{"title":"Complete Location Datasets – Global Brand Store Locations (CSV \u0026 GeoJSON)","description":"\u003ch1 data-end=\"824\" data-start=\"745\"\u003e\u003cstrong data-end=\"822\" data-start=\"745\"\u003eComplete Location Datasets – Global Brand Store Locations (CSV \u0026amp; GeoJSON)\u003c\/strong\u003e\u003c\/h1\u003e\n\u003cp data-end=\"1129\" data-start=\"829\"\u003eExplore a curated collection of \u003cstrong data-end=\"891\" data-start=\"861\"\u003ecomplete location datasets\u003c\/strong\u003e featuring store locations from well-known global brands across multiple industries.\u003cbr data-end=\"978\" data-start=\"975\"\u003eThese datasets provide \u003cstrong data-end=\"1048\" data-start=\"1003\"\u003efull coverage of Points of Interest (POI)\u003c\/strong\u003e, designed for professional use in analytics, mapping, and business intelligence.\u003c\/p\u003e\n\u003cp data-end=\"1287\" data-start=\"1134\"\u003eAll datasets are sourced using \u003cstrong data-end=\"1199\" data-start=\"1165\"\u003eOpenStreetMap and Overpass API\u003c\/strong\u003e, then cleaned, validated, and standardized to ensure high data quality and consistency.\u003c\/p\u003e\n\u003ch2 data-end=\"1338\" data-start=\"1300\" data-section-id=\"17b676n\"\u003eWhat’s Included in Each Dataset\u003c\/h2\u003e\n\u003cp data-end=\"1370\" data-start=\"1343\"\u003eEach full dataset contains:\u003c\/p\u003e\n\u003cul data-end=\"1603\" data-start=\"1375\"\u003e\n\u003cli data-end=\"1439\" data-start=\"1375\" data-section-id=\"1cqvxjr\"\u003eComplete store coverage (hundreds to thousands of locations)\u003c\/li\u003e\n\u003cli data-end=\"1489\" data-start=\"1442\" data-section-id=\"13ji6pj\"\u003eAccurate latitude and longitude coordinates\u003c\/li\u003e\n\u003cli data-end=\"1526\" data-start=\"1492\" data-section-id=\"1r41yn7\"\u003eFull address and regional data\u003c\/li\u003e\n\u003cli data-end=\"1560\" data-start=\"1529\" data-section-id=\"7u3gfc\"\u003eBrand and location metadata\u003c\/li\u003e\n\u003cli data-end=\"1601\" data-start=\"1563\" data-section-id=\"13m0t9\"\u003eStructured formats (CSV \u0026amp; GeoJSON)\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-end=\"1647\" data-start=\"1606\"\u003eAll files are ready for immediate use in:\u003c\/p\u003e\n\u003cul data-end=\"1814\" data-start=\"1652\"\u003e\n\u003cli data-end=\"1680\" data-start=\"1652\" data-section-id=\"c50p3m\"\u003eGIS tools (QGIS, ArcGIS)\u003c\/li\u003e\n\u003cli data-end=\"1729\" data-start=\"1683\" data-section-id=\"p059iy\"\u003eData analysis workflows (Python, R, Excel)\u003c\/li\u003e\n\u003cli data-end=\"1778\" data-start=\"1732\" data-section-id=\"17st6b0\"\u003eDashboards and business intelligence tools\u003c\/li\u003e\n\u003cli data-end=\"1812\" data-start=\"1781\" data-section-id=\"1ndlr7e\"\u003eWeb and mobile applications\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2 data-end=\"1860\" data-start=\"1825\" data-section-id=\"fy7cve\"\u003eAvailable Dataset Categories\u003c\/h2\u003e\n\u003cp data-end=\"1929\" data-start=\"1865\"\u003eOur datasets cover a wide range of global brands and industries:\u003c\/p\u003e\n\u003cul data-end=\"2235\" data-start=\"1934\"\u003e\n\u003cli data-end=\"2009\" data-start=\"1934\" data-section-id=\"19msbzo\"\u003e\n\u003ca href=\"https:\/\/www.datalocatr.com\/collections\/supermarket-location-datasets\" title=\"Supermarkets \u0026amp;amp; Grocery Chains\"\u003e\u003cstrong data-end=\"1969\" data-start=\"1936\"\u003eSupermarkets \u0026amp; Grocery Chains\u003c\/strong\u003e\u003c\/a\u003e (Aldi, Lidl, Carrefour, Albert Heijn)\u003c\/li\u003e\n\u003cli