Business location data for Maptitude mapping software are from Caliper Corporation and contain point locations for businesses.

Walmart Store Location Data

Walmart Inc. is an American multinational retail corporation that operates a chain of hypermarkets, discount department stores, and grocery stores, headquartered in Bentonville, Arkansas

This is a complete list of all Walmart store locations, along with their geographic coordinates, Street addresses, City, State, ZIP code etc in the US.

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Contact Datahut (https://datahut.co/) for more information and a fresh data set. We give this data for free for startups, journalists bloggers, researchers, analysts, etc.

Quadrant's location data contains 16 attributes, including standard attributes such as Latitude, Longitude, and Timestamp, and non-standard attributes such as Geohash. Our historical data spans as far back as 2019.

We conduct stringent evaluations on supplier feeds to ensure authenticity and quality. Our proprietary algorithms detect and cleanse corrupted and duplicated data points - allowing you to leverage our datasets rapidly with minimal data processing or cleaning.

Quadrant’s mobile location data is processed through a deduplicating algorithm that focuses on a combination of four important attributes: Device ID, Latitude, Longitude, and Timestamp. This algorithm scours our data and identifies rows that contain the same combination of these four attributes. Post-identification, it retains a single copy and eliminates duplicate values to ensure our customers only pay for complete and unique datasets.

We actively identify overlapping values at the supply level to determine the value each supplier offers. Our data science team has developed a sophisticated overlap analysis model that helps us maintain a high-quality data feed by qualifying suppliers based on unique data values rather than volumes alone – measures that provide significant benefits to our buyers.

Through our in-house data science team, we offer sophisticated technical documentation, location data algorithms, and queries that help data buyers get a headstart on their analyses.

Quadrant’s Data Noise Algorithm weeds out events that occurred seven days before the data is received (unless historical data is requested). By filtering these outdated events, we ensure that the data we deliver to our customers is recent and relevant. Reducing latency also decreases file sizes, which results in more efficient data delivery.

Our world is more connected than ever. Our smartphone has become the most important device for surfing the Internet, checking the latest news and shopping online. In contrast, we also live in a world where we watch TV, listen to the Radio and cut out coupons from newspapers and flyers. Outside, we pass by Billboards and see screens with advertisements in elevators and supermarkets on a daily basis. This world seems far removed from the online world. It seems a challenge to bridge the gap between online and offline consumer behavior. But with the right tools and the right data, this is easier than you think.

Mobile Location data connects the online and offline world. We are able to analyze any location in the world with the help of smartphones that anonymously share their location when they pass by a predefined area (geofence).

The process for collecting location data involves several steps, including anonymization. Users consent to the sharing of their location data by logging in when prompted in an app or browser. SDKs then collect and transmit information about a user's location, including geographic coordinates and time spent. The location data is then cleansed, anonymized and merged into a database to create specific consumer profiles.

Privacy

The processing of the data is also crucial in order to guarantee the privacy of the user. For example, we anonymize the locations of users by linking them to a zip code or by making the residential address inaccurate so that it cannot be traced to a specific address and therefore person.

For retargeting purposes device IDs will be pushed to publishers like Facebook and Google DV360. These device IDs will never be provided to our clients. There is a one-to-one connection between our database and the publisher platforms without any interaction needed by our clients.

In addition, we work continuously to maintain a watertight strategy on how personal data is handled, processed and used for campaigns - in line with the strictest privacy regulations. Furthermore, we have an action plan for deleting unused, irrelevant and outdated user data. Internal training and procedures also play an important role in regulatory compliance. All contracts of vendors and external suppliers of user data are audited to ensure regulatory compliance.

Our world is more connected than ever. Our smartphone has become the most important device for surfing the Internet, checking the latest news and shopping online. In contrast, we also live in a world where we watch TV, listen to the Radio and cut out coupons from newspapers and flyers. Outside, we pass by Billboards and see screens with advertisements in elevators and supermarkets on a daily basis. This world seems far removed from the online world. It seems a challenge to bridge the gap between online and offline consumer behavior. But with the right tools and the right data, this is easier than you think.

Mobile Location data connects the online and offline world. We are able to analyze any location in the world with the help of smartphones that anonymously share their location when they pass by a predefined area (geofence).

The process for collecting location data involves several steps, including anonymization. Users consent to the sharing of their location data by logging in when prompted in an app or browser. SDKs then collect and transmit information about a user's location, including geographic coordinates and time spent. The location data is then cleansed, anonymized and merged into a database to create specific consumer profiles.

