👨‍💻 Author: Azhar Saleem

"https://github.com/azharsaleem18" target="_blank"> https://img.shields.io/badge/GitHub-Profile-blue?style=for-the-badge&logo=github" alt="GitHub Profile"> "https://www.kaggle.com/azharsaleem" target="_blank"> https://img.shields.io/badge/Kaggle-Profile-blue?style=for-the-badge&logo=kaggle" alt="Kaggle Profile"> "https://www.linkedin.com/in/azhar-saleem/" target="_blank"> https://img.shields.io/badge/LinkedIn-Profile-blue?style=for-the-badge&logo=linkedin" alt="LinkedIn Profile">
"https://www.youtube.com/@AzharSaleem19" target="_blank"> https://img.shields.io/badge/YouTube-Profile-red?style=for-the-badge&logo=youtube" alt="YouTube Profile"> "https://www.facebook.com/azhar.saleem1472/" target="_blank"> https://img.shields.io/badge/Facebook-Profile-blue?style=for-the-badge&logo=facebook" alt="Facebook Profile"> "https://www.tiktok.com/@azhar_saleem18" target="_blank"> https://img.shields.io/badge/TikTok-Profile-blue?style=for-the-badge&logo=tiktok" alt="TikTok Profile">
"https://twitter.com/azhar_saleem18" target="_blank"> https://img.shields.io/badge/Twitter-Profile-blue?style=for-the-badge&logo=twitter" alt="Twitter Profile"> "https://www.instagram.com/azhar_saleem18/" target="_blank"> https://img.shields.io/badge/Instagram-Profile-blue?style=for-the-badge&logo=instagram" alt="Instagram Profile"> "mailto:azharsaleem6@gmail.com"> https://img.shields.io/badge/Email-Contact%20Me-red?style=for-the-badge&logo=gmail" alt="Email Contact">

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...

Explore the booming Google Maps Platform consulting market: market size, growth drivers, key trends like AI integration, and restraints, with insights for large enterprises and SMEs.

The professional map services market is booming, projected to reach $625.6 million by 2025 with a 7% CAGR. Discover key trends, leading companies, and regional insights in this comprehensive market analysis. Learn about the impact of AI, IoT, and autonomous vehicles on this rapidly growing sector.

As global communities responded to COVID-19, we heard from public health officials that the same type of aggregated, anonymized insights we use in products such as Google Maps would be helpful as they made critical decisions to combat COVID-19. These Community Mobility Reports aimed to provide insights into what changed in response to policies aimed at combating COVID-19. The reports charted movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

This dataset is ideal for analyzing trends in customer feedback across different types of businesses, understanding the impact of online presence through websites on customer ratings, and exploring geographical patterns in business performance via Google Maps links. Suitable for data scientists, market analysts, or anyone interested in business analytics or sentiment analysis. ​

• Title: Name of the restaurant.
• CategoryName: Type or category of the establishment (e.g., Mexican, Asian).
• Website: URL to the establishment's official website, if available.
• URL: Google Maps URL of the establishment.
• ReviewsCount: Number of reviews the establishment has received on Google Maps.
• Stars: Average star rating of the establishment on Google Maps, on a scale from 1 to 5.
• Text: Actual text of the reviews (partially available, as some entries are missing review text).

Discover the booming digital map ecosystem market, projected to reach $450 billion by 2033. Explore key drivers, regional trends, and leading companies shaping this rapidly evolving landscape, including autonomous vehicle integration and LBS advancements. Learn more about market size, CAGR, and segmentation analysis in this comprehensive report.

