The Google Maps dataset is ideal for getting extensive information on businesses anywhere in the world. Easily filter by location, business type, and other factors to get the exact data you need. The Google Maps dataset includes all major data points: timestamp, name, category, address, description, open website, phone number, open_hours, open_hours_updated, reviews_count, rating, main_image, reviews, url, lat, lon, place_id, country, and more.

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Dataset Overview

Welcome to the Google Places Comprehensive Business Dataset! This dataset has been meticulously scraped from Google Maps and presents extensive information about businesses across several countries. Each entry in the dataset provides detailed insights into business operations, location specifics, customer interactions, and much more, making it an invaluable resource for data analysts and scientists looking to explore business trends, geographic data analysis, or consumer behaviour patterns.

Key Features

• Business Details: Includes unique identifiers, names, and contact information.
• Geolocation Data: Precise latitude and longitude for pinpointing business locations on a map.
• Operational Timings: Detailed opening and closing hours for each day of the week, allowing analysis of business activity patterns.
• Customer Engagement: Data on review counts and ratings, offering insights into customer satisfaction and business popularity.
• Additional Attributes: Links to business websites, time zone information, and country-specific details enrich the dataset for comprehensive analysis.

Potential Use Cases

This dataset is ideal for a variety of analytical projects, including: - Market Analysis: Understand business distribution and popularity across different regions. - Customer Sentiment Analysis: Explore relationships between customer ratings and business characteristics. - Temporal Trend Analysis: Analyze patterns of business activity throughout the week. - Geospatial Analysis: Integrate with mapping software to visualise business distribution or cluster businesses based on location.

Dataset Structure

The dataset contains 46 columns, providing a thorough profile for each listed business. Key columns include:

• business_id: A unique Google Places identifier for each business, ensuring distinct entries.
• phone_number: The contact number associated with the business. It provides a direct means of communication.
• name: The official name of the business as listed on Google Maps.
• full_address: The complete postal address of the business, including locality and geographic details.
• latitude: The geographic latitude coordinate of the business location, useful for mapping and spatial analysis.
• longitude: The geographic longitude coordinate of the business location.
• review_count: The total number of reviews the business has received on Google Maps.
• rating: The average user rating out of 5 for the business, reflecting customer satisfaction.
• timezone: The world timezone the business is located in, important for temporal analysis.
• website: The official website URL of the business, providing further information and contact options.
• category: The category or type of service the business provides, such as restaurant, museum, etc.
• claim_status: Indicates whether the business listing has been claimed by the owner on Google Maps.
• plus_code: A sho...

Outscraper's Location Intelligence Service is a powerful and innovative tool that harnesses the rich data available from Google Maps to provide valuable Point of Interest (POI) data for businesses. This service is an excellent solution for local intelligence needs, using advanced technology to efficiently gather and analyze data from Google Maps, creating precise and relevant POI datasets​.

This Location Intelligence Service is backed by reliable and up-to-date data, thanks to Outscraper's advanced web scraping technology. This ensures that the data extracted from Google Maps is both accurate and fresh, providing a dependable source of data for your business operations and strategic planning​.

A key feature of Outscraper's Location Intelligence Service is its advanced filtering capabilities, enabling you to retrieve only the POI data you require. This means you can target specific categories, locations, and other criteria to get the most relevant and valuable data for your business needs, eliminating the need to sift through irrelevant records​.

With Outscraper, you also get worldwide coverage for your POI data needs. The service's advanced data scraping technology allows you to collect data from any country and city without limitations, making it an invaluable tool for businesses with global operations or those seeking to expand internationally​.

Outscraper provides a vast amount of data, offering the largest number of fields available to compile and enrich your POI data. With more than 40 data fields, you can create comprehensive and detailed datasets that provide deep insights into your areas of interest​.