data-end=\"2086\" data-start=\"2012\" data-section-id=\"17lraq0\"\u003e\n\u003ca href=\"https:\/\/www.datalocatr.com\/collections\/fast-food-restaurant-location-datasets\" title=\"Restaurants \u0026amp; Fast Food Chains\"\u003e\u003cstrong data-end=\"2048\" data-start=\"2014\"\u003eRestaurants \u0026amp; Fast Food Chains\u003c\/strong\u003e\u003c\/a\u003e (McDonald’s, Domino’s, KFC, Subway)\u003c\/li\u003e\n\u003cli data-end=\"2147\" data-start=\"2089\" data-section-id=\"1qyu9vo\"\u003e\n\u003cstrong data-end=\"2118\" data-start=\"2091\"\u003eFashion \u0026amp; Retail Brands\u003c\/strong\u003e (ZARA, H\u0026amp;M, Nike, Primark)\u003c\/li\u003e\n\u003cli data-end=\"2191\" data-start=\"2150\" data-section-id=\"1mwqixx\"\u003e\u003cstrong data-end=\"2189\" data-start=\"2152\"\u003eConvenience Stores \u0026amp; Gas Stations\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli data-end=\"2233\" data-start=\"2194\" data-section-id=\"dgd2e4\"\u003eAnd many more global brand datasets\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2 data-end=\"2262\" data-start=\"2246\" data-section-id=\"yhqpv9\"\u003eUse Cases\u003c\/h2\u003e\n\u003cp data-end=\"2320\" data-start=\"2267\"\u003eThese datasets are built for real-world applications:\u003c\/p\u003e\n\u003cul data-end=\"2542\" data-start=\"2325\"\u003e\n\u003cli data-end=\"2359\" data-start=\"2325\" data-section-id=\"1721911\"\u003eMarket and competitor analysis\u003c\/li\u003e\n\u003cli data-end=\"2406\" data-start=\"2362\" data-section-id=\"iqmr7k\"\u003eLocation intelligence and site selection\u003c\/li\u003e\n\u003cli data-end=\"2446\" data-start=\"2409\" data-section-id=\"2z2biz\"\u003eProximity and geospatial analysis\u003c\/li\u003e\n\u003cli data-end=\"2480\" data-start=\"2449\" data-section-id=\"1jhewnn\"\u003eStore network visualization\u003c\/li\u003e\n\u003cli data-end=\"2540\" data-start=\"2483\" data-section-id=\"1o0bi0b\"\u003eData enrichment with demographic or mobility datasets\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2 data-end=\"2582\" data-start=\"2553\" data-section-id=\"1gjhc1y\"\u003eData Quality \u0026amp; Updates\u003c\/h2\u003e\n\u003cp data-end=\"2717\" data-start=\"2587\"\u003eAll datasets are regularly updated to reflect real-world changes, including new openings and closures.\u003cbr data-end=\"2692\" data-start=\"2689\"\u003eEach download includes:\u003c\/p\u003e\n\u003cul data-end=\"2821\" data-start=\"2722\"\u003e\n\u003cli data-end=\"2761\" data-start=\"2722\" data-section-id=\"1ttxi4e\"\u003eClean dataset files (CSV \u0026amp; GeoJSON)\u003c\/li\u003e\n\u003cli data-end=\"2790\" data-start=\"2764\" data-section-id=\"1kblpfb\"\u003eMetadata documentation\u003c\/li\u003e\n\u003cli data-end=\"2819\" data-start=\"2793\" data-section-id=\"unjlgq\"\u003eChangelog with updates\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2 data-end=\"2859\" data-start=\"2832\" data-section-id=\"1bgruzs\"\u003eFrom Sample to Scale\u003c\/h2\u003e\n\u003cp data-end=\"2991\" data-start=\"2864\"\u003eLooking to test first? Start with a \u003ca title=\"free sample dataset\" href=\"https:\/\/www.datalocatr.com\/collections\/free-location-datasets\"\u003efree sample dataset\u003c\/a\u003e to evaluate structure and quality before upgrading to the full version.\u003c\/p\u003e\n\u003cp data-end=\"3111\" data-start=\"3004\"\u003e\u003cem data-end=\"3111\" data-start=\"3007\"\u003eAccess complete, ready-to-use location datasets and power your projects with reliable geospatial data.\u003c\/em\u003e\u003c\/p\u003e","products":[{"product_id":"mcdonalds-europe-verified-locations-dataset-csv-geojson","title":"McDonald's Europe – Verified Locations Dataset (CSV, GeoJSON)","description":"\u003cp data-start=\"1875\" data-end=\"2222\"\u003eThis dataset provides a complete, up-to-date overview of McDonald’s restaurant locations across Europe.