Building footprint and height data were obtained from the latest global 3D building database. The building footprint data originated from Microsoft and Google datasets. Building height information was estimated using an XGBoost machine learning regression model that integrates multi-source remote sensing features. The height estimation model was trained using datasets from ONEGEO Map, Microsoft, Baidu, and EMU Analytics, utilizing 2020 data for the final estimations. Validation of this database demonstrates that the height estimation models perform exceptionally well at a global scale across both the Northern and Southern Hemispheres. The estimated heights closely match reference height data, especially for landmark buildings, showcasing superior accuracy compared to other global height products. The 3D building data that support this dataset are available in Zenodo DOI:10.5194/essd-16-5357-2024 (Che, Y., Li, X., Liu, X., Wang, Y., Liao, W., Zheng, X., Zhang, X., Xu, X., Shi, Q., Zhu, J., Yuan, H., and Dai, Y. 3D-GloBFP: the first global three-dimensional building footprint dataset. Earth System Science Data)Based on the 3D building database, we verify the locations and boundaries of individual cultural heritage sites and their buffer zones using UNESCO's heritage map platform (https://whc.unesco.org/), and categorize heritage into three groups for data extraction:Broad Scale Sites: For sites encompassing continuous building clusters or portions of cities (e.g., City of Bath), we extract buildings within the designated buffer zones provided by the UNESCO platform.Single Building Sites: For individual monuments or structures (e.g., Tower of London), we precisely extract the building footprints based on their exact coordinates.Multiple Dispersed Buildings: For sites consisting of multiple, non-contiguous structures (e.g., Wooden Churches of Southern Małopolska, Poland), we identify each location using the platform’s data and verify them through Google Maps before extracting the relevant buildings.A few linear heritage sites, such as extensive archaeological routes spanning over a thousand kilometers, are excluded due to the complexities associated with their vast spatial extent and the variability of climate conditions across different segments.The effective data coverage varies across continents: Europe and North America have an effective rate of 82.5%, Asia and the Pacific 68.3%, Latin America and the Caribbean 75.7%, Arab States 76.5%, and Africa 49.2%. This variability reflects differences in data availability. In less developed regions, remote sensing data tends to overlook non-urban heritage sites, and soil and rock structures common in Africa and Southeast Asia are more difficult to detect using satellite remote sensing techniques, leading to lower effective data coverage in these regions.This dataset accompanies the following published article:Chen, Zihua, Gao, Qian, Wu, Yajing, Li, Jiaxin, Li, Xiaowei, Li, Xiao, Wang, Zhenbo, & Cui, Haiyang (2025). World Cultural Heritage sites are under climate stress and no emissions mitigation pathways can uniformly protect them. Communications Earth & Environment, 6:628. https://doi.org/10.1038/s43247-025-02603-8

This dataset represents a yearly summary of web activity for mississauga.ca by country. This data is compiled by Google Analytics and is updated annually.

Context

I created these files and analysis as part of working on a case study for the Google Data Analyst certificate.

Question investigated: Do annual members and casual riders use Cyclistic bikes differently? Why do we want to know?: Knowing bike usage/behavior by rider type will allow the Marketing, Analytics, and Executive team stakeholders to design, assess, and approve appropriate strategies that drive profitability.

Content

I used the script noted below to clean the files and then added some additional steps to create the visualizations to complete my analysis. The additional steps are noted in corresponding R Markdown file for this data set.

Acknowledgements

Files: most recent 1 year of data available, Divvy_Trips_2019_Q2.csv, Divvy_Trips_2019_Q3.csv, Divvy_Trips_2019_Q4.csv, Divvy_Trips_2020_Q1.csv Source: Downloaded from https://divvy-tripdata.s3.amazonaws.com/index.html

Data cleaning script: followed this script to clean and merge files https://docs.google.com/document/d/1gUs7-pu4iCHH3PTtkC1pMvHfmyQGu0hQBG5wvZOzZkA/copy

Note: Combined data set has 3,876,042 rows, so you will likely need to run R analysis on your computer (e.g., R Console) rather than in the cloud (e.g., RStudio Cloud)

Inspiration

This was my first attempt to conduct an analysis in R and create the R Markdown file. As you might guess, it was an eye-opening experience, with both exciting discoveries and aggravating moments.

One thing I have not yet been able to figure out is how to add a legend to the map. I was able to get a legend to appear on a separate (empty) map, but not on the map you will see here.

I am also interested to see what others did with this analysis - what were the findings and insights you found?