Outscraper's Location Intelligence Service is designed to be user-friendly, even for those without coding skills. Creating a Google Maps scraping task is quick and simple with the Outscraper App Dashboard, where you select a few parameters like category, location, limits, language, and file extension to scrape data from Google Maps​.

Outscraper also offers API support, providing a fast and easy way to fetch Google Maps results in real-time. This feature is ideal for businesses that need to access location data quickly and efficiently​.

Explore APISCRAPY, your AI-powered Google Map Data Scraper. Easily extract Business Location Data from Google Maps and other platforms. Seamlessly access and utilize publicly available map data for your business needs. Scrape All Publicly Available Data From Google Maps & Other Platforms.

Are you looking to identify B2B leads to promote your business, product, or service? Outscraper Google Maps Scraper might just be the tool you've been searching for. This powerful software enables you to extract business data directly from Google's extensive database, which spans millions of businesses across countless industries worldwide.

Outscraper Google Maps Scraper is a tool built with advanced technology that lets you scrape a myriad of valuable information about businesses from Google's database. This information includes but is not limited to, business names, addresses, contact information, website URLs, reviews, ratings, and operational hours.

Whether you are a small business trying to make a mark or a large enterprise exploring new territories, the data obtained from the Outscraper Google Maps Scraper can be a treasure trove. This tool provides a cost-effective, efficient, and accurate method to generate leads and gather market insights.

By using Outscraper, you'll gain a significant competitive edge as it allows you to analyze your market and find potential B2B leads with precision. You can use this data to understand your competitors' landscape, discover new markets, or enhance your customer database. The tool offers the flexibility to extract data based on specific parameters like business category or geographic location, helping you to target the most relevant leads for your business.

In a world that's growing increasingly data-driven, utilizing a tool like Outscraper Google Maps Scraper could be instrumental to your business' success. If you're looking to get ahead in your market and find B2B leads in a more efficient and precise manner, Outscraper is worth considering. It streamlines the data collection process, allowing you to focus on what truly matters – using the data to grow your business.

https://outscraper.com/google-maps-scraper/

As a result of the Google Maps scraping, your data file will contain the following details:

Query Name Site Type Subtypes Category Phone Full Address Borough Street City Postal Code State Us State Country Country Code Latitude Longitude Time Zone Plus Code Rating Reviews Reviews Link Reviews Per Scores Photos Count Photo Street View Working Hours Working Hours Old Format Popular Times Business Status About Range Posts Verified Owner ID Owner Title Owner Link Reservation Links Booking Appointment Link Menu Link Order Links Location Link Place ID Google ID Reviews ID

If you want to enrich your datasets with social media accounts and many more details you could combine Google Maps Scraper with Domain Contact Scraper.

Domain Contact Scraper can scrape these details:

Email Facebook Github Instagram Linkedin Phone Twitter Youtube

Discover the booming Google Maps Platform consulting market! Our analysis reveals a $2B market in 2025 projected to reach $6B by 2033, driven by location intelligence and online service adoption. Explore key trends, regional insights, and leading companies shaping this dynamic landscape.

Google Data with verified US business listings from Google Maps, including locations, reviews, hours, and ratings. This Google Data is updated weekly and fully customizable — ideal for lead scoring, market mapping, location analysis, and CRM enrichment.

Data includes reviews of different restaurants on Google Maps. There are 1100 comments in total and pictures of each comment in the data set. The data is labeled according to 4 classes (Taste, Menu, Indoor atmosphere, Outdoor atmosphere) for the artificial intelligence to predict. The dataset has been prepared in a way that can be used in both text processing and image processing fields.

The dataset contains the following columns: business_name, author_name, text, photo, rating, rating_category

IMPORTANT: The rating_category column is related to the photo of the review. If you want to use this dataset for NLP, you need to label it yourself. I will label it for you when I am available.

