The All CMS Data Feeds dataset is an expansive resource offering access to 118 unique report feeds, providing in-depth insights into various aspects of the U.S. healthcare system. With over 25.8 billion rows of data meticulously collected since 2007, this dataset is invaluable for healthcare professionals, analysts, researchers, and businesses seeking to understand and analyze healthcare trends, performance metrics, and demographic shifts over time. The dataset is updated monthly, ensuring that users always have access to the most current and relevant data available.

Dataset Overview:

118 Report Feeds: - The dataset includes a wide array of report feeds, each providing unique insights into different dimensions of healthcare. These topics range from Medicare and Medicaid service metrics, patient demographics, provider information, financial data, and much more. The breadth of information ensures that users can find relevant data for nearly any healthcare-related analysis. - As CMS releases new report feeds, they are automatically added to this dataset, keeping it current and expanding its utility for users.

25.8 Billion Rows of Data:

• With over 25.8 billion rows of data, this dataset provides a comprehensive view of the U.S. healthcare system. This extensive volume of data allows for granular analysis, enabling users to uncover insights that might be missed in smaller datasets. The data is also meticulously cleaned and aligned, ensuring accuracy and ease of use.

Historical Data Since 2007: - The dataset spans from 2007 to the present, offering a rich historical perspective that is essential for tracking long-term trends and changes in healthcare delivery, policy impacts, and patient outcomes. This historical data is particularly valuable for conducting longitudinal studies and evaluating the effects of various healthcare interventions over time.

Monthly Updates:

• To ensure that users have access to the most current information, the dataset is updated monthly. These updates include new reports as well as revisions to existing data, making the dataset a continuously evolving resource that stays relevant and accurate.

Data Sourced from CMS:

• The data in this dataset is sourced directly from the Centers for Medicare & Medicaid Services (CMS). After collection, the data is meticulously cleaned and its attributes are aligned, ensuring consistency, accuracy, and ease of use for any application. Furthermore, any new updates or releases from CMS are automatically integrated into the dataset, keeping it comprehensive and current.

Use Cases:

Market Analysis:

• The dataset is ideal for market analysts who need to understand the dynamics of the healthcare industry. The extensive historical data allows for detailed segmentation and analysis, helping users identify trends, market shifts, and growth opportunities. The comprehensive nature of the data enables users to perform in-depth analyses of specific market segments, making it a valuable tool for strategic decision-making.

Healthcare Research:

• Researchers will find the All CMS Data Feeds dataset to be a robust foundation for academic and commercial research. The historical data, combined with the breadth of coverage across various healthcare metrics, supports rigorous, in-depth analysis. Researchers can explore the effects of healthcare policies, study patient outcomes, analyze provider performance, and more, all within a single, comprehensive dataset.

Performance Tracking:

• Healthcare providers and organizations can use the dataset to track performance metrics over time. By comparing data across different periods, organizations can identify areas for improvement, monitor the effectiveness of initiatives, and ensure compliance with regulatory standards. The dataset provides the detailed, reliable data needed to track and analyze key performance indicators.

Compliance and Regulatory Reporting:

• The dataset is also an essential tool for compliance officers and those involved in regulatory reporting. With detailed data on provider performance, patient outcomes, and healthcare utilization, the dataset helps organizations meet regulatory requirements, prepare for audits, and ensure adherence to best practices. The accuracy and comprehensiveness of the data make it a trusted resource for regulatory compliance.

Data Quality and Reliability:

The All CMS Data Feeds dataset is designed with a strong emphasis on data quality and reliability. Each row of data is meticulously cleaned and aligned, ensuring that it is both accurate and consistent. This attention to detail makes the dataset a trusted resource for high-stakes applications, where data quality is critical.

Integration and Usability:

Ease of Integration:

• The dataset is provided in a CSV format, which is widely compatible with most data analysis tools and platforms. This ensures that users can easily integrate the data into their existing wo...

The library maintains several RSS feeds: Author Events, Free Library Blog, Free Library Podcast, Book Reviews, and Digital Collections. You can also build a custom RSS feed: http://libwww.freelibrary.org/rss/rssmenu.cfm

Discover the Walmart Products Free Dataset, featuring 2,000 records in CSV format. This dataset includes detailed information about various Walmart products, such as names, prices, categories, and descriptions.

It’s perfect for data analysis, e-commerce research, and machine learning projects. Download now and kickstart your insights with accurate, real-world data.

Cryptocurrencies

Finage offers you more than 1700+ cryptocurrency data in real time.

With Finage, you can react to the cryptocurrency data in Real-Time via WebSocket or unlimited API calls. Also, we offer you a 7-year historical data API.