Privacy

The processing of the data is also crucial in order to guarantee the privacy of the user. For example, we anonymize the locations of users by linking them to a zip code or by making the residential address inaccurate so that it cannot be traced to a specific address and therefore person.

For retargeting purposes device IDs will be pushed to publishers like Facebook and Google DV360. These device IDs will never be provided to our clients. There is a one-to-one connection between our database and the publisher platforms without any interaction needed by our clients.

In addition, we work continuously to maintain a watertight strategy on how personal data is handled, processed and used for campaigns - in line with the strictest privacy regulations. Furthermore, we have an action plan for deleting unused, irrelevant and outdated user data. Internal training and procedures also play an important role in regulatory compliance. All contracts of vendors and external suppliers of user data are audited to ensure regulatory compliance.

Onemata leverages direct relationships with SDK developers, Applications, and other hardware manufacturers to provide a robust aggregated raw mobile location data feed. Quality, Reliability, and Privacy are our differentiators.

All data collected, and associated partners are required to, support clear and compliant privacy notices and opt-in/out management that allow for collection, use, and distribution to 3rd parties.

Smart businesses are leveraging Onemata's Mobile Device Location Data for some of the following reasons:

-Providing quality location data. -Up to 700 million monthly active devices globally. -Low-latency and streamlined delivery. -Privacy-compliant data you can trust. -Industry-leading customer support.

• This dataset contains simulated location data for contact tracing during the Covid-19 pandemic.
• The data was generated using Python code and includes random timestamps and coordinates for a group of individuals.
• Simulation Parameters: The simulation assumed a start date of July 4th, 2020 and an end date of July 5th, 2020, with latitude and longitude ranges of [13.0, 13.3] and [77.5, 77.7], respectively.
• Data: The dataset includes data for 10 individuals with randomly generated names.
• Use: This dataset can be used for research and analysis of contact tracing methods and their effectiveness.

This data set provides spatially explicit estimates of the area directly used for surface mining on a global scale. It contains more than 21,000 polygons of activities related to mining, mainly of coal and metal ores.

Several data sources were compiled to identify the approximate location of mines active at any time between the years 2000 to 2017. This data set does not cover all existing mining locations across the globe. The polygons were delineated by experts using Sentinel-2 cloudless (https://s2maps.eu by EOX IT Services GmbH (contains modified Copernicus Sentinel data 2017 & 2018)) and very high-resolution satellite images available from Google Satellite and Bing Imagery. The derived polygons cover the direct land used by mining activities, including open cuts, tailing dams, waste rock dumps, water ponds, and processing infrastructure.

The ZIP file contains:

• The main data set consists of a GeoPackage (GPKG) file, including the following variables: ISO3_CODE
• The summary of the mining area per country is available in comma-separated values (CSV) file, including the following variables: ISO3_CODE
• Grid data sets with the mining area per cell were derived from the polygons. The grid data is available at: 30 arc-second resolution (approximately 1x1 km at the equator), 5 arc-minute (approximately 10x10 km at the equator), 30 arc-minute resolution (approximately 55x55 km at the equator).
  • global_miningarea_v1_30arcsecond.tif
  • global_miningarea_v1_5arcminute.tif
  • global_miningarea_v1_30arcminute.tif
• We performed an independent validation of the mining data set using control points. For that, we draw a 1,000 random samples stratified between two classes: mine and no-mine. The control points are also available as a GPKG file, including the variables: MAPPED

Source: https://doi.pangaea.de/10.1594/PANGAEA.910894

Always use the following citation when using this data: Maus, Victor; Giljum, Stefan; Gutschlhofer, Jakob; da Silva, Dieison M; Probst, Michael; Gass, Sidnei L B; Luckeneder, Sebastian; Lieber, Mirko; McCallum, Ian (2020): Global-scale mining polygons (Version 1). PANGAEA, https://doi.org/10.1594/PANGAEA.910894

License: Creative Commons Attribution-ShareAlike 4.0 International

An Open Context "predicates" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Variables" record is part of the "Iraq Heritage Program" data publication.

The location analytics market size reached USD 14.05 Billion in 2020 and is expected to reach a market a size of USD 43.57 Billion by 2028 and register a CAGR of 15.3%. Location analytics industry report classifies global market by share, trend, and on the basis of component, location, application, end-use, and region

National database of grocery store locations (address level)

The Food Access Research Atlas:

Presents a spatial overview of food access indicators for low-income and other census tracts using different measures of supermarket accessibility; Provides food access data for populations within census tracts; and Offers census-tract-level data on food access that can be downloaded for community planning or research purposes.