\u003cbr data-start=\"1978\" data-end=\"1981\"\u003eAll records are sourced, structured, and verified using OpenStreetMap through Overpass API queries.\u003cbr data-start=\"2080\" data-end=\"2083\"\u003eEach location includes accurate latitude\/longitude coordinates, address attributes, brand metadata,\u003cbr data-start=\"2182\" data-end=\"2185\"\u003eand opening hours (when available).\u003c\/p\u003e\n\u003cp data-start=\"2224\" data-end=\"2395\"\u003eAll files have been cleaned, validated, and standardized for immediate use in GIS tools, data analysis,\u003cbr data-start=\"2327\" data-end=\"2330\"\u003ebusiness intelligence dashboards, or location-based applications.\u003c\/p\u003e\n\u003cp data-start=\"2397\" data-end=\"2433\"\u003eWhat you can do with this dataset:\u003c\/p\u003e\n\u003cul data-start=\"2434\" data-end=\"2629\"\u003e\n\u003cli data-start=\"2434\" data-end=\"2463\"\u003e\n\u003cp data-start=\"2436\" data-end=\"2463\"\u003eBuild maps and dashboards\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli data-start=\"2464\" data-end=\"2490\"\u003e\n\u003cp data-start=\"2466\" data-end=\"2490\"\u003eRun proximity analysis\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli data-start=\"2491\" data-end=\"2531\"\u003e\n\u003cp data-start=\"2493\" data-end=\"2531\"\u003eStudy regional distribution patterns\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli data-start=\"2532\" data-end=\"2583\"\u003e\n\u003cp data-start=\"2534\" data-end=\"2583\"\u003eIntegrate locations into apps or internal tools\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli data-start=\"2584\" data-end=\"2629\"\u003e\n\u003cp data-start=\"2586\" data-end=\"2629\"\u003eCombine with demographic or mobility data\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-start=\"2631\" data-end=\"2722\"\u003eThe dataset is updated regularly, and each download includes a changelog and metadata file.\u003c\/p\u003e\n\u003cp data-start=\"2631\" data-end=\"2722\"\u003eThis product includes data from OpenStreetMap contributors, licensed under the Open Database License (ODbL) 1.0.\u003cbr data-start=\"3245\" data-end=\"3248\"\u003e© OpenStreetMap contributors.\u003c\/p\u003e","brand":"McDonald’s","offers":[{"title":"Netherlands \/ CSV","offer_id":56553817342283,"sku":"UFMC84920141","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Netherlands \/ GeoJSON","offer_id":56553845981515,"sku":"UFMC84920142","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Belgium \/ CSV","offer_id":56553817375051,"sku":"UFMC84920143","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Belgium \/ GeoJSON","offer_id":56553846014283,"sku":"UFMC84920144","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Germany \/ CSV","offer_id":56553817407819,"sku":"UFMC84920145","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Germany \/ GeoJSON","offer_id":56553846047051,"sku":"UFMC84920146","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"United Kingdom \/ CSV","offer_id":57762381332811,"sku":"UFMC84920147","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"United Kingdom \/ GeoJSON","offer_id":57762381365579,"sku":"UFMC84920148","price":15.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0982\/1936\/0587\/files\/Gemini_Generated_Image_v23tc4v23tc4v23t.png?v=1765221648"},{"product_id":"dominos-europe-verified-locations-data-csv-geojson","title":"Domino's Europe – Verified Locations Dataset (CSV, GeoJSON)","description":"\u003cp data-end=\"2222\" data-start=\"1875\"\u003eThis dataset provides a complete, up-to-date overview of Domino's restaurant locations across Europe.