You can view the full Cryptocurrency market coverage with the link given below. https://finage.s3.eu-west-2.amazonaws.com/Finage_Crypto_Coverage.pdf

Comprehensive dataset containing 2 verified Feed manufacturer businesses in Free municipal consortium of Syracuse, Italy with complete contact information, ratings, reviews, and location data.

🇺🇸 미국

Forex Symbols

Finage offers you more than 1300+ forex data as real-time.

With Finage, you can react to the forex data in Real-Time via WebSocket or unlimited API calls. Also, we offer you a 15-year historical data API.

Commodities Bonds Metals Forex You can view the full FX market coverage with the link given below. https://finage.s3.eu-west-2.amazonaws.com/Finage_FX_Symbol_List.pdf

We offer web activity data of users that are browsing popular websites around the world. This data can be used to analyze web behavior across the web and build highly accurate audience segments based on web activity for targeting ads based on interest categories and search/browsing intent.

Web Data Reach: Our reach data represents the total number of data counts available within various categories and comprises attributes such as Country, Anonymous ID, IP addresses, Search Query, and so on.

Data Export Methodology: Since we collect data dynamically, we provide the most updated data and insights via a best-suited method at a suitable interval (daily/weekly/monthly).

Data Attributes: Anonymous_id IDType Timestamp Estid Ip userAgent browserFamily deviceType Os Url_metadata_canonical_url Url_metadata_raw_query_params refDomain mappedEvent Channel searchQuery Ttd_id Adnxs_id Keywords Categories Entities Concepts

Use Cases: Personalized Targeting Targeting audiences with data enables deeper personalization and higher engagement rates Data Enrichment Leverage Online to Offline consumer profiles to build holistic audience segments to improve campaign targeting using user data enrichment. Market Intelligence Study various market areas, the proximity of points or interests and the competitive landscape. Fraud & Cybersecurity Use the power of multiple alternative data sources to identify fraudulent behavior across digital channels

The best choice for those looking for license-free US market data for commercial use is US Equities Basic, which includes data display, redistribution, professional trading, and more.

US Equities Basic is based upon a derived IEX feed. The volume coverage is 3-5% of the total trading volume in North America, which helps entities mitigate license expenses and start with real-time data.

US Equities Basic provides raw quotes, trades, aggregated time series (OHLCV), and snapshots. Both REST API and WebSocket API are available.

End-of-day price information disseminated after 12:00 AM EST does not require licensing in the United States by law. This applies to all exchanges, even those not included in the US Equities Basic. Finazon combines all price information after every trading day, meaning that while markets are open, real-time prices are available from a subset of exchanges, and when markets close, data is synced and contains 100% of US volume. All historical prices are adjusted for corporate actions and splits.

Tip: Individuals with non-professional usage are not required to get exchange licenses for real-time data and, hence, are better off with the US Equities Max dataset.

Whether you're building an eCommerce dashboard, researching market trends, or prototyping beauty intelligence tools — this dataset is a perfect place to start.

Interested in Live Tracking or API?

This dataset represents just a snapshot of what we track in real time at https://beautyfeeds.io/" target="_new" rel="noopener" data-start="2004" data-end="2041">BeautyFeeds:

• Monitor price & stock changes daily or weekly

• Track products from major retailers like Sephora, Ulta, Nykaa, Amazon, and more

• Access via export or live API

• Filter by brand, country, or category

• Assign custom URLs for targeted scraping

👉 Learn more and get 500 free credits at https://beautyfeeds.io/" target="_new" rel="noopener" data-start="2342" data-end="2382">BeautyFeeds.io

United States - Producer Price Index by Commodity: Processed Foods and Feeds: Fat Free or Skim Milk was 337.01000 Index Dec 1982=100 in July of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Commodity: Processed Foods and Feeds: Fat Free or Skim Milk reached a record high of 346.81300 in November of 2024 and a record low of 99.70000 in November of 1983. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Commodity: Processed Foods and Feeds: Fat Free or Skim Milk - last updated from the United States Federal Reserve on September of 2025.

Snapshot img

Government Open Data Management Platform Market Size 2025-2029

The government open data management platform market size is valued to increase USD 189.4 million, at a CAGR of 12.5% from 2024 to 2029. Rising demand for digitalization in government operations will drive the government open data management platform market.