The digital map market, currently valued at $25.55 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 13.39% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing adoption of location-based services (LBS) across diverse sectors like automotive, logistics, and smart city initiatives is a primary catalyst. Furthermore, advancements in technologies such as AI, machine learning, and high-resolution satellite imagery are enabling the creation of more accurate, detailed, and feature-rich digital maps. The shift towards cloud-based deployment models offers scalability and cost-effectiveness, further accelerating market growth. While data privacy concerns and the high initial investment costs for sophisticated mapping technologies present some challenges, the overall market outlook remains overwhelmingly positive. The competitive landscape is dynamic, with established players like Google, TomTom, and ESRI vying for market share alongside innovative startups offering specialized solutions. The segmentation of the market by solution (software and services), deployment (on-premise and cloud), and industry reveals significant opportunities for growth in sectors like automotive navigation, autonomous vehicle development, and precision agriculture, where real-time, accurate mapping data is crucial. The Asia-Pacific region, driven by rapid urbanization and technological advancements in countries like China and India, is expected to witness particularly strong growth. The market's future hinges on continuous innovation. We anticipate a rise in the demand for 3D maps, real-time updates, and integration with other technologies like the Internet of Things (IoT) and augmented reality (AR). Companies are focusing on enhancing the accuracy and detail of their maps, incorporating real-time traffic data, and developing tailored solutions for specific industry needs. The increasing adoption of 5G technology promises to further boost the market by enabling faster data transmission and real-time updates crucial for applications like autonomous driving and drone delivery. The development of high-precision mapping solutions catering to specialized sectors like infrastructure management and disaster response will also fuel future growth. Ultimately, the digital map market is poised for continued expansion, driven by technological advancements and increased reliance on location-based services across a wide spectrum of industries. Recent developments include: December 2022 - The Linux Foundation has partnered with some of the biggest technology companies in the world to build interoperable and open map data in what is an apparent move t. The Overture Maps Foundation, as the new effort is called, is officially hosted by the Linux Foundation. The ultimate aim of the Overture Maps Foundation is to power new map products through openly available datasets that can be used and reused across applications and businesses, with each member throwing their data and resources into the mix., July 27, 2022 - Google declared the launch of its Street View experience in India in collaboration with Genesys International, an advanced mapping solutions company, and Tech Mahindra, a provider of digital transformation, consulting, and business re-engineering solutions and services. Google, Tech Mahindra, and Genesys International also plan to extend this to more than around 50 cities by the end of the year 2022.. Key drivers for this market are: Growth in Application for Advanced Navigation System in Automotive Industry, Surge in Demand for Geographic Information System (GIS); Increased Adoption of Connected Devices and Internet. Potential restraints include: Complexity in Integration of Traditional Maps with Modern GIS System. Notable trends are: Surge in Demand for GIS and GNSS to Influence the Adoption of Digital Map Technology.

GapMaps Live is an easy-to-use location intelligence platform available across 25 countries globally that allows you to visualise your own store data, combined with the latest demographic, economic and population movement intel right down to the micro level so you can make faster, smarter and surer decisions when planning your network growth strategy.

With one single login, you can access the latest estimates on resident and worker populations, census metrics (eg. age, income, ethnicity), consuming class, retail spend insights and point-of-interest data across a range of categories including fast food, cafe, fitness, supermarket/grocery and more.

Some of the world's biggest brands including McDonalds, Subway, Burger King, Anytime Fitness and Dominos use GapMaps Live Map Data as a vital strategic tool where business success relies on up-to-date, easy to understand, location intel that can power business case validation and drive rapid decision making.