\u003cbr data-end=\"1981\" data-start=\"1978\"\u003eAll records are sourced, structured, and verified using OpenStreetMap through Overpass API queries.\u003cbr data-end=\"2083\" data-start=\"2080\"\u003eEach location includes accurate latitude\/longitude coordinates, address attributes, brand metadata, and opening hours (when available).\u003c\/p\u003e\n\u003cp data-end=\"2395\" data-start=\"2224\"\u003eAll files have been cleaned, validated, and standardized for immediate use in GIS tools, data analysis,\u003cbr data-end=\"2330\" data-start=\"2327\"\u003ebusiness intelligence dashboards, or location-based applications.\u003c\/p\u003e\n\u003cp data-end=\"2433\" data-start=\"2397\"\u003eWhat you can do with this dataset:\u003c\/p\u003e\n\u003cul data-end=\"2629\" data-start=\"2434\"\u003e\n\u003cli data-end=\"2463\" data-start=\"2434\"\u003e\n\u003cp data-end=\"2463\" data-start=\"2436\"\u003eBuild maps and dashboards\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli data-end=\"2490\" data-start=\"2464\"\u003e\n\u003cp data-end=\"2490\" data-start=\"2466\"\u003eRun proximity analysis\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli data-end=\"2531\" data-start=\"2491\"\u003e\n\u003cp data-end=\"2531\" data-start=\"2493\"\u003eStudy regional distribution patterns\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli data-end=\"2583\" data-start=\"2532\"\u003e\n\u003cp data-end=\"2583\" data-start=\"2534\"\u003eIntegrate locations into apps or internal tools\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli data-end=\"2629\" data-start=\"2584\"\u003e\n\u003cp data-end=\"2629\" data-start=\"2586\"\u003eCombine with demographic or mobility data\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-end=\"2722\" data-start=\"2631\"\u003eThe dataset is updated regularly, and each download includes a changelog and metadata file.\u003c\/p\u003e\n\u003cp data-end=\"2722\" data-start=\"2631\"\u003eThis product includes data from OpenStreetMap contributors, licensed under the Open Database License (ODbL) 1.0.\u003cbr data-end=\"3248\" data-start=\"3245\"\u003e© OpenStreetMap contributors.\u003c\/p\u003e","brand":"Domino's","offers":[{"title":"Netherlands \/ CSV","offer_id":56553894281547,"sku":"UFDM84920141","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Netherlands \/ GeoJSON","offer_id":56553894314315,"sku":"UFDM84920142","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Belgium \/ CSV","offer_id":56553894347083,"sku":"UFDM84920143","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Belgium \/ GeoJSON","offer_id":56553894379851,"sku":"UFDM84920144","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Germany \/ CSV","offer_id":56553894412619,"sku":"UFDM84920145","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Germany \/ GeoJSON","offer_id":56553894445387,"sku":"UFDM84920146","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"France \/ CSV","offer_id":56553964962123,"sku":"UFDM84920147","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"France \/ GeoJSON","offer_id":56553964994891,"sku":"UFDM84920148","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Luxembourg \/ CSV","offer_id":56553965027659,"sku":"UFDM84920149","price":5.0,"currency_code":"EUR","in_stock":true},{"title":"Luxembourg \/ GeoJSON","offer_id":56553965060427,"sku":"UFDM84920150","price":5.