About bulk data feeds

For customers requiring access to bulk property and owner data for aggregations, analytics, or integration with existing data (proprietary or public), bulk data feeds provide an easy way to obtain the data you need for offline use. Our data pipeline runs weekly, ensuring we always have the most recent property data available. Once your job is configured, we can schedule it to deliver refreshed data on whatever cadence suits you (weekly, monthly, quarterly, etc.).

The interactive simulation below demonstrates the basic steps to creating and using a bulk data feed. It shows only a few of the over 70 available search settings and a small fraction of the over 400 available data attributes, but it illustrates the key concepts of defining properties of interest, specifying the data attributes you want, running the job, and retrieving the output file.

Real bulk data feed jobs run asynchronously, meaning jobs are queued and run based on availability of backend resources. Jobs may take up to 12 hours to complete, but you can generally expect results in 1-2 hours. You'll receive an email notification when the output is available.

We offer two approaches:

• Customized scheduled delivery: Work with a Reonomy Customer Success Manager to identify the properties of interest and the data you want, then receive the most recent data for those properties on a cadence that suits your needs (typically weekly or monthly).
• Scheduled delivery using our API: If you prefer more control and have a technical team to manage the integration, you can configure a bulk data feed yourself. For configuration instructions, see Configuring bulk data feeds.

Defining a bulk data feed is a 3-step process you'll go through with your Reonomy Customer Success Manager, or with the help of the Solutions team:

1. Identify properties of interest. You can search for properties that meet certain criteria, or you can upload a file of addresses or geocoded locations for us to match against.
2. Specify the data you want and the format you'd like to receive it (CSV or NDJSON). The data attributes we offer are subdivided into broad categories like sales, mortgages, ownership, etc. Select the categories you want, or select specific attributes within one or more categories (CSV only).
3. Specify optional settings, including how often the job should run, how the data files should be delivered, and who should receive notifications.

Reonomy provides two distinct ways to identify properties of interest:

1. Search: Returns the requested data for properties that match a set of parameters you define.
2. Match: You provide us with a list of property addresses, geolocations, or property IDs, and we return the requested data for those properties.

We provide an extensive range of search parameters for creating targeted searches that return a very specific set of properties. See the full list of search parameters on the right.

The interactive simulation below provides a simplified view of the four basic steps for a match job. It illustrates the key concepts of identifying properties using location information (addresses in this case, but could be geo-locations), specifying the data you want, running the job, and retrieving the resulting output file.

Once you've identified the properties you're interested in, we need to know:

• Which data attributes you'd like to receive for each matching property.
• The format you'd like to receive the data (CSV or NDJSON).
• How we should bundle the resulting data records (single-file or multi-file).

Individual attribute selection is only available for CSV output. With NDJSON, you can select which categories to include (sales, mortgages, etc.), but can't select individual attributes within those categories. Use the interactive attribute tree below to explore the available attributes in each category.

We offer two output file formats, illustrated on the right:

• NDJSON: Each property record is represented as a separate JSON object within a single file, with a new line (\n) character between each object. NDJSON provides a complete nested representation of all the available data for the selected properties and the selected detail types.
• CSV: Each property record is represented as a separate row within a single flat CSV file. With CSV output, you must select which of the available attributes you'd like to include. Additionally, for lists (for example, sales, taxes, etc.), you must specify how many list items to include. Flat file conversion is described below.

When you select CSV as the output format, the bulk data feed file assembly component must transform the nested data schema into a flat file representation. This requires that you select which of the available attributes you'd like to include in the output file. Additionally, for lists (for example, mortgages, taxes, etc. as well as some nested attributes), you must specify how many list items to include (5 is typical). We require this to control the width of the resulting CSV file (see the example on the right).

The interactive example below illustrates how we convert a nested hierarchy into a flat file. Click attributes in the nested representation to see how the columns in the resulting CSV file will look. Use the slider to see how changing the list item count affects the number of output columns (the property_id column is not included in the count).

With the default output format, property data is returned as one-record-per-property within a single file. Because each record represents a single property, we call these property-centric reports.

As an alternative, we offer multi-file output, where the data for each selected detail type (mortgages, taxes, etc.) is returned as a separate file. Within each file, each constituent record (mortgage document, tax record, etc.) is returned as a separate NDJSON record or row in the CSV file. We call these entity-centric reports.

The interactive example below illustrates the difference between single file (property centric) and multi file (entity centric) output:

• With single file, all data for a given property is nested under its own node, or included within the same row for CSV files.
• With multi file, all mortgage data is returned within a mortgages file, all tax data within a taxes file, and so on. Within the mortgages file, each mortgage is a separate record, etc. The property_id is included with each record, so you always know which property the record belongs with.

Our data pipeline runs weekly to integrate the latest updates from our many data providers. This ensures we always deliver the most recent property data available.

Since bulk data feeds output files are decoupled from our data pipeline, we provide a scheduling mechanism to run your job automatically and deliver new output files. This enables you to refresh your downstream applications and data models with the latest updates on whatever cadence suits you (weekly, monthly, quarterly, etc.). When new output files are ready, we send automated email notifications letting you know they are available to download.

For scheduled runs, we can deliver a full dataset each time, or deliver only those records that have changed since the last run.

Bulk data feeds supports the following output delivery options:

• Email: Receive a download link by email when the job completes.
• SFTP: Password-protected access to a private SFTP site where you can download files from the last run of each job, as well as all prior runs.
• AWS S3: Delivery to your own AWS S3 bucket. See Configuring S3 file delivery for configuration requirements.
• Microsoft Azure: Delivery to your own Microsoft Azure Storage container. See Configuring Azure Storage file delivery for configuration requirements.
• API: Programmatic access via the bulk data feeds API.