Personal Location Data Market

Data From: "There’s a Multibillion-Dollar Market for Your Phone’s Location Data"

Original source. Author: The Markup

About this dataset

There’s a multibillion-dollar market for your phone’s location data. We surveyed 100 companies to find out who they are, what they do with your data, and whether they follow best practices.

Your phone’s location is constantly being tracked and collected by hundreds of companies, many of which are unknown to you. This data is valuable—and it’s being bought and sold in a thriving industry with little regulation.

The Markup surveyed 100 companies that collect or sell location data to get a better understanding of this industry and what it means for your privacy. We asked these companies about their policies and practices around collecting, using, and selling location data. We also reviewed their public statements and website disclosures related to privacy.

What we found was an industry that lacks transparency and accountability, with few companies following best practices around protecting the privacy of their users’ data. In many cases, these companies are collecting more data than they need, retaining it for longer than necessary, sharing it with third parties without user consent, or failing to secure it properly—putting users at risk of identity theft, fraud, or other harms.

If you care about your privacy, you should know who has access to your location data—and what they’re doing with it. This dataset contains information on the 100 companies we surveyed so that you can make informed choices about which ones to trust with your personal data

How to use the dataset

This dataset contains information on companies that collect and sell location data. The data includes the company name, website, logo, narrative, company response, privacy email, privacy policy, and whether or not the company is a California-licensed data broker

Research Ideas

• To study how location data is collected and sold
• To understand the business model of location data companies
• To learn about the privacy policies of these companies

Acknowledgements

This dataset was compiled and analyzed by The Markup. The Markup is a nonprofit newsroom that investigates how powerful institutions impact our lives

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: location-data-companies.csv | Column name | Description | |:-------------------|:--------------------------------------------------------------------| | name | The name of the company. (String) | | website | The company's website. (String) | | logo | The company's logo. (String) | | narrative | A description of the company. (String) | | privacy_email | The company's privacy email address. (String) | | privacy_policy | The company's privacy policy. (String) | | CA_broker | Whether the company is a California-licensed data broker. (Boolean) |

This collection of data includes over seventeen million global companies. The dataset has information such as a company's name, website domain, size, year founded, industry, city/state, country and the handle of their LinkedIn URL.

Schema, data stats, and further documentation can be found at: https://docs.bigpicture.io/docs/free-datasets/companies/

Update: Following SavvyIQ's acquisition of BigPicture technology, our team is now building next-generation business intelligence APIs powered by AI agents.

While this free dataset remains available, our paid offerings now include: - 265M+ government-verified entities (vs 17M in free dataset) - Deep industry classification (NAICS codes, business models, and products & services) - Legal entity information and corporate hierarchies - Works for global businesses - with or without web presence

Learn more at: https://savvyiq.ai/docs

This dataset is about companies in New Boston. It has 18 rows. It features 3 columns: employees, and website.

Context

E-commerce has become a new channel to support businesses development. Through e-commerce, businesses can get access and establish a wider market presence by providing cheaper and more efficient distribution channels for their products or services. E-commerce has also changed the way people shop and consume products and services. Many people are turning to their computers or smart devices to order goods, which can easily be delivered to their homes.

Content

This is a sales transaction data set of UK-based e-commerce (online retail) for one year. This London-based shop has been selling gifts and homewares for adults and children through the website since 2007. Their customers come from all over the world and usually make direct purchases for themselves. There are also small businesses that buy in bulk and sell to other customers through retail outlet channels.

The data set contains 500K rows and 8 columns. The following is the description of each column. 1. TransactionNo (categorical): a six-digit unique number that defines each transaction. The letter “C” in the code indicates a cancellation. 2. Date (numeric): the date when each transaction was generated. 3. ProductNo (categorical): a five or six-digit unique character used to identify a specific product. 4. Product (categorical): product/item name. 5. Price (numeric): the price of each product per unit in pound sterling (£). 6. Quantity (numeric): the quantity of each product per transaction. Negative values related to cancelled transactions. 7. CustomerNo (categorical): a five-digit unique number that defines each customer. 8. Country (categorical): name of the country where the customer resides.

