This dataset is a compilation of address point data for the City of Tempe. The dataset contains a point location, the official address (as defined by The Building Safety Division of Community Development) for all occupiable units and any other official addresses in the City. There are several additional attributes that may be populated for an address, but they may not be populated for every address. Contact: Lynn Flaaen-Hanna, Development Services Specialist Contact E-mail Link: Map that Lets You Explore and Export Address Data Data Source: The initial dataset was created by combining several datasets and then reviewing the information to remove duplicates and identify errors. This published dataset is the system of record for Tempe addresses going forward, with the address information being created and maintained by The Building Safety Division of Community Development.Data Source Type: ESRI ArcGIS Enterprise GeodatabasePreparation Method: N/APublish Frequency: WeeklyPublish Method: AutomaticData Dictionary

Updated Continually

Our address datasets contain all geospatial address data of Portugal. You can use this data to send direct mail campaigns to households within a certain radius of your store, or to limit your online campaigns to viewers within a specific catchment area.

Address-Level Targeting in Portugal

Spotzi users can also combine our address data with consumer demographics and behavior data - such as insights into purchasing habits or disposable income - to ensure that every campaign targets their best-fit customers.

Points representing the locations of known active addresses in the Portland Metro Region. Addresses been culled from the City of Portland Master Address Repository, Multnomah County Assessor Records and the RLIS Master Address Points dataset.This dataset contains active addresses - those that are currently in use in the Portland Metro Region.The Schema of this dataset is built to match legacy address datasets to support existing applications and tools.--Additional Information: Category: Address Purpose: For mapping, geocoding, mailing, and analysis of addresses in the Portland Metro Region. Update Frequency: Weekly-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=52064

Address points were developed to supplement the address information supplied by the CSCL centerline. Some computer aided dispatch systems use address points as the primary source for locating an address. For additional information and resources, please visit https://nycmaps-nyc.hub.arcgis.com/datasets/nyc::address-point/about

This dataset shows the Address Points in Allegheny County. The Address Points were created by GDR for the Allegheny County CAD project, October 2008. Data is updated by County staff as changes and corrections are found, on a continuous basis. Updates are sent to PASDA monthly. The most authoritative source for this data is now the PASDA page (https://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=1219), which includes links to historical versions of the shapefile representations of this data.

This layer contains address point features which are used for geocoding addresses and property identification numbers. Data attributes include property addresses and property identification numbers. Addresses are stored in both parsed and concatenated fields.Link to Attribute Table Information: https://gis.hennepin.us/OpenData/Metadata/Address%20Points.pdfData updated: daily

Welcome to Apiscrapy, your ultimate destination for comprehensive location-based intelligence. As an AI-driven web scraping and automation platform, Apiscrapy excels in converting raw web data into polished, ready-to-use data APIs. With a unique capability to collect Google Address Data, Google Address API, Google Location API, Google Map, and Google Location Data with 100% accuracy, we redefine possibilities in location intelligence.

Key Features:

Unparalleled Data Variety: Apiscrapy offers a diverse range of address-related datasets, including Google Address Data and Google Location Data. Whether you seek B2B address data or detailed insights for various industries, we cover it all.

Integration with Google Address API: Seamlessly integrate our datasets with the powerful Google Address API. This collaboration ensures not just accessibility but a robust combination that amplifies the precision of your location-based insights.

Business Location Precision: Experience a new level of precision in business decision-making with our address data. Apiscrapy delivers accurate and up-to-date business locations, enhancing your strategic planning and expansion efforts.

Tailored B2B Marketing: Customize your B2B marketing strategies with precision using our detailed B2B address data. Target specific geographic areas, refine your approach, and maximize the impact of your marketing efforts.

Use Cases:

Location-Based Services: Companies use Google Address Data to provide location-based services such as navigation, local search, and location-aware advertisements.

Logistics and Transportation: Logistics companies utilize Google Address Data for route optimization, fleet management, and delivery tracking.

E-commerce: Online retailers integrate address autocomplete features powered by Google Address Data to simplify the checkout process and ensure accurate delivery addresses.

Real Estate: Real estate agents and property websites leverage Google Address Data to provide accurate property listings, neighborhood information, and proximity to amenities.

Urban Planning and Development: City planners and developers utilize Google Address Data to analyze population density, traffic patterns, and infrastructure needs for urban planning and development projects.

Market Analysis: Businesses use Google Address Data for market analysis, including identifying target demographics, analyzing competitor locations, and selecting optimal locations for new stores or offices.

Geographic Information Systems (GIS): GIS professionals use Google Address Data as a foundational layer for mapping and spatial analysis in fields such as environmental science, public health, and natural resource management.

Government Services: Government agencies utilize Google Address Data for census enumeration, voter registration, tax assessment, and planning public infrastructure projects.

Tourism and Hospitality: Travel agencies, hotels, and tourism websites incorporate Google Address Data to provide location-based recommendations, itinerary planning, and booking services for travelers.