South Korea Geospatial Analytics Market size was valued at USD 970 Million in 2024 and is projected to reach USD 1953 Million by 2032, growing at a CAGR of 9.1% from 2026 to 2032. Key Market Drivers:Rising Government Investments in Smart City Development: The South Korea geospatial analytics market is experiencing strong growth due to increasing government funding for smart city infrastructure and digital transformation. According to the Ministry of Land, Infrastructure and Transport (2023), South Korea allocated 1.2 Trillion (USD 900 Million) for smart city projects leveraging geospatial data. Key players like SK Telecom and LG CNS have developed AI-powered geospatial platforms for urban planning. In 2024, Naver Labs launched a 3D digital twin solution for Seoul, enhancing real-time spatial analytics. Recent news highlights Samsung SDS’s partnership with local governments to integrate geospatial AI into traffic and disaster management systems.Growing Demand for Location-Based Services in Retail & Logistics: The rapid expansion of e-commerce and last-mile delivery services is driving adoption of geospatial analytics for route optimization and customer targeting. A 2023 Korea Statistics Bureau report revealed that over 65% of logistics firms now use geospatial data for fleet management. Companies like Coupang and Baemin are implementing real-time tracking systems powered by Google Maps Platform and Kakao Mobility. In early 2024, KT (Korea Telecom) introduced an AI-driven logistics analytics tool to reduce delivery times. Recent developments include Lotte Data Communication’s geofencing solutions for personalized retail marketing.Increasing Use of Geospatial Tech in Autonomous Vehicles & Drones: The push toward autonomous mobility and drone delivery is accelerating demand for high-precision geospatial mapping and analytics. The Korean Ministry of Science and ICT (2024) reported that autonomous vehicle testing zones expanded by 30% in 2023, requiring advanced spatial data. Hyundai’s Motional and Kia are collaborating with TomTom and HERE Technologies for HD mapping. In 2024, Kakao Mobility launched a drone delivery pilot in Seoul using real-time geospatial analytics. Recent news highlights Hanwha Systems’ AI-based geospatial platform for military and civilian drone operations.

This dataset displays the number of page views each day in 2017 for mississauga.ca. This data is compiled by Google Analytics and is updated annually.

The Location Intelligence Platforms (LIP) market is booming, projected to reach $14.15B by 2025 with an 11.7% CAGR. This comprehensive analysis explores key drivers, trends, and challenges, profiling major players like Esri and Google. Discover market segmentation, regional breakdowns, and future growth predictions.

Discover the booming Location-Based Services (LBS) market! This comprehensive analysis explores market size, CAGR, key drivers, trends, and regional insights for 2025-2033. Learn about top companies and the future of location technology.

The size of the India Geospatial Analytics market was valued at USD XXX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 14.82% during the forecast period. Recent developments include: January 2023: Eris India, a company providing Geographic Information System (GIS) software and solutions, announced that the company is developing a policy map to offer data to help states and policymakers in decision-making. The Policy Maps have been designed to provide meaningful insights into various government functions., July 2022: Google announced a new partnership in India with local authorities and organizations in order to provide customized features for the diverse needs of the people in the country. Also, Google is building helpful maps that provide more visual and accurate navigation.. Key drivers for this market are: Increasing Demand of Location Based Service, Growing Availability of Spatial Data. Potential restraints include: High Initial Cost in Implementing Geospatial Analytics Solutions. Notable trends are: Increasing Demand of Location Based Service.