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0982\/1936\/0587\/files\/dominos-pizza-locations-dataset-map-visual.png?v=1776802114"},{"product_id":"aldi-supermarkets-europe-verified-locations-dataset-csv-geojson","title":"ALDI Supermarkets Europe – Verified Locations Dataset (CSV, GeoJSON)","description":"\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThis dataset provides a structured and up-to-date overview of ALDI supermarket locations across Europe, including both \u003c\/span\u003e\u003ca href=\"https:\/\/www.datalocatr.com\/pages\/aldi-locations-germany\"\u003e\u003cstrong\u003e\u003cspan\u003eALDI Nord\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e and \u003c\/span\u003e\u003cstrong\u003e\u003cspan\u003eALDI Süd\u003c\/span\u003e\u003c\/strong\u003e\u003c\/a\u003e\u003cspan\u003e store networks. Each record represents a verified store location and includes detailed geographic and address information suitable for mapping, analytics, and location intelligence.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eALDI operates as two independent groups, ALDI Nord and ALDI Süd, each with its own regional store distribution across Europe. This dataset captures locations from both organizations, making it particularly valuable for understanding full market coverage and regional differences within the ALDI network.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eAll records are sourced and structured using OpenStreetMap data through Overpass API queries, ensuring reliable and standardized location data. Each entry includes precise latitude and longitude coordinates, store name, address attributes, brand classification (ALDI Nord or ALDI Süd), and opening hours when available.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe dataset has been cleaned, validated, and standardized so it can be used immediately in GIS tools, mapping software, business intelligence dashboards, or custom applications.\u003c\/span\u003e\u003c\/p\u003e\n\u003cdiv\u003e\u003chr\u003e\u003c\/div\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cstrong\u003e\u003cspan\u003eWhat you can do with this dataset\u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThis dataset is suitable for a wide range of retail analytics and geospatial applications, including:\u003c\/span\u003e\u003c\/p\u003e\n\u003cul data-spread=\"false\"\u003e\n\u003cli\u003e\u003cspan\u003eBuilding interactive maps of ALDI store locations across Europe\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\n\u003cspan\u003eAnalyzing the geographic distribution of \u003c\/span\u003e\u003cstrong\u003e\u003cspan\u003eALDI Nord vs ALDI Süd\u003c\/span\u003e\u003c\/strong\u003e\n\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eRunning proximity and catchment area analysis\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eStudying supermarket density and regional retail patterns\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eIntegrating store locations into apps or internal business tools\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eCombining location data with demographic, mobility, or market datasets\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cdiv\u003e\u003chr\u003e\u003c\/div\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cstrong\u003e\u003cspan\u003eDataset format\u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe download package includes ready-to-use files:\u003c\/span\u003e\u003c\/p\u003e\n\u003cul data-spread=\"false\"\u003e\n\u003cli\u003e\u003cspan\u003eCSV – compatible with spreadsheets, databases, and analytics tools\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eGeoJSON – ideal for GIS software and mapping platforms\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eEach download also includes metadata and a changelog, allowing users to track dataset updates over time.