There is a small percentage of order cancellation in the data set. Most of these cancellations were due to out-of-stock conditions on some products. Under this situation, customers tend to cancel an order as they want all products delivered all at once.

Inspiration

Information is a main asset of businesses nowadays. The success of a business in a competitive environment depends on its ability to acquire, store, and utilize information. Data is one of the main sources of information. Therefore, data analysis is an important activity for acquiring new and useful information. Analyze this dataset and try to answer the following questions. 1. How was the sales trend over the months? 2. What are the most frequently purchased products? 3. How many products does the customer purchase in each transaction? 4. What are the most profitable segment customers? 5. Based on your findings, what strategy could you recommend to the business to gain more profit?

Photo by CardMapr on Unsplash

To search for a business - click here

To view a glossary of terms for the directory - click here

What is this directory for?

Mayor Michelle Wu is committed to creating equal opportunities for businesses of all kinds in Boston. Through the business certification process, the City identifies businesses that are owned by women, minorities, veterans as well as those that are small or local. Once a business is certified with our office, they are included in any vendor outreach efforts for City contracting opportunities and are also connected to resources offered inside and outside of the City.

In order to provide access to more minority-owned and woman-owned businesses, small and small local businesses, and veteran and service disabled veteran-owned small businesses, the City of Boston Directory of certified businesses is now available on Analyze Boston.

If you think you might be eligible for certification, visit our website and apply today

If you have questions about obtaining certification, please contact stacey.williams@boston.gov

What does each certification category mean?

Minority Business Enterprise (MBE) - means a business organization which is beneficially owned or substantially invested in by one or more minority group members as follows:

• The business must be at least 51% beneficially owned by minority group members.
• The minority owners must demonstrate that they have control over management.

• The firm has not been solely established for the purpose of taking advantage of a special program which has been developed to assist minority-owned businesses.

  Woman Business Enterprise (WBE) - means a business organization which is beneficially owned or substantially invested in by one or more women meeting the following criteria:

• The business must be at least 51% beneficially owned by a woman.

• The woman owner must demonstrate that she has control over management.

• The firm has not been solely established for the purpose of taking advantage of a special program which has been developed to assist woman-owned businesses.

Small Business Enterprise (SBE) - means a business with gross receipts, that when averaged over a three-year period do not exceed gross income limitations for that particular industry as defined by the Small Local Business Enterprise Office.

Small Local Business Enterprise (SLBE) - means a business which is a Small Business Enterprise, as defined above, and whose principal office is physically located in the City of Boston, as defined by the SLBE certification regulations.

A Veteran Owned Small Business (VOSB) and a Service Disabled Veteran Owned Small Business (SDVOSB) is a business that has already been verified as such by the U.S. Department of Veteran Affairs.

Can a business hold multiple certifications at the same time?

Yes, businesses may qualify for more than one certification.

How long are these certifications valid for?

Businesses are required to renew their certification _ every three years_.

This dataset has info on over 10,000 different companies from Ambition Box, a website that lets people share their experiences working at different companies.

The dataset includes:

Company name: The name of the company. Ratings: The overall star rating given by users. Total reviews: How many reviews the company has gotten. Average salary: The typical pay for workers at the company. Interviews taken: How many job interviews the company has done. Total jobs available: How many job openings the company has. Total benefits: Info on things like health insurance, vacation time, etc. that the company offers. Number of employees: How many people work at the company. Years in business: How long the company has been around. Industry type: What kind of business the company is in.

This dataset is about companies in Mosta. It has 1 row. It features 3 columns: employees, and website.