The Geospatial Analytics Marketsize was valued at USD 79.06 USD billion in 2023 and is projected to reach USD 202.74 USD billion by 2032, exhibiting a CAGR of 14.4 % during the forecast period. Recent developments include: February 2024: Placer.ai and Esri, a Geographic Information System (GIS) technology provider, partnered to empower customers with enhanced analytics capabilities, integrating consumer behavior analysis. Additionally, the agreement will foster collaborations to unlock further features by synergizing our respective product offerings., December 2023: CKS and Esri India Technologies Pvt Ltd teamed up to introduce the 'MMGEIS' program, focusing on students from 8th grade to undergraduates, to position India as a global leader in geospatial technology through skill development and innovation., December 2023: In collaboration with Bayanat, the UAE Space Agency revealed the initiation of the operational phase of the Geospatial Analytics Platform during its participation in organizing the Space at COP28 initiatives., November 2023: USAID unveiled its inaugural Geospatial Strategy, designed to harness geospatial data and technology for more targeted international program delivery. The strategy foresees a future where geographic methods enhance the effectiveness of USAID's efforts by pinpointing development needs, monitoring program implementation, and evaluating outcomes based on location., May 2023: TomTom International BV, a geolocation technology specialist, expanded its partnership with Alteryx, Inc. Through this partnership, Alteryx will use TomTom’s Maps APIs and location data to integrate spatial data into Alteryx’s products and location insights packages, such as Alteryx Designer., May 2023: Oracle Corporation announced the launch of Oracle Spatial Studio 23.1, available in the Oracle Cloud Infrastructure (OCI) marketplace and for on-premises deployment. Users can browse, explore, and analyze geographic data stored in and managed by Oracle using a no-code mapping tool., May 2023: CAPE Analytics, a property intelligence company, announced an enhanced insurance offering by leveraging Google geospatial data. Google’s geospatial data can help CAPE create appropriate solutions for insurance carriers., February 2023: HERE Global B.V. announced a collaboration with Cognizant, an information technology, services, and consulting company, to offer digital customer experience using location data. In this partnership, Cognizant will utilize the HERE location platform’s real-time traffic data, weather, and road attribute data to develop spatial intelligent solutions for its customers., July 2022: Athenium Analytics, a climate risk analytics company, launched a comprehensive tornado data set on the Esri ArcGIS Marketplace. This offering, which included the last 25 years of tornado insights from Athenium Analytics, would extend its Bronze partner relationship with Esri. . Key drivers for this market are: Advancements in Technologies to Fuel Market Growth. Potential restraints include: Lack of Standardization Coupled with Shortage of Skilled Workforce to Limit Market Growth. Notable trends are: Rise of Web-based GIS Platforms Will Transform Market.

The Location Intelligence Systems (LIS) market is booming, projected to reach $15.66 billion by 2025, with a 12.3% CAGR. Discover key trends, drivers, and restraints shaping this dynamic sector, including insights into leading companies and regional market shares. Explore how AI, big data, and cloud solutions are transforming location-based analytics.

The booming digital map market, valued at $9.05B in 2025 and growing at a 26.06% CAGR, is driven by location-based services, AI, and autonomous vehicles. Explore key trends, leading companies, and regional insights in this comprehensive market analysis covering navigation, geocoding, and more. Forecast to 2033.

The India Geospatial Analytics Market is booming, projected to reach $1.38 billion by 2025, with a CAGR of 14.82%. Discover key drivers, trends, restraints, and leading companies shaping this dynamic sector. Explore market segmentation by type and end-user vertical. Recent developments include: January 2023: Eris India, a company providing Geographic Information System (GIS) software and solutions, announced that the company is developing a policy map to offer data to help states and policymakers in decision-making. The Policy Maps have been designed to provide meaningful insights into various government functions., July 2022: Google announced a new partnership in India with local authorities and organizations in order to provide customized features for the diverse needs of the people in the country. Also, Google is building helpful maps that provide more visual and accurate navigation.. Key drivers for this market are: Increasing Demand of Location Based Service, Growing Availability of Spatial Data. Potential restraints include: Increasing Demand of Location Based Service, Growing Availability of Spatial Data. Notable trends are: Increasing Demand of Location Based Service.

This file lists public websites and all calls made to external domains, when they concern Google analytics trackers, google maps, twitter pixels, facebook and other CDNs

Source: https://github.com/revolunet/trackscan

LinkedIn Job Postings Data - Comprehensive Professional Intelligence for HR Strategy & Market Research

LinkedIn Job Postings Data represents the most comprehensive professional intelligence dataset available, delivering structured insights across millions of LinkedIn job postings, LinkedIn job listings, and LinkedIn career opportunities. Canaria's enriched LinkedIn Job Postings Data transforms raw LinkedIn job market information into actionable business intelligence—normalized, deduplicated, and enhanced with AI-powered enrichment for deep workforce analytics, talent acquisition, and market research.