Major Market Trends & Insights

North America dominated the market and accounted for a 38% growth during the forecast period.
By End-user - Large enterprises segment was valued at USD 108.50 million in 2023
By Deployment - On-premises segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 138.56 million
Market Future Opportunities: USD 189.40 million 
CAGR : 12.5%
North America: Largest market in 2023

Market Summary

The market is a dynamic and continually evolving landscape, driven by the rising demand for digitalization in government operations. Core technologies and applications, such as cloud computing, big data analytics, and artificial intelligence (AI) and machine learning (ML), are transforming the way governments manage and share open data. According to recent studies, the adoption rate of AI and ML in open data management platforms is projected to reach 30% by 2025. However, this market also faces challenges, including data privacy concerns related to open data platforms. Regulations, such as the European Union's General Data Protection Regulation (GDPR) and the U.S. Freedom of Information Act (FOIA), play a crucial role in shaping the market's evolution. Looking ahead, the forecast period for the market extends to 2027. This period is expected to bring significant opportunities for market growth, as governments worldwide continue to invest in digital transformation initiatives. Related markets such as the Cloud Computing Market and the Big Data Analytics Market are also experiencing robust growth, further fueling the demand for advanced open data management solutions.

What will be the Size of the Government Open Data Management Platform Market during the forecast period?

Get Key Insights on Market Forecast (PDF) Request Free Sample

How is the Government Open Data Management Platform Market Segmented and what are the key trends of market segmentation?

The government open data management platform industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. End-userLarge enterprisesSMEsDeploymentOn-premisesCloud-basedComponentSolutionsServicesGeographyNorth AmericaUSCanadaMexicoEuropeFranceGermanyItalyUKAPACAustraliaChinaIndiaRest of World (ROW)

By End-user Insights

The large enterprises segment is estimated to witness significant growth during the forecast period.

In today's data-driven business landscape, large enterprises are increasingly utilizing government open data management platforms to access, manage, and derive valuable insights from the extensive datasets published by government agencies. These platforms enable organizations to stay informed about market trends, consumer behavior, and emerging opportunities by assessing demographic, socioeconomic, and infrastructure data, among others. Moreover, government open data can lead to significant cost savings. For instance, large enterprises can identify new suppliers through open data, optimize their supply chains, and improve energy efficiency. The adoption of government open data management platforms is on the rise, with an estimated 35% of large enterprises currently using these platforms. Furthermore, industry experts anticipate that over the next five years, up to 45% of businesses will integrate government open data into their operations. Effective management of government open data involves several key components. Data accessibility standards ensure that data is easily accessible and usable. Ontology development and data cataloging systems facilitate efficient data organization and discovery. Cloud data storage offers scalability and flexibility. Knowledge graph implementation and data transformation services enable data integration and analysis. Data privacy compliance, data lineage tracking, and real-time data feeds ensure data security and accuracy. User interface design and linked data principles enhance user experience and data interoperability. API documentation standards, metadata management tools, and data enrichment pipelines streamline data processing and integration. Data usage metrics, API integration strategies, and data breach prevention measures help organizations maximize the value of their data while minimizing risks. Data governance frameworks, data visualization dashboards, and data warehousing solutions provide a centralized platform for data management

Our clickstream data offers unparalleled access to a vast array of global datasets, capturing user interactions across websites, apps, and digital platforms worldwide. With coverage spanning multiple industries and geographies, our data provides detailed insights into consumer behavior, online trends, and digital engagement patterns.

Whether you're analyzing traffic flows, identifying audience interests, or tracking competitive performance, our clickstream datasets deliver the scale and granularity needed to inform strategic decisions. Updated regularly to ensure accuracy and relevance, this robust resource empowers businesses to uncover actionable insights and stay ahead in a dynamic digital landscape.

Fashion products dataset list from athleta gap. last extracted on 26 Dec 2021.

