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Arbo is a real estate platform that provides property management and listing services for real estate agencies. It offers tools for managing properties, condominiums, owners, and real estate transactions, enabling real estate professionals to efficiently organize and showcase their property portfolios.

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Configuring Arbo as a Source

In the Sources tab, click on the “Add source” button located on the top right of your screen. Then, select the Arbo option from the list of connectors. Click Next and you’ll be prompted to add your access.

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1. Add account access

You’ll need to provide your Arbo API authentication token to access your data. The following configuration is required:
  • Auth Token: The API key to authenticate against the Arbo API service. Contact Arbo support to obtain your API authentication token.
Once you’re done, click Next.

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2. Select streams

Choose which data streams you want to sync. For faster extractions, select only the streams that are relevant to your analysis. You can select entire groups of streams or pick specific ones.
Tip: The stream can be found more easily by typing its name.
Select the streams and click Next.

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3. Configure data streams

Customize how you want your data to appear in your catalog. Select the desired layer where the data will be placed, a folder to organize it inside the layer, a name for each table (which will effectively contain the fetched data) and the type of sync.
  • Layer: choose between the existing layers on your catalog. This is where you will find your new extracted tables as the extraction runs successfully.
  • Folder: a folder can be created inside the selected layer to group all tables being created from this new data source.
  • Table name: we suggest a name, but feel free to customize it. You have the option to add a prefix to all tables at once and make this process faster!
  • Sync Type: you can choose between INCREMENTAL and FULL_TABLE.
    • Incremental: every time the extraction happens, we’ll get only the new data - which is good if, for example, you want to keep every record ever fetched.
    • Full table: every time the extraction happens, we’ll get the current state of the data - which is good if, for example, you don’t want to have deleted data in your catalog.
Once you are done configuring, click Next.

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4. Configure data source

Describe your data source for easy identification within your organization, not exceeding 140 characters. To define your Trigger, consider how often you want data to be extracted from this source. This decision usually depends on how frequently you need the new table data updated (every day, once a week, or only at specific times). Optionally, you can define some additional settings:
  • Configure Delta Log Retention and determine for how long we should store old states of this table as it gets updated. Read more about this resource here.
  • Determine when to execute an Additional Full Sync. This will complement the incremental data extractions, ensuring that your data is completely synchronized with your source every once in a while.
Once you are ready, click Next to finalize the setup.

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5. Check your new source

You can view your new source on the Sources page. If needed, manually trigger the source extraction by clicking on the arrow button. Once executed, your data will appear in your Catalog.
For you to be able to see it on your Catalog, you need at least one successful source run.