\u003c\/span\u003e\u003c\/p\u003e\n\u003cdiv\u003e\u003chr\u003e\u003c\/div\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cstrong\u003e\u003cspan\u003eData source and license\u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThis product contains data derived from OpenStreetMap contributors, licensed under the Open Database License (ODbL) 1.0.\u003c\/span\u003e\u003cbr\u003e\u003cspan\u003e© OpenStreetMap contributors.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eThis dataset is an independent data compilation and is not affiliated with or endorsed by ALDI. All brand names are used for descriptive identification purposes only.\u003c\/span\u003e\u003c\/p\u003e","brand":"ALDI","offers":[{"title":"Netherlands \/ CSV","offer_id":56795509555531,"sku":"UFMC84920141","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Netherlands \/ GeoJSON","offer_id":56795509588299,"sku":"UFMC84920142","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Germany \/ CSV","offer_id":56795509686603,"sku":"UFMC84920145","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"Germany \/ GeoJSON","offer_id":56795509719371,"sku":"UFMC84920146","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"France \/ CSV","offer_id":56813491323211,"sku":"UFMC84920147","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"France \/ GeoJSON","offer_id":56813491355979,"sku":"UFMC84920148","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"United Kingdom \/ CSV","offer_id":57330804785483,"sku":"UFMC84920149","price":15.0,"currency_code":"EUR","in_stock":true},{"title":"United Kingdom \/ GeoJSON","offer_id":57330804818251,"sku":"UFMC84920150","price":15.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0982\/1936\/0587\/files\/Aldi-supermarket-locations-dataset-map-visual.png?v=1776802042"},{"product_id":"mcdonalds-usa-locations-dataset-verified-store-locations-csv-geojson","title":"McDonald's USA Locations Dataset – Verified Store Locations (CSV, GeoJSON)","description":"\u003ch1 data-end=\"1397\" data-start=\"1121\"\u003eMcDonald's US Store Locations Data – Complete \u0026amp; Verified Dataset\u003c\/h1\u003e\n\u003cp data-end=\"1397\" data-start=\"1121\"\u003eThis dataset provides a comprehensive and up-to-date overview of all \u003cstrong data-end=\"1246\" data-start=\"1190\"\u003eMcDonald’s restaurant locations in the United States\u003c\/strong\u003e.\u003cbr data-end=\"1250\" data-start=\"1247\"\u003eIt is designed for developers, analysts, and businesses that need reliable geospatial data without the complexity of scraping or API limitations.\u003c\/p\u003e\n\u003cp data-end=\"1547\" data-start=\"1402\"\u003eAll locations are sourced and verified using \u003cstrong data-end=\"1486\" data-start=\"1447\"\u003eOpenStreetMap data via Overpass API\u003c\/strong\u003e, then cleaned, standardized, and enriched for immediate use.\u003c\/p\u003e\n\u003cp data-end=\"1573\" data-start=\"1552\"\u003eEach record includes:\u003c\/p\u003e\n\u003cul data-end=\"1739\" data-start=\"1578\"\u003e\n\u003cli data-end=\"1625\" data-start=\"1578\" data-section-id=\"13ji6pj\"\u003eAccurate latitude and longitude coordinates\u003c\/li\u003e\n\u003cli data-end=\"1666\" data-start=\"1628\" data-section-id=\"1i18m9h\"\u003eStore address and location details\u003c\/li\u003e\n\u003cli data-end=\"1700\" data-start=\"1669\" data-section-id=\"7u3gfc\"\u003eBrand and location metadata\u003c\/li\u003e\n\u003cli data-end=\"1737\" data-start=\"1703\" data-section-id=\"ibtmzn\"\u003eOpening hours (when available)\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-end=\"1798\" data-start=\"1742\"\u003eThe