Discover the difference with Apiscrapy – where accuracy meets diversity in address-related datasets, including Google Address Data, Google Address API, Google Location API, and more. Redefine your approach to location intelligence and make data-driven decisions with confidence. Revolutionize your business strategies today!

Our address datasets contain all geospatial address data of Lithuania. You can use this data to send direct mail campaigns to households within a certain radius of your store, or to limit your online campaigns to viewers within a specific catchment area.

Address-Level Targeting in Lithuania

Spotzi users can also combine our address data with consumer demographics and behavior data - such as insights into purchasing habits or disposable income - to ensure that every campaign targets their best-fit customers.

The AIMS: Address data table contains details relating to the creation and updating of an address including the version of an address and is part of the AIMS: Street Address.

Refer to the NZ Addresses Data Dictionary for detailed metadata and information about this dataset.

Background

This dataset provides all allocated addresses as advised to Toitū Te Whenua LINZ by Territorial Authorities (TAs). Under the Local Government Act 1974 (section 319) it is the responsibility of the TAs to advise the Surveyor-General at Toitū Te Whenua LINZ of all allocated addresses in their district.

The dataset is maintained by Toitū Te Whenua LINZ in the Address Information Management System (AIMS) which is centralised database for the management of national addresses, including for electoral purposes. This dataset is updated weekly on the LINZ Data Service.

For a simplified version of the data contained within these tables see NZ Addresses

Connecticut address point dataset used for locating 9-1-1 calls. The address point feature class format is derived from National Emergency Number Association (NENA) and Federal Geographic Data Committee (FGDC) addressing standards. All address components, like address number, streets name and unit number, are broken up into their individual components to enable maximum flexibility for use. Fields within feature class should be able to accommodate all addresses within the state of Connecticut. The source for the addresses is primarily derived from municipal parcel data and other municipal sources.

National Address DatabaseThis National Geospatial Data Asset (NGDA) dataset, shared as a U.S. Department of Transportation (USDOT) feature layer, displays address data in the United States. Per USDOT, "The U.S. Department of Transportation (USDOT) and its partners from all levels of government recognize the need for a National Address Database (NAD). Accurate and up-to-date addresses are critical to transportation safety and are a vital part of Next Generation 9-1-1. They are also essential for a broad range of government services, including mail delivery, permitting, and school siting. To meet this need, USDOT partners with address programs from state, local, and tribal governments to compile their authoritative data into the NAD."District of Columbia (DC) Residential AddressesData currency: Current federal service (Address Points from National Address Database)NGDAID: 196 (National Address Database (NAD))For more information: Getting to know the National Address Database (NAD); National Address DatabaseFor feedback, please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Transportation Theme Community. Per the Federal Geospatial Data Committee (FGDC), Transportation is defined as the "means and aids for conveying persons and/or goods. The transportation system includes both physical and non-physical components related to all modes of travel that allow the movement of goods and people between locations".For other NGDA Content: Esri Federal Datasets

The US Consumer Email file has 700 million+ emails with new emails monthly. Emails are stored in plain text, MD5, SHA 256, and SHA1 formats. Additionally, our email recency validation processing can increase the success of your email campaigns by as much as 4X.

We have developed this file to be tied to our Consumer Demographics Database so additional demographics can be applied as needed. Each record is ranked by confidence and only the highest quality data is used.

Note - all Consumer packages can include necessary PII (address, email, phone, DOB, etc.) for merging, linking, and activation of the data.

BIGDBM Privacy Policy: https://bigdbm.com/privacy.html

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Address Ranges Feature Shapefile (ADDRFEAT.dbf) contains the geospatial edge geometry and attributes of all unsuppressed address ranges for a county or county equivalent area. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. Single-address address ranges have been suppressed to maintain the confidentiality of the addresses they describe. Multiple coincident address range feature edge records are represented in the shapefile if more than one left or right address ranges are associated to the edge. The ADDRFEAT shapefile contains a record for each address range to street name combination. Address range associated to more than one street name are also represented by multiple coincident address range feature edge records. Note that the ADDRFEAT shapefile includes all unsuppressed address ranges compared to the All Lines Shapefile (EDGES.shp) which only includes the most inclusive address range associated with each side of a street edge. The TIGER/Line shapefile contain potential address ranges, not individual addresses. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.

Our address datasets contain all geospatial address data of United Kingdom. You can use this data to send direct mail campaigns to households within a certain radius of your store, or to limit your online campaigns to viewers within a specific catchment area.

Address-Level Targeting in United Kingdom

Spotzi users can also combine our address data with consumer demographics and behavior data - such as insights into purchasing habits or disposable income - to ensure that every campaign targets their best-fit customers.