Primary Use Cases for GapMaps Live Map Data include:

1. Retail Site Selection - Identify optimal locations for future expansion and benchmark performance across existing locations.
2. Customer Profiling: get a detailed understanding of the demographic profile of your customers and where to find more of them.
3. Analyse your catchment areas at a granular grid levels using all the key metrics
4. Target Marketing: Develop effective marketing strategies to acquire more customers.
5. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)
6. Customer Profiling
7. Target Marketing
8. Market Share Analysis

Some of features our clients love about GapMaps Live Map Data include: - View business locations, competitor locations, demographic, economic and social data around your business or selected location - Understand consumer visitation patterns (“where from” and “where to”), frequency of visits, dwell time of visits, profiles of consumers and much more. - Save searched locations and drop pins - Turn on/off all location listings by category - View and filter data by metadata tags, for example hours of operation, contact details, services provided - Combine public data in GapMaps with views of private data Layers - View data in layers to understand impact of different data Sources - Share maps with teams - Generate demographic reports and comparative analyses on different locations based on drive time, walk time or radius. - Access multiple countries and brands with a single logon - Access multiple brands under a parent login - Capture field data such as photos, notes and documents using GapMaps Connect and integrate with GapMaps Live to get detailed insights on existing and proposed store locations.

Comprehensive business dataset extracted from Google Maps containing 21 data points per business including contact information, ratings, hours, and location data.

Scrape business and place information from Google Maps in real time. Get addresses, phone numbers, websites, ratings, reviews, photos, business hours, and location coordinates. Useful for business directories, store locators, review analytics, and local search tools.

As of October 2020, the average amount of mobile data used by Apple Maps per 20 minutes was 1.83 MB, while Google maps used only 0.73 MB. Waze, which is also owned by Google, used the least amount at 0.23 MB per 20 minutes.

This case study document provides information on how Google Maps is using our open datasets and articulates citizen benefits.

Web map tile service (WMTS), which enables viewing of cadastral map both in digital and analogue form. Data are provided in a form of map tiles in WGS84/Pseudo-Mercator coordinate reference system. A Google Maps compatible scale set is used. The service fulfills the OGC WMTS 1.0.0 standard. The service is publicly available, free-of-charge and covers the whole territory of the Czech Republic. All layers except overview map are provided in levels 17 (1 : 4 265) to 25 (1 : 16).

Dataset

This dataset was created by Rohit Raghuram Murarishetti

Contents

The Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (guis_geomorphology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (guis_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (guis_geomorphology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (guis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (guis_geomorphology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (guis_geomorphology_metadata_faq.pdf). Please read the guis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (guis_geomorphology_metadata.txt or guis_geomorphology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:26,000 and United States National Map Accuracy Standards features are within (horizontally) 13.2 meters or 43.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

The National Geologic Map Database (NGMDB) is a Congressionally mandated national archive of geoscience maps, reports, and stratigraphic information. The Geologic Mapping Act of 1992 and its Reauthorizations calls for the U.S. Geological Survey and the Association of American State Geologists (AASG) to cooperatively build this national archive, according to technical and scientific standards whose development is coordinated by the NGMDB. The NGMDB consists of a comprehensive set of publication citations, stratigraphic nomenclature, downloadable content in raster and vector formats, unpublished source information, and guidance on standards development. The NGMDB contains information on more than 110,000 maps and related geoscience reports published from the early 1800s to the present day, by more than 630 agencies, universities, associations, and private companies.

Author: E Gunderson, educator, Minnesota Alliance for Geographic EducationGrade/Audience: grade 8, high schoolResource type: lessonSubject topic(s): gisRegion: united statesStandards: Minnesota Social Studies Standards

Standard 1. People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context.Objectives: Students will be able to:

1. Create a custom map using Google Maps
2. Collect and plot data using Google MapsSummary: Students will learn the basics of Google Maps while using geospatial data to create their neighborhood map with the places they spend time. They will also collect data of their choice from another source (website, book, personal life) and plot the data using Google Maps.

The Google Reviews dataset is perfect for obtaining comprehensive insights into businesses and their customer feedback globally. Easily filter by location, business type, or reviewer details to extract the precise data you need. The Google Reviews dataset includes key data points such as URL, place ID, place name, country, address, review ID, reviewer name, total reviews and photos by the reviewer, reviewer profile URL, and more. This dataset provides valuable information for sentiment analysis, business comparisons, and customer behavior studies.