Abilene TX 311
Public data
Service requests reported to Abilene, Texas's 311 line, as the city publishes them. 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
- See which request types are most commonCount requests by type to see what residents report most.
- Watch demand week by weekCount requests by the day they were made to see weekly patterns.
- Map where requests come fromPlot requests using their coordinates to see which areas report most.
What you get
| Table | Each row is |
|---|---|
Service requestsservice_requests | One service request |
Request typesservices | One request type the city accepts |
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 a day once its copy is at least 7 days old. Older requests keep the values they had when last read.
- Request types: Each run re-reads everything and updates rows that changed. Rows the source removes stay in your table.
How it works
- Choose Abilene TX 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 Abilene TX 311 data include?
- 2 tables: service requests (one row per service request) and request types (one row per request type the city accepts).
- Do I need an account with Abilene TX 311?
- No. The data is public, so there is nothing to sign up for and nothing to paste in.
- Which warehouses can Abilene TX 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 abilene_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_requestsPublic requests from the selected creation-history period, defaulting to the last 30 completed days. Completed days within the selected horizon become eligible for refresh after seven days by default; later edits are captured when their creation day is read again. Increase lookback_days to include older creation days. Requests outside the horizon and records removed from the source retain their last synced values. Requests are not filtered by membership in the current service-type catalog. 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 280 days old waits 14 days). | beta | window | merge | service_request_id | lookback_days |
servicesPublic service types returned by the Abilene SeeClickFix catalog. Each run reads and merges service codes; previously synced types remain if removed from the source. The catalog does not filter the requests collection. | beta | full | 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: Albany NY 311, Ann Arbor MI 311, Anne Arundel County MD 311, Auburn WA 311, Aurora IL 311, Austin TX 311.
- How Ingest reads a REST source
- Ingest for government teams
- The tables Ingest creates
- Every source Ingest connects
Get Abilene TX 311 data into your warehouse
Last updated .