The Unicorn Companies Dataset is a comprehensive collection of information on privately held startup companies that have reached a valuation of $1 billion or more. The dataset contains 17 columns, including:

Sno: Serial number assigned to each entry in the dataset. Company: The name of the company. Valuation ($B): The valuation of the company in billions of dollars. Date Joined: The date on which the company achieved unicorn status. Country: The country where the company is headquartered. City: The city where the company is headquartered. Industry: The industry in which the company operates. Investors: The list of investors who have invested in the company. Founded Year: The year in which the company was founded. Total Raised: The total amount of funding that the company has raised. Financial Stage: The financial stage of the company (e.g., Series A, Series B, etc.). Investors Count: The total number of investors who have invested in the company. Deal Terms: The terms of the company's funding deals. Portfolio Exits: Information on any exits the company has made from its portfolio. Unicorn Nest website link: The website link to the company's profile on the Unicorn Nest website. Fund Structure: The fund structure of the company (e.g., VC, PE, etc.). Social Media Presence: Whether the Companies are active on Social Media. The dataset is intended for use by data scientists, researchers, and business analysts who are interested in exploring the world of unicorn companies and analyzing trends in the startup ecosystem. The dataset can be used for various purposes, including predictive modeling, trend analysis, and portfolio optimization.

The dataset has been meticulously gathered from the website https://companiesmarketcap.com/largest-companies-by-revenue/, which provides comprehensive information on the largest companies globally, ranked by their revenue. This particular dataset is a product of web scraping, a technique used to extract large amounts of data from websites in a structured format. Web scraping involves automated methods to retrieve and process data from web pages, allowing for the collection of information that may not be readily available in a downloadable format. In this case, the scraping process targeted specific elements of the webpage to obtain relevant details such as company names, revenue figures, industry classifications, and other pertinent metrics that reflect the financial performance and stature of these corporations.

About Dataset

Context

This dataset contains financial information of 1500 companies across 8 different industries scraped from companiesmarketcap.com on May 2024. It contains information about the company's name, industry, country, employees, marketcap, revenue, earnings, etc.

• The scraped program of this dataset can be found in Industry Market Cap Analysis Github repository.
• Tableau visualization of this dataset can also be found in Industry Market Cap: Visualization

Content

The dataset contains 2 files with the same column names. scraped_company_data.csv file is further transformed and cleaned to produce the finaltransformed_company_data.csvfile.

1. Company: Full name of the company
2. Company Path: Website URL of the company
3. Industry: Associated industry of the company
4. Country: Location of the company
5. Employees: Total number of employees of the company
6. Market Cap: Market capital of the company (as of Mar 2024)
7. Revenue: Company's current revenue (31 Mar 2023 - 31 Mar 2024)
8. Earnings: Company's current earnings (31 Mar 2023 - 31 Mar 2024)
9. Operating Margin: Company's current operating margin (at the end of 2023)
10. Total Assets: Company's total assets (as of Mar 2024)
11. Total Liabilities: Company's total liabilities
12. Total Debt: Company's total debt
13. Net Assets: Company’s net assets
14. PE Ratio: Company's current price-to-earnings ratio (31 Mar 2023 - 31 Mar 2024)
15. PS Ratio: Company's current price-to-sales ratio (31 Mar 2023 - 31 Mar 2024)

Acknowledgements

The website companiesmarketcap.com was used to scrape this dataset. Please include citations for this dataset if you use it in your own research.

Inspiration

The dataset can be used to find industries with the highest average market value, most profitable industries, most growth-oriented sectors, etc. More interesting insights can be found in this README file.

This collection of data includes over seventeen million global companies. The dataset has information such as a company's name, website domain, size, year founded, industry, city/state, country and the handle of their LinkedIn URL. Schema, data stats, general documentation, and other datasets can be found at: https://docs.bigpicture.io/docs/free-datasets/companies/

  Update:

Following SavvyIQ's acquisition of BigPicture technology, our team is now building next-generation business… See the full description on the dataset page: https://huggingface.co/datasets/bigpictureio/companies-2023-q4-sm.