Crawl Feeds ready to download fashion datasets

API operated by Louisville Metro that returns AQI information from local sensors operated by APCD. Shows the latest hourly data in a JSON feed.The Air Quality Index (AQI) is an easy way to tell you about air quality without having to know a lot of technical details. The “Metropolitan Air Quality Index” shows the AQI from the monitor in Kentuckiana that is currently detecting the highest level of air pollution. See: https://louisvilleky.gov/government/air-pollution-control-district/servi...See the air quality map (Louisville Air Watch) for more details: airqualitymap.louisvilleky.gov/#Read the FAQ for more information about the AQI data: https://louisvilleky.gov/government/air-pollution-control-district/louis...If you'd prefer air quality forecast data (raw data, maps, API) instead, please see AIRNow: https://www.airnow.gov/index.cfm?action=airnow.local_city&zipcode=40204&...See the Data Dictionary section below for information about what the AQI numbers mean, their corresponding colors, recommendations, and more info and links.To download daily snapshots of AQI for the last 25 years, visit the EPA website, set your year range, and choose, Louisville KY. Then download with the CSV link at the bottom of the page.IFTTT integration trigger that fires and after retrieving air quality from Louisville Metro air sensors via the APIGives a forecast instead of the current conditions, so you can take action before the air quality gets bad.The U.S. EPA AirNow program (www.AirNow.gov) protects public health by providing forecast and real-time observed air quality information across the United States, Canada, and Mexico. AirNow receives real-time air quality observations from over 2,000 monitoring stations and collects forecasts for more than 300 cities.Sign up for a free account and get started using the RSS data feed for Louisville. https://docs.airnowapi.org/feedsAir Quality Forecast via AirNowAQI Level - Value and Related Health Concerns LegendGood 0-50 GreenAir quality is considered satisfactory, and air pollution poses little or no risk.Moderate 51-100 YellowAir quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people who are unusually sensitive to air pollution.Unhealthy for Sensitive Groups 101-150 OrangeMembers of sensitive groups may experience health effects. The general public is not likely to be affected.Unhealthy 151-200 RedEveryone may begin to experience health effects; members of sensitive groups may experience more serious health effects.Very Unhealthy 201-300 PurpleHealth alert: everyone may experience more serious health effects.Hazardous > 300 Dark PurpleHealth warnings of emergency conditions. The entire population is more likely to be affected.Here are citizen actions APCD recommends on air quality alert days, that is, days when the forecast is for the air quality to reach or exceed the “unhealthy for sensitive groups” (orange) level:Don’t idle your car. (Recommended all the time; see the second link below.)Put off mowing grass with a gas mower until the alert ends.“Refuel when it’s cool” (pump gasoline only in the evening or night).Avoid driving if possible. Share rides or take TARC.Check on neighbors with breathing problems.Here are some links in relation to the recommendations:KAIRE, www.helptheair.org/Idle Free Louisville, www.helptheair.org/idle-freeTARCTicket to Ride, tickettoride.org/Lawn Care for Cleaner Air (rebates)Contact:Bryan FrazerBryan.Frazar@louisvilleky.gov

PUDL v2025.2.0 Data Release

This is our regular quarterly release for 2025Q1. It includes updates to all the datasets that are published with quarterly or higher frequency, plus initial verisons of a few new data sources that have been in the works for a while.

One major change this quarter is that we are now publishing all processed PUDL data as Apache Parquet files, alongside our existing SQLite databases. See Data Access for more on how to access these outputs.

Some potentially breaking changes to be aware of:

In the EIA Form 930 – Hourly and Daily Balancing Authority Operations Report a number of new energy sources have been added, and some old energy sources have been split into more granular categories. See Changes in energy source granularity over time.

We are now running the EPA’s CAMD to EIA unit crosswalk code for each individual year starting from 2018, rather than just 2018 and 2021, resulting in more connections between these two datasets and changes to some sub-plant IDs. See the note below for more details.

Many thanks to the organizations who make these regular updates possible! Especially GridLab, RMI, and the ZERO Lab at Princeton University. If you rely on PUDL and would like to help ensure that the data keeps flowing, please consider joining them as a PUDL Sustainer, as we are still fundraising for 2025.

New Data

EIA 176

Add a couple of semi-transformed interim EIA-176 (natural gas sources and dispositions) tables. They aren’t yet being written to the database, but are one step closer. See #3555 and PRs #3590, #3978. Thanks to @davidmudrauskas for moving this dataset forward.

Extracted these interim tables up through the latest 2023 data release. See #4002 and #4004.

EIA 860

Added EIA 860 Multifuel table. See #3438 and #3946.

FERC 1

Added three new output tables containing granular utility accounting data. See #4057, #3642 and the table descriptions in the data dictionary:

out_ferc1_yearly_detailed_income_statements

out_ferc1_yearly_detailed_balance_sheet_assets

out_ferc1_yearly_detailed_balance_sheet_liabilities

SEC Form 10-K Parent-Subsidiary Ownership

We have added some new tables describing the parent-subsidiary company ownership relationships reported in the SEC’s Form 10-K, Exhibit 21 “Subsidiaries of the Registrant”. Where possible these tables link the SEC filers or their subsidiary companies to the corresponding EIA utilities. This work was funded by a grant from the Mozilla Foundation. Most of the ML models and data preparation took place in the mozilla-sec-eia repository separate from the main PUDL ETL, as it requires processing hundreds of thousands of PDFs and the deployment of some ML experiment tracking infrastructure. The new tables are handed off as nearly finished products to the PUDL ETL pipeline. Note that these are preliminary, experimental data products and are known to be incomplete and to contain errors. Extracting data tables from unstructured PDFs and the SEC to EIA record linkage are necessarily probabalistic processes.