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Streams and Fields

Below you’ll find all available data streams from Arbo and their corresponding fields:
Stream for managing property listings, including all property details, location information, pricing, and features.Identifiers:
  • ref_id - Unique identifier for the property (primary key)
  • codigo - Property code
  • codigo_origem - Original property code
Status & Visibility:
  • ativo - Whether the property is active
  • publicado - Whether the property is published
  • status_comercial - Commercial status
  • origemcadastro - Registration origin
Property Information:
  • titulo - Property title
  • descricao - Property description
  • categoria - Property category
  • categoria_imovel - Property category type
  • tipo_imovel - Property type (Residencial, Comercial, etc.)
  • finalidade - Property purpose (Venda, Aluguel, Venda e Locação)
  • mobiliado - Whether the property is furnished
  • permuta - Whether exchange is accepted
  • financiamento - Whether financing is available
Property Details:
  • qtd_quartos - Number of bedrooms
  • qtd_suites - Number of suites
  • qtd_vagas - Number of parking spaces
  • qtd_banheiro - Number of bathrooms
  • area_total - Total area
  • area_privativa - Private area
Address Information:
  • end_condominio - Condominium name
  • end_bairro - Neighborhood
  • end_cidade - City
  • end_estado - State
  • end_logradouro - Street address
  • end_complemento - Address complement
  • end_numero - Address number
  • end_cep - ZIP code
  • latitude - Latitude coordinate
  • longitude - Longitude coordinate
Pricing:
  • valor_venda - Sale price
  • valor_aluguel - Rental price
  • valor_condominio - Condominium fee
  • valor_iptu - IPTU tax value
Media:
  • fotos - Array of property photos, each containing:
    • url - Photo URL
    • ordem - Display order
    • principal - Whether it’s the main photo
    • marcadagua_url - Watermark URL
    • sizes - Object with medium and small image URLs
  • url_video - Video URL
  • url_tour - Virtual tour URL
Relationships:
  • condominio - Condominium ID (foreign key to condominios)
  • prop_id - Property ID (used for child stream proprietarios)
  • corretor - Broker information object:
    • codigo - Broker code
    • nome - Broker name
  • imobiliaria - Real estate agency information object:
    • nome - Agency name
    • infos - Array of info objects with url and tipo
    • telefones - Array of phone numbers
Features & Metadata:
  • caracteristicas - Array of property features/amenities
  • emp_fields - Enterprise fields object with pricing and area filters:
    • emp_preco_min - Minimum price
    • emp_preco_max - Maximum price
    • emp_preco_min_loc - Minimum rental price
    • emp_preco_max_loc - Maximum rental price
    • emp_areautil_min - Minimum usable area
    • emp_areautil_max - Maximum usable area
    • emp_areaprivativa_min - Minimum private area
    • emp_areaprivativa_max - Maximum private area
    • emp_areatotal_min - Minimum total area
    • emp_areatotal_max - Maximum total area
    • emp_dorm_min - Minimum bedrooms
    • emp_dorm_max - Maximum bedrooms
    • emp_porcentagem_total - Total percentage
Timestamps:
  • created_at - Creation timestamp
  • updated_at - Last update timestamp
Stream for managing condominium information, including location, characteristics, and photos.Identifiers:
  • id - Unique identifier for the condominium (primary key)
  • cond_cod - Condominium code
  • cond_cod_origem - Original condominium code
Basic Information:
  • cond_nome - Condominium name
  • cond_tipo - Condominium type
  • cond_ano - Construction year (can be string or number)
  • cond_construt - Builder/Constructor
  • cond_desc - Description
  • cond_coment - Comments
  • condominio_ativo - Whether the condominium is active
Address Information:
  • cond_logradouro - Street address
  • cond_numero - Address number
  • cond_bairro - Neighborhood
  • cond_ptref - Reference point
  • cond_city - City
  • cond_est - State
  • cond_cep - ZIP code
  • cond_latitude - Latitude coordinate
  • cond_longitude - Longitude coordinate
  • cond_raiomapa - Map radius
Media & Features:
  • fotos - Array of condominium photos, each containing:
    • url - Photo URL
    • ordem - Display order
    • principal - Whether it’s the main photo
    • marcadagua_url - Watermark URL
    • sizes - Object with medium and small image URLs
  • caracteristicas - Array of condominium features/amenities
  • imobiliaria - Real estate agency information (can be ID number or full object)
Timestamps:
  • createdat - Creation timestamp
  • updatedat - Last update timestamp
Stream for managing property owners. This is a child stream of Imoveis, meaning it requires a parent property record to fetch owner information.Identifiers:
  • id - Unique identifier for the owner (primary key)
  • usu_id - User ID (property ID, references prop_id from imoveis)
  • imb_id - Real estate agency ID
Owner Information:
  • nome - Owner name
  • email - Owner email
  • rg - RG (Brazilian ID)
  • cpf - CPF (Brazilian tax ID)
Contact Information:
  • telefones - Array of phone number objects, each containing:
    • id - Phone number ID
    • numero - Phone number
    • contato - Contact name/description
Timestamps:
  • createdat - Creation timestamp
  • updatedat - Last update timestamp
Stream for retrieving cities with available properties.Identifiers:
  • end_cidade - City name (primary key)
Metrics:
  • count - Number of properties in this city
Stream for retrieving neighborhoods with available properties.Identifiers:
  • end_bairro - Neighborhood name (part of composite primary key)
  • end_cidade - City name (part of composite primary key)
Metrics:
  • count - Number of properties in this neighborhood
Stream for retrieving property type categories.Identifiers:
  • id - Property type ID (primary key)
Information:
  • categoria - Property type category

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Data Model

The following diagram illustrates the relationships between the data streams in Arbo. The arrows indicate the join keys that link the different entities, providing a clear overview of the data structure.

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Use Cases for Data Analysis

This guide outlines valuable business intelligence use cases when consolidating Arbo data, along with ready-to-use SQL queries that you can run on Explorer.