Success.ai’s Company Data Solutions provide businesses with powerful, enterprise-ready B2B company datasets, enabling you to unlock insights on over 28 million verified company profiles. Our solution is ideal for organizations seeking accurate and detailed B2B contact data, whether you’re targeting large enterprises, mid-sized businesses, or small business contact data.

Success.ai offers B2B marketing data across industries and geographies, tailored to fit your specific business needs. With our white-glove service, you’ll receive curated, ready-to-use company datasets without the hassle of managing data platforms yourself. Whether you’re looking for UK B2B data or global datasets, Success.ai ensures a seamless experience with the most accurate and up-to-date information in the market.

Why Choose Success.ai’s Company Data Solution? At Success.ai, we prioritize quality and relevancy. Every company profile is AI-validated for a 99% accuracy rate and manually reviewed to ensure you're accessing actionable and GDPR-compliant data. Our price match guarantee ensures you receive the best deal on the market, while our white-glove service provides personalized assistance in sourcing and delivering the data you need.

Why Choose Success.ai?

• Best Price Guarantee: We offer industry-leading pricing and beat any competitor.
• Global Reach: Access over 28 million verified company profiles across 195 countries.
• Comprehensive Data: Over 15 data points, including company size, industry, funding, and technologies used.
• Accurate & Verified: AI-validated with a 99% accuracy rate, ensuring high-quality data.
• Real-Time Updates: Stay ahead with continuously updated company information.
• Ethically Sourced Data: Our B2B data is compliant with global privacy laws, ensuring responsible use.
• Dedicated Service: Receive personalized, curated data without the hassle of managing platforms.
• Tailored Solutions: Custom datasets are built to fit your unique business needs and industries.

Our database spans 195 countries and covers 28 million public and private company profiles, with detailed insights into each company’s structure, size, funding history, and key technologies. We provide B2B company data for businesses of all sizes, from small business contact data to large corporations, with extensive coverage in regions such as North America, Europe, Asia-Pacific, and Latin America.

Comprehensive Data Points: Success.ai delivers in-depth information on each company, with over 15 data points, including:

Company Name: Get the full legal name of the company. LinkedIn URL: Direct link to the company's LinkedIn profile. Company Domain: Website URL for more detailed research. Company Description: Overview of the company’s services and products. Company Location: Geographic location down to the city, state, and country. Company Industry: The sector or industry the company operates in. Employee Count: Number of employees to help identify company size. Technologies Used: Insights into key technologies employed by the company, valuable for tech-based outreach. Funding Information: Track total funding and the most recent funding dates for investment opportunities. Maximize Your Sales Potential: With Success.ai’s B2B contact data and company datasets, sales teams can build tailored lists of target accounts, identify decision-makers, and access real-time company intelligence. Our curated datasets ensure you’re always focused on high-value leads—those who are most likely to convert into clients. Whether you’re conducting account-based marketing (ABM), expanding your sales pipeline, or looking to improve your lead generation strategies, Success.ai offers the resources you need to scale your business efficiently.

Tailored for Your Industry: Success.ai serves multiple industries, including technology, healthcare, finance, manufacturing, and more. Our B2B marketing data solutions are particularly valuable for businesses looking to reach professionals in key sectors. You’ll also have access to small business contact data, perfect for reaching new markets or uncovering high-growth startups.

From UK B2B data to contacts across Europe and Asia, our datasets provide global coverage to expand your business reach and identify new markets. With continuous data updates, Success.ai ensures you’re always working with the freshest information.

Key Use Cases:

• Targeted Lead Generation: Build accurate lead lists by filtering data by company size, industry, or location. Target decision-makers in key industries to streamline your B2B sales outreach.
• Account-Based Marketing (ABM): Use B2B company data to personalize marketing campaigns, focusing on high-value accounts and improving conversion rates.
• Investment Research: Track company growth, funding rounds, and employee trends to identify investment opportunities or potential M&A targets.
• Market Research: Enrich your market intelligence initiatives by gain...