dataset is structured for seamless integration into:\u003c\/p\u003e\n\u003cul data-end=\"1958\" data-start=\"1803\"\u003e\n\u003cli data-end=\"1834\" data-start=\"1803\" data-section-id=\"ns7b3q\"\u003eGIS software (QGIS, ArcGIS)\u003c\/li\u003e\n\u003cli data-end=\"1883\" data-start=\"1837\" data-section-id=\"p059iy\"\u003eData analysis workflows (Python, R, Excel)\u003c\/li\u003e\n\u003cli data-end=\"1922\" data-start=\"1886\" data-section-id=\"151r8do\"\u003eBusiness intelligence dashboards\u003c\/li\u003e\n\u003cli data-end=\"1956\" data-start=\"1925\" data-section-id=\"1ndlr7e\"\u003eWeb and mobile applications\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3 data-end=\"1985\" data-start=\"1969\" data-section-id=\"yhqpv9\"\u003eUse Cases\u003c\/h3\u003e\n\u003cp data-end=\"2018\" data-start=\"1990\"\u003eThis dataset can be used to:\u003c\/p\u003e\n\u003cul data-end=\"2291\" data-start=\"2023\"\u003e\n\u003cli data-end=\"2068\" data-start=\"2023\" data-section-id=\"2kohiu\"\u003eBuild interactive maps and store locators\u003c\/li\u003e\n\u003cli data-end=\"2116\" data-start=\"2071\" data-section-id=\"at6jai\"\u003ePerform proximity and geospatial analysis\u003c\/li\u003e\n\u003cli data-end=\"2174\" data-start=\"2119\" data-section-id=\"1lqslvv\"\u003eAnalyze market coverage and expansion opportunities\u003c\/li\u003e\n\u003cli data-end=\"2232\" data-start=\"2177\" data-section-id=\"4i2fzj\"\u003eCombine with demographic, traffic, or mobility data\u003c\/li\u003e\n\u003cli data-end=\"2289\" data-start=\"2235\" data-section-id=\"qihcbn\"\u003eEnrich internal tools or customer-facing platforms\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3 data-end=\"2326\" data-start=\"2302\" data-section-id=\"1aiy4fq\"\u003eUpdates \u0026amp; Quality\u003c\/h3\u003e\n\u003cp data-end=\"2422\" data-start=\"2331\"\u003eThe dataset is regularly updated to reflect real-world changes.\u003cbr data-end=\"2397\" data-start=\"2394\"\u003eEach download includes:\u003c\/p\u003e\n\u003cul data-end=\"2535\" data-start=\"2427\"\u003e\n\u003cli data-end=\"2467\" data-start=\"2427\" data-section-id=\"1ms2qfy\"\u003eA structured dataset (CSV or GeoJSON)\u003c\/li\u003e\n\u003cli data-end=\"2487\" data-start=\"2470\" data-section-id=\"w73vfn\"\u003eMetadata file\u003c\/li\u003e\n\u003cli data-end=\"2533\" data-start=\"2490\" data-section-id=\"6xdywq\"\u003eChangelog with updates and improvements\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3 data-end=\"2560\" data-start=\"2546\" data-section-id=\"m2nk5g\"\u003eLicense\u003c\/h3\u003e\n\u003cp data-end=\"2711\" data-start=\"2565\"\u003eThis product includes data from OpenStreetMap contributors, licensed under the Open Database License (ODbL) 1.0.\u003cbr data-end=\"2680\" data-start=\"2677\"\u003e© OpenStreetMap contributors.\u003c\/p\u003e\n\u003cp data-end=\"2711\" data-start=\"2565\"\u003e\u003cem data-end=\"2844\" data-start=\"2727\"\u003eSave time and skip complex data collection — get instant access to a ready-to-use McDonald’s USA locations dataset.\u003c\/em\u003e\u003c\/p\u003e","brand":"McDonald’s","offers":[{"title":"United States \/ CSV","offer_id":57167726608715,"sku":"UFMC84920147","price":30.0,"currency_code":"EUR","in_stock":true},{"title":"United States \/ GeoJSON","offer_id":57167726641483,"sku":"UFMC84920148","price":30.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0982\/1936\/0587\/files\/Gemini_Generated_Image_v23tc4v23tc4v23t.png?v=1765221648"}],"url":"https:\/\/www.datalocatr.com\/collections\/complete-location-datasets-global-brand-store-locations-csv-geojson.oembed","provider":"DataLocatr","version":"1.0","type":"link"}