guide.
For your data team: technical reference
Connector provo_311, version 0.1.0, a REST source, status beta, authentication none.
Vendor documentation: https://seeclickfix.com/open311/v2/docs
Configuration
No configuration required.
Resources
| Resource | Status | Plan | Write | Primary key | Overrides |
|---|---|---|---|---|---|
service_requestsFetches request creation windows covering the previous 30 completed UTC days by default. The current UTC day becomes eligible after it ends. Completed windows still inside the selected horizon become eligible for refresh 1 day(s) after their last successful read, on a subsequent scheduled run. This is bounded history, not all history. Merge updates returned IDs; older requests outside the horizon and deleted or no-longer-exposed records retain their last loaded values, and later edits outside the horizon are not refreshed. Older completed days wait longer between reads, becoming eligible again only after the longer of the refresh interval and a twentieth of their age at their last read (with the default interval, a day read at 40 days old waits 2 days). | beta | window | merge | service_request_id | lookback_days, staleness_days |
servicesReads the current public service-type catalog exposed by this organization on scheduled runs when 1 day(s) have elapsed since the last successful read. All returned service codes are retained; the catalog is not used to filter request rows. Merge updates returned codes, while removed or no-longer-exposed codes retain their last loaded values. | beta | staleness | merge | service_code | - |
Where this lands, and what else connects
Setting up the destination is its own short guide, one per warehouse or lake: Amazon S3, Google Cloud Storage, Azure Blob Storage, Apache Iceberg, Ingest Managed Lakehouse, MotherDuck, Postgres, Amazon Athena, Databricks, Redshift, BigQuery, ClickHouse, MySQL / generic SQL, Snowflake.
Other sources Ingest connects for government teams: Abilene TX 311, Albany NY 311, Ann Arbor MI 311, Anne Arundel County MD 311, Auburn WA 311, Aurora IL 311.
- How Ingest reads a REST source
- Ingest for government teams
- The tables Ingest creates
- Every source Ingest connects
Get Provo UT 311 data into your warehouse
Last updated .