Context

Typically e-commerce datasets are proprietary and consequently hard to find among publicly available data. However, The UCI Machine Learning Repository has made this dataset containing actual transactions from 2010 and 2011. The dataset is maintained on their site, where it can be found by the title "Online Retail".

Content

"This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.The company mainly sells unique all-occasion gifts. Many customers of the company are wholesalers."

Acknowledgements

Per the UCI Machine Learning Repository, this data was made available by Dr Daqing Chen, Director: Public Analytics group. chend '@' lsbu.ac.uk, School of Engineering, London South Bank University, London SE1 0AA, UK.

Image from stocksnap.io.

Inspiration

Analyses for this dataset could include time series, clustering, classification and more.

The Small Business Administration maintains the Dynamic Small Business Search (DSBS) database. As a small business registers in the System for Award Management, there is an opportunity to fill out the small business profile. The information provided populates DSBS. DSBS is another tool contracting officers use to identify potential small business contractors for upcoming contracting opportunities. Small businesses can also use DSBS to identify other small businesses for teaming and joint venturing.

This dataset is about companies in Pico Rivera. It has 32 rows. It features 3 columns: revenues, and website.

This dataset is about companies in Milwaukee. It has 1,827 rows. It features 2 columns including website.

The Industrial Development Bureau of the Ministry of Economic Affairs has opened the dataset of "List of Companies that Have Passed the Evaluation for Creative Life Business" from now on. It welcomes everyone to make good use of it. In order to encourage businesses to unleash creativity from their daily lives, integrate innovative thinking and cultural connotations into their business models, and shape their unique business styles, the Industrial Development Bureau of the Ministry of Economic Affairs has been promoting the creative life industry since 2003. So far, it has evaluated 170 creative life businesses to drive the diffusion of industry innovation and promote industry exchanges, learning, and cooperation.Creative life is based on the demand for a good quality of life that pursues delicacy, creativity, comfort, and taste. With experience as the core, it integrates entertainment, education, aesthetics, interaction, and other aspects, combines core knowledge, high-quality aesthetics, and deep experiences to shape its characteristics, strengthens the cultural depth of enterprise operations, and promotes enterprise transformation, upgrades, and innovation. It provides consumers with experiential connotations of lifestyle, conveys deep emotional memories, cultivates high-quality taste, and thereby creates positive and qualitative influences on industrial economic activities.In line with the government's measures to promote open data, the Industrial Development Bureau of the Ministry of Economic Affairs has opened the website for querying the list of companies that have passed the evaluation for creative life business (http://www.creativelife.org.tw/index.php) from now on, and welcomes everyone to make good use of it.

Check out the PHL Taking Care of Business Clean Corridors website for more information about this program. View metadata for key information about this dataset. PHL TCB has four main goals: 1. Maintain clean commercial districts in Philadelphia neighborhoods.2. Promote the economic success of neighborhood businesses by creating an inviting environment for shoppers.3. Create work opportunities for Philadelphians.4. Grow the capacity of local small businesses and organizations that provide cleaning services. For questions about this dataset, contact samuel.hall@phila.gov. For technical assistance, email maps@phila.gov.

This dataset contains information of about 9800 companies. And all this information is sourced from a website called as AmbitionBox, this website houses information of about 600k companies. Web Scraping was used to get this data (Web scraping is a technique used to extract information from web pages in an automated way through software programs that simulate the navigation of a human on the web either by using the HTTP protocol manually or by embedding a browser in an application.).

The main motive behind this dataset was to firstly learn web scraping and then put that knowledge gained into some useful task. So, hence I decided to make this dataset. This dataset can be used with various Machine Learning models like 'Regression', 'Classification' etc., one can really get creative.

This dataset is about companies in Walnut Creek. It has 457 rows. It features 3 columns: employees, and website.