Primary address points in and around the City of Cupertino city boundary. Primary addresses do not include suite, unit, or apartment number. This layer is primarily used as a reference layer. The layer is updated as needed by the GIS division. Address Points (Primary) has the following fields:OBJECTID:Unique identifier automatically generated by Esritype: OID, length: 4, domain: noneAPN:The Assesor's Parcel Number where the primary address point is locatedtype: String, length: 10, domain: noneLocation:Further description of the location of the addresstype: String, length: 36, domain: noneAddress:The address of the featuretype: String, length: 56, domain: noneHouse Number:The house number associated with the address pointtype: String, length: 11, domain: noneStreet Prefix:Prefix for the street nametype: String, length: 7, domain: AddressPrefixdomain values: ['S', 'E', 'W', 'N']Street Name:Name of the street on which the address point is locatedtype: String, length: 23, domain: noneStreet Suffix:The suffix for the street nametype: String, length: 7, domain: AddressSuffixdomain values: ['CMN', 'EXPY', 'LN', 'SQ', 'PLZ', 'PKWY', 'RD', 'CIR', 'LOOP', 'WAY', 'BLVD', 'AVE', 'TER', 'ST', 'DR', 'PL', 'CT']Street Suffix Direction:The suffix for the direction of the street nametype: String, length: 11, domain: AddressPrefixdomain values: ['S', 'E', 'W', 'N']State:The State in which the feature is locatedtype: String, length: 7, domain: noneComments:Any relevant comments relating to the featuretype: String, length: 50, domain: noneZip:The zip code of the address pointtype: String, length: 10, domain: noneX:The X coordinate of the address pointtype: Double, length: 8, domain: noneY:The Y coordinate of the address pointtype: Double, length: 8, domain: noneFloor:Floor number associated with the address pointtype: SmallInteger, length: 2, domain: Floordomain values: ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10']Shape:Field that stores geographic coordinates associated with featuretype: Geometry, length: 4, domain: noneGlobalID:Unique identifier automatically generated for features in enterprise databasetype: GlobalID, length: 38, domain: noneStatus:The active or construction status of the asset in the fieldtype: String, length: 20, domain: AddStatusdomain values: ['Active', 'Inactive', 'Temporary', 'Proposed']AssetID:Cupertino maintained GIS primary keytype: String, length: 50, domain: nonePostalCity:The city associated to the postal address of the pointtype: String, length: 50, domain: shdOwnedBydomain values: ['Cupertino', 'San Jose Water', 'CalTrans', 'PGE', 'Los Altos', 'Santa Clara', 'Private HOA', 'Saratoga', 'Other Public', 'Santa Clara County', 'San Jose', 'Santa Clara Valley Water District', 'Private', 'California Water Service', 'State Parks', 'Sunnyvale', 'Cupertino Sanitary District', 'CWA']CenterlineID:The ID associating the address to the street centerlinetype: String, length: 50, domain: noneIsDuplicateAddress:Indicator of whether the address is a duplicate or nottype: String, length: 3, domain: shdBooleanYesNodomain values: ['Yes', 'No']PlaceType:The use type of the facility at the address pointtype: String, length: 50, domain: AddressPlaceTypedomain values: ['Educational', 'Transportation', 'Business', 'Government', 'Hospital', 'Recreational', 'Miscellaneous', 'Residential Single Family', 'Residential Multi Family']City:The city in which the address is locatedtype: String, length: 50, domain: shdOwnedBydomain values: ['Cupertino', 'San Jose Water', 'CalTrans', 'PGE', 'Los Altos', 'Santa Clara', 'Private HOA', 'Saratoga', 'Other Public', 'Santa Clara County', 'San Jose', 'Santa Clara Valley Water District', 'Private', 'California Water Service', 'State Parks', 'Sunnyvale', 'Cupertino Sanitary District', 'CWA']

Our address datasets contain all geospatial address data of Czech Republic. You can use this data to send direct mail campaigns to households within a certain radius of your store, or to limit your online campaigns to viewers within a specific catchment area.

Address-Level Targeting in Czech Republic

Spotzi users can also combine our address data with consumer demographics and behavior data - such as insights into purchasing habits or disposable income - to ensure that every campaign targets their best-fit customers.

More Metadata

Data updated daily.

Address points mark the location of each addressable structure and its access point. The access point is the place where a driveway intersects the road. The building point is where the structure is located. An addressable structure is one where people live, work, or gather. A 1 to 5-digit number designates an address. Purpose: The access point is used to assign an address to the structure. Addresses are also assigned to assist in the provision of emergency services; they can be queried at all Fire and Rescue stations and by E-911 dispatchers. Supplemental Information: Data are stored in the corporate ArcSDE Geodatabase as a feature class. The coordinate system is Virginia State Plane (North), Zone 4501, datum NAD83 HARN. Maintenance and Update Frequency: Daily Completeness Report: Features may have been eliminated or generalized due to scale and intended use. To assist Loudoun County, Virginia in the maintenance of the data, please provide any information concerning discovered errors, omissions, or other discrepancies found in the data.

Data Owner: Office of Mapping and Geographic Information