What can you do with the Atlas?

Create maps showing food access indicators by census tract using different measures and indicators of supermarket accessibility; View indicators of food access for selected subpopulations; and Download census-tract-level data on food access measures.

Layers and Tables

Legend

DATASET

Snapshot img

Location-Based Services (LBS) Market Forecast 2023-2027

The location-based services (LBS) market size is forecast to increase by USD 167.69 billion at a CAGR of 26.22% between 2022 and 2027. Market expansion hinges on factors such as escalating demand for personal and enterprise navigation services, widespread usage of mobile computing devices, and swift integration of beacon technology. Location-based services, integral to software applications, utilize location data on IP-capable mobile devices to pinpoint device locations. This fusion of technologies enables precise tracking and tracing functionalities, catering to diverse needs ranging from personal navigation to enterprise solutions.

What will be the size of the Market During the Forecast Period?

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Market Segmentation

This market report extensively covers market segmentation by component (hardware, software, and services), type (outdoor and indoor), and geography (North America, Europe, APAC, South America, and the Middle East and Africa). It also includes an in-depth analysis of drivers, trends, and challenges. Furthermore, the report includes historic market data from 2017 to 2021.

Market Segmentation By Component

Considering the realm of Location-Based Services (LBS), the convergence of UWB (Ultra-Wideband), RFID (Radio-Frequency Identification), and BLE (Bluetooth Low Energy) technologies has ushered in a new era of connectivity. Leveraging IP addresses and geolocation data, businesses can tap into the vast network of connected devices to deliver tailored experiences. The MarTech series is abuzz with innovations in IoT devices, AR/VR technologies, and location-based technologies, aiming to enhance the accuracy and relevance of services provided. With a focus on delivering immersive virtual experiences and leveraging augmented reality (AR)/VR technologies, location intelligence is harnessed to fuel location-based advertising and contextual advertising campaigns. Through the seamless integration of mobile phones, tablets, and other devices, LBS providers are poised to redefine consumer engagement, offering personalized solutions tailored to individual preferences and behaviors.

The market share growth by the hardware segment will be significant during the forecast period. They include passive and active radio frequency identification (RFID) tags, beacons, and sensors. They can use existing infrastructure like Wi-Fi access points or might require upgrading of the prevalent infrastructure with components like infrared (IR) sensors and RFID or sonar components as per requirements. For instance, Hewlett Packard Enterprise Development provides Aruba Tags that produce location-based data within the range of BLE-enabled access points.

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The hardware segment shows a gradual increase in the market share of USD 11.42 billion in 2017 and continue to grow by 2021. Aruba tags have other features like batteries that require minimal maintenance as well as compatibility with medical applications and can be remotely controlled and easily deployed. Moreover, components used like RFID tags are economical and offered by numerous vendors such as AiRISTA Flow. They also have motion sensors to determine the transmission intervals, which help in battery usage optimization. Hence, other factors are likely to contribute to the growth of the market during the forecast period.

Market Segmentation By Type

The outdoor location-based services segment plays a vital role in improving the response times of emergency services. This ensures that government and local authorities can build cities keeping in mind population density from heat map which also enables public transport managers to predict and adjust routes to match the actual and future needs of commuters. This helps reduce congestion, improve safety, and optimize traffic clearance. Moreover, they help provide retailers, developers, and franchises with key location-based insights on which they can further leverage AI and other technologies to improve customer relationship management (CRM) and business intelligence (BI). Banks can utilize location-based data to drive branch expansion, optimize their regional promotions. Hence the above factors are likely to boost the growth of the market during the forecast period.

Regional Overview

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North America is estimated to contribute 48% to the growth of the global market during the forecast period. Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period. In the region, the US is the largest market with major vendors like major vendors such as ESRI, Alphabet Inc., Apple Inc, and Cisco Systems Inc. North America, who are also

The NSW Address Location Service web service allows the user to enter an address and pinpoint the location of that address.

The NSW Address Location Service is derived from the Geocoded Urban and Rural Address System (GURAS) database.

This web service allows users to easily integrate NSW addressing information into spatial platforms and applications.

The addressing web service provides users with a unique and unambiguous identification of an address site and its location within NSW. The ability to identify the location of an address supports a wide range of business functions including: the delivery of products and services, public safety, communication and socio-economic and demographic analysis.

