SQL Queries - Precisely Data Integrity Suite

Data Integrity Suite APIs
Product
Data_Integrity
Spatial_Analytics
Data_Enrichment
geo_addressing_1
Services
Spatial Analytics
Data Enrichment
Geo Addressing
ft:title
Data Integrity Suite APIs
ft:locale
en-US
PublicationType
pt_developer
copyrightfirst
2023
copyrightlast
2026

Use these queries to start using the Data Graph service.
Note: In any query, replace APP-NAME with your actual application name.

getByAddress

This query requires address as input parameters to derive Data Graph based on the defined data type and required attributes. The query can only be used by the users who know about the address while executing. Address and country are needed to be passed as variables in the query along with all the required attributes that are required in response.
  • address: Specific address for which we want the entities (mandatory field)
  • country: Specific country if we need results of specific country (optional field)

Query Syntax

 getByAddress( 
        address: String! 
        country: String 
    ): RelationEntity

Address queries with json results for addresses

Query for buildings by address from addresses with json result:

SELECT ADDRESS, COUNTRY, <APP-NAME>.v1.execute_data_graph_query(CONCAT('query buildingsByAddress { 
getByAddress(address: "',ADDRESS,'") { 
 buildings { 
   data { 
     buildingID 
     buildingType { 
       value 
       description 
     } 
     geometry 
   } 
 } 
} 
}  '), '<API_KEY>', '<API_SECRET>') as buildings_By_Address 
FROM <YOUR-ADDRESS-TABLE>;

Output from above query:

Table 1.
Address Country BUILDINGSBYADDRESS
3017 ACTION RV MOODY AB USA 
{ "data": { "getByAddress": { "buildings": { "data": [ { "buildingID": " B000VTGGLEAX ", "buildingType": { "description": "Unknown", "value": "X" } }, { "buildingID": "B000VTGGLEAX", "buildingType": { "description": "Residential", "value": "R" } } ] } } } }
7503 E 20TH AVC Degver CV USA 
{ "data": { "getByAddress": { "buildings": { "data": [ { "buildingID": " B000VTGGLEAX ", "buildingType": { "description": "Residential", "value": "R" } }, { "buildingID": " B000VTGGLEAX ", "buildingType": { "description": "Residential", "value": "R" } }, { "buildingID": " B000VTGGLEAX ", "buildingType": { "description": "Residential", "value": "R" } }, { "buildingID": "B000CTRQBKCR", "buildingType": { "description": "Residential", "value": "R" } } ] } } } }

Query for property attributes by address from addresses with json result:

SELECT ADDRESS, COUNTRY, <APP-NAME>.v1.execute_data_graph_query(CONCAT('query propertyAttributesByAddress { 
getByAddress(address: "',ADDRESS,'") { 
 propertyAttributes { 
   data { 
     livingSquareFootage 
     bedroomCount 
     bathroomCount { 
       value 
     } 
     saleAmount 
   } 
 } 
} 
}  '), '<API_KEY>', '<API_SECRET>') as Property_Attributes_By_Address 
FROM <YOUR-ADDRESS-TABLE>;

Output from above query:

Table 2.
Address Country Buildings by Address
3017 ACTION RV MOODY AB USA 
{ "data": { "getByAddress": { "propertyAttributes": { "data": [ { "bathroomCount": { "value": null }, "bedroomCount": -777, "livingSquareFootage": -77, "saleAmount": "00000" } ] } } } }
7503 E 20TH AVC Degver CV USA 
{ "data": { "getByAddress": { "propertyAttributes": null } } }

To explore more about Data Graph Queries refer to Data Graph Play Ground