This premium LinkedIn job postings dataset is engineered to help HR professionals, recruiters, analysts, and business strategists answer mission-critical questions: • What LinkedIn job opportunities are available in target companies? • Which skills are trending in LinkedIn job postings across specific industries? • How are companies advertising their LinkedIn career opportunities? • What are the salary expectations across different LinkedIn job listings and regions?

With real-time updates and comprehensive LinkedIn job posting enrichment, our data provides unparalleled visibility into LinkedIn job market trends, hiring patterns, and workforce dynamics.

Use Cases: What This LinkedIn Job Postings Data Solves

Our dataset transforms LinkedIn job advertisements, market information, and career listings into structured, analyzable insights—powering everything from talent acquisition to competitive intelligence and job market research.

Talent Acquisition & LinkedIn Recruiting Intelligence • LinkedIn job market mapping • LinkedIn career opportunity intelligence • LinkedIn job posting competitive analysis • LinkedIn job skills gap identification

HR Strategy & Workforce Analytics • Organizational network analysis • Employee mobility tracking • Compensation benchmarking • Diversity & inclusion analytics • Workforce planning intelligence • Skills evolution monitoring

Market Research & Competitive Intelligence • Company growth analysis • Industry trend identification • Competitive talent mapping • Market entry intelligence • Partnership & business development • Investment due diligence

LinkedIn Job Market Research & Economic Analysis • Regional LinkedIn job analysis • LinkedIn job skills demand forecasting • LinkedIn job economic impact assessment • LinkedIn job education-industry alignment • LinkedIn remote job trend analysis • LinkedIn career development ROI

What Makes This LinkedIn Job Postings Data Unique

AI-Enhanced LinkedIn Job Intelligence • LinkedIn job posting enrichment with advanced NLP • LinkedIn job seniority classification • LinkedIn job industry expertise mapping • LinkedIn job career progression modeling

Comprehensive LinkedIn Job Market Intelligence • Real-time LinkedIn job postings with salary, requirements, and company insights • LinkedIn recruiting activity tracking • LinkedIn job application analytics • LinkedIn job skills demand analysis • LinkedIn compensation intelligence

Company & Organizational Intelligence • Company growth indicators • Cultural & values intelligence • Competitive positioning

LinkedIn Job Data Quality & Normalization • Advanced LinkedIn job deduplication • LinkedIn job skills taxonomy standardization • LinkedIn job geographic normalization • LinkedIn job company matching • LinkedIn job education standardization

Who Uses Canaria's LinkedIn Data

HR & Talent Acquisition Teams • Optimize recruiting pipelines • Benchmark compensation • Identify talent pools • Develop data-driven hiring strategies

Market Research & Intelligence Analysts • Track industry trends • Build competitive intelligence models • Analyze workforce dynamics

HR Technology & Analytics Platforms • Power recruiting tools and analytics solutions • Fuel compensation engines and dashboards

Academic & Economic Researchers • Study labor market dynamics • Analyze career mobility trends • Research professional development

Government & Policy Organizations • Evaluate workforce development programs • Monitor skills gaps • Inform economic initiatives

Summary

Canaria's LinkedIn Job Postings Data delivers the most comprehensive LinkedIn job market intelligence available. It combines job posting insights, recruiting intelligence, and organizational data in one unified dataset. With AI-enhanced enrichment, real-time updates, and enterprise-grade data quality, it supports advanced HR analytics, talent acquisition, job market research, and competitive intelligence.

About Canaria Inc. Canaria Inc. is a leader in alternative data, specializing in job market intelligence, LinkedIn company data, Glassdoor salary analytics, and Google Maps location insights. We deliver clean, structured, and enriched datasets at scale using proprietary data scraping pipelines and advanced AI/LLM-based modeling, all backed by human validation. Our platform also includes Google Maps data, providing verified business location intelligen...