The GURAS database is the authoritative property addressing system for NSW.

NOTE: Please contact the Customer HUB https://customerhub.spatial.nsw.gov.au/ for advice on datasets access.

Grid Referenced locations of tall 9,755 pharmacies in England and the point location of those which could be accurately geo-referenced Source: Health and Social Care Information Centre (HSCIC) Publisher: Neighbourhood Statistics Geographies: Grid Reference Geographic coverage: England Time coverage: 2006 Type of data: Administrative data Notes: It is important to note that the data provide information about the location of pharmacies at unique locations, and not a count of pharmacies operating in England.

Decision criteria and decision-making process in the choice of location of companies who recently completed a change of location. Topics: Characteristics of the business such as e.g. number of employees and development of number of employees, location of management, level of turnover and proportion of wage sums in the total costs; use of modern production procedures at new location; distance problems in procurement, sales and place of residence of employees; length of search for location; reasons for the search for location; choice of location according to areas or municipalities or according to trade tax or wage sum tax; decision criteria against a municipality; advantages and disadvantages of city proximity or conurbations; the significance of transport costs for choice of location; information problems in choice of location; use of external consultants; evaluation of counseling services of the chamber of commerce; most important location factors; evaluation of and utilization of government support funds; reasons for rejection of subsidies; municipal service for the business; judgement on official information policies regarding regional promotion; personal information processing and planning time period; amount of investment sum. Entscheidungskriterien und Entscheidungsprozeß bei der Standortwahl von Betrieben, die kürzlich einen Standortwechsel vollzogen haben. Themen: Charakteristika des Unternehmens wie z. B. Beschäftigtenzahl und Entwicklung der Beschäftigtenzahl, Standort der Geschäftsleitung, Umsatzhöhe und Anteil der Lohnsumme an den Gesamtkosten; Einsatz moderner Produktionsverfahren am neuen Standort; Entfernungsprobleme bei Beschaffung, Absatz und Beschäftigtenwohnort; Dauer der Standortsuche; Gründe für die Standortsuche; Standortwahl nach Gebieten oder Gemeinden bzw. nach Gewerbesteuer oder Lohnsummensteuer; Entscheidungskriterien gegen eine Gemeinde; Vor- und Nachteile von Stadtnähe bzw. von Ballungsräumen; die Bedeutung der Transportkosten für die Standortwahl; Informationsprobleme bei der Standortwahl; Hinzuziehung externer Berater; Bewertung der Beratungsleistungen der IHK; wichtigste Standortfaktoren; Bewertung und Inanspruchnahme staatlicher Fördermittel; Gründe für die Ablehnung von Subventionen; Gemeindeleistungen an das Unternehmen; Beurteilung der behördlichen Informationspolitik bezüglich regionaler Förderung; eigene Informationsverarbeitung und Planungszeitraum; Höhe der Investitionssumme.

The location analytics market is set to thrive at a strong CAGR of 14.8% during the forecast period. The market holds a share of US$ 20.66 billion in 2023, while it is anticipated to cross a value of US$ 82.14 billion by 2033.

Attributes	Details
Location Analytics Market CAGR (2023 to 2033)	14.8%
Location Analytics Market Size (2023)	US$ 20.66 billion
Location Analytics Market Size (2033)	US$ 82.14 billion

Category-wise Insights

Segment	Top Application
Top Sub-segment	Remote Monitoring
Attributes	10% gains through 2033

Segment	Top Industry Vertical
Top Sub-segment	Transportation and Logistics
Attributes	25% of the global share

During a U.S. mobile user survey conducted from March to April 2019, it was found that over half of respondents assumed that companies and brands collect location data to provide tailored advertising and offers. A total of 47 percent of respondents also stated that they thought that companies used location data to deliver relevant search results.

The Location Affordability Index is an indicator of housing and transportation costs at the neighborhood level. It gives the percentage of a given family's income estimated to be spent on housing and transportation costs in a given location for eight different household profiles. It is calculated using actual and modeled data for Census block groups in all 942 Combined Base Statistical Areas, which cover 94% of the U.S. population.

The data gives the name, address, postcode, co-ordinates and enrolment data for schools in Northern Ireland. Further information regarding schools can be found on DE's website http://apps.education-ni.gov.uk/appinstitutes/default.aspx and ETI inspection reports on their website https://www.etini.gov.uk/