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1. Property Portfolio Overview

Get a comprehensive view of your property portfolio with key metrics including property counts, pricing distribution, and availability by location. Business Value:
  • Identify property distribution across cities and neighborhoods
  • Analyze pricing trends and availability
  • Track active vs. published properties
  • Understand property type distribution
SELECT
   i.end_cidade AS city,
   i.end_bairro AS neighborhood,
   i.categoria AS category,
   i.tipo_imovel AS property_type,
   i.finalidade AS purpose,
   COUNT(*) AS property_count,
   COUNT(DISTINCT i.condominio) AS condominium_count,
   AVG(i.valor_venda) AS avg_sale_price,
   AVG(i.valor_aluguel) AS avg_rental_price,
   SUM(CASE WHEN i.ativo = true THEN 1 ELSE 0 END) AS active_count,
   SUM(CASE WHEN i.publicado = true THEN 1 ELSE 0 END) AS published_count,
   AVG(i.area_total) AS avg_total_area,
   AVG(i.qtd_quartos) AS avg_bedrooms
FROM
   nekt_raw.arbo_imoveis i
WHERE
   i.ativo = true
GROUP BY
   1, 2, 3, 4, 5
ORDER BY
   property_count DESC
cityneighborhoodcategoryproperty_typepurposeproperty_countcondominium_countavg_sale_priceavg_rental_priceactive_countpublished_countavg_total_areaavg_bedrooms
PelotasCentroStudioResidencialVenda4512245000.00NULL454235.51.0
PelotasTrês VendasApartamentoResidencialVenda e Locação388385000.002800.00383572.32.5
PelotasLaranjalTerrenoResidencialVenda223150000.00NULL2220250.0NULL

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2. Property-Owner Relationships

Analyze the relationship between properties and their owners to understand portfolio distribution and owner information. Business Value:
  • Identify owners with multiple properties
  • Analyze owner contact information completeness
  • Track property-owner associations
  • Understand property distribution per owner
SELECT
   p.nome AS owner_name,
   p.email AS owner_email,
   p.cpf AS owner_cpf,
   COUNT(DISTINCT p.usu_id) AS property_count,
   STRING_AGG(DISTINCT i.categoria, ', ') AS property_categories,
   STRING_AGG(DISTINCT i.end_cidade, ', ') AS cities,
   AVG(i.valor_venda) AS avg_property_value,
   SUM(ARRAY_LENGTH(p.telefones)) AS total_phone_numbers
FROM
   nekt_raw.arbo_proprietarios p
   LEFT JOIN nekt_raw.arbo_imoveis i ON p.usu_id = i.prop_id
GROUP BY
   1, 2, 3
HAVING
   COUNT(DISTINCT p.usu_id) > 0
ORDER BY
   property_count DESC
owner_nameowner_emailowner_cpfproperty_countproperty_categoriescitiesavg_property_valuetotal_phone_numbers
João Silva[email protected]123.456.789-005Studio, ApartamentoPelotas285000.002
Maria Santos[email protected]987.654.321-003Terreno, CasaPelotas, Rio Grande320000.001

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3. Condominium Analysis

Analyze condominium data to understand property distribution, features, and location patterns. Business Value:
  • Understand property concentration in condominiums
  • Analyze condominium characteristics and features
  • Track condominium locations and distribution
  • Compare property values within condominiums
SELECT
   c.cond_nome AS condominium_name,
   c.cond_city AS city,
   c.cond_bairro AS neighborhood,
   COUNT(DISTINCT i.ref_id) AS property_count,
   AVG(i.valor_venda) AS avg_sale_price,
   AVG(i.area_total) AS avg_area,
   ARRAY_LENGTH(c.caracteristicas) AS feature_count,
   ARRAY_LENGTH(c.fotos) AS photo_count,
   c.condominio_ativo AS is_active
FROM
   nekt_raw.arbo_condominios c
   LEFT JOIN nekt_raw.arbo_imoveis i ON c.id = i.condominio
GROUP BY
   1, 2, 3, 7, 8, 9
ORDER BY
   property_count DESC

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Implementation Notes

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Data Quality Considerations

  • The proprietarios stream is a child stream of imoveis and requires a parent property record with a valid prop_id
  • Property prices (valor_venda, valor_aluguel) may be NULL for properties not available for sale/rent
  • Some fields like cond_ano (construction year) may be returned as strings or numbers depending on the API response
  • The imobiliaria field in condominios can be either an ID number or a full object, and is converted to a string format for consistency

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API Limits & Performance

  • The API uses pagination with a page size of 100 records
  • For faster extractions, select only the streams necessary for your analysis
  • The proprietarios stream will only sync for properties that have a valid prop_id value