See PRs #4026, #4031, #4035, #4046, #4048, #4050 and check out the table descriptions in the PUDL data dictionary:

out_sec10k_parents_and_subsidiaries

core_sec10k_quarterly_filings

core_sec10k_quarterly_exhibit_21_company_ownership

core_sec10k_quarterly_company_information

Expanded Data Coverage

EPA CEMS

Added 2024 Q4 of CEMS data. See #4041 and #4052.

EPA CAMD EIA Crosswalk

In the past, the crosswalk in PUDL has used the EPA’s published crosswalk (run with 2018 data), and an additional crosswalk we ran with 2021 EIA 860 data. To ensure that the crosswalk reflects updates in both EIA and EPA data, we re-ran the EPA R code which generates the EPA CAMD EIA crosswalk with 4 new years of data: 2019, 2020, 2022 and 2023. Re-running the crosswalk pulls the latest data from the CAMD FACT API, which results in some changes to the generator and unit IDs reported on the EPA side of the crosswalk, which feeds into the creation of core_epa_assn_eia_epacamd.

The changes only result in the addition of new units and generators in the EPA data, with no changes to matches at the plant level. However, the updates to generator and unit IDs have resulted in changes to the subplant IDs - some EIA boilers and generators which previously had no matches to EPA data have now been matched to EPA unit data, resulting in an overall reduction in the number of rows in the core_epa_assn_eia_epacamd_subplant_ids table. See issues #4039 and PR #4056 for a discussion of the changes observed in the course of this update.

EIA 860M

Added EIA 860m through December 2024. See #4038 and #4047.

EIA 923

Added EIA 923 monthly data through September 2024. See #4038 and #4047.

EIA Bulk Electricity Data

Updated the EIA Bulk Electricity data to include data published up through 2024-11-01. See #4042 and PR #4051.

EIA 930

Updated the EIA 930 data to include data published up through the beginning of February 2025. See #4040 and PR #4054. 10 new energy sources were added and 3 were retired; see Changes in energy source granularity over time for more information.

Bug Fixes

Fix an accidentally swapped set of starting balance / ending balance column rename parameters in the pre-2021 DBF derived data that feeds into core_ferc1_yearly_other_regulatory_liabilities_sched278. See issue #3952 and PRs #3969, #3979. Thanks to @yolandazzz13 for making this fix.

Added preliminary data validation checks for several FERC 1 tables that were missing it #3860.

Fix spelling of Lake Huron and Lake Saint Clair in out_vcerare_hourly_available_capacity_factor and related tables. See issue #4007 and PR #4029.

Quality of Life Improvements

We added a sources parameter to pudl.metadata.classes.DataSource.from_id() in order to make it possible to use the pudl-archiver repository to archive datasets that won’t necessarily be ingested into PUDL. See this PUDL archiver issue and PRs #4003 and #4013.

Other PUDL v2025.2.0 Resources

PUDL v2025.2.0 Data Dictionary

PUDL v2025.2.0 Documentation

PUDL in the AWS Open Data Registry

PUDL v2025.2.0 in a free, public AWS S3 bucket: s3://pudl.catalyst.coop/v2025.2.0/

PUDL v2025.2.0 in a requester-pays GCS bucket: gs://pudl.catalyst.coop/v2025.2.0/

Zenodo archive of the PUDL GitHub repo for this release

PUDL v2025.2.0 release on GitHub

PUDL v2025.2.0 package in the Python Package Index (PyPI)

Contact Us

If you're using PUDL, we would love to hear from you! Even if it's just a note to let us know that you exist, and how you're using the software or data. Here's a bunch of different ways to get in touch:

Follow us on GitHub

Use the PUDL Github issue tracker to let us know about any bugs or data issues you encounter

GitHub Discussions is where we provide user support.

Watch our GitHub Project to see what we're working on.

Email us at hello@catalyst.coop for private communications.

On Mastodon: @CatalystCoop@mastodon.energy

On BlueSky: @catalyst.coop

On Twitter: @CatalystCoop

Connect with us on LinkedIn

Play with our data and notebooks on Kaggle

Combine our data with ML models on HuggingFace

Learn more about us on our website: https://catalyst.coop

Subscribe to our announcements list for email updates.

Both the scheduled timetable and the real-time data are available to you for free. There are two GTFS feeds available: The scheduled data which are updated daily The real-time data which are updated every 30 seconds

Analysis of ‘London bike sharing dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/hmavrodiev/london-bike-sharing-dataset on 12 November 2021.

--- Dataset description provided by original source is as follows ---

License

These licence terms and conditions apply to TfL's free transport data service and are based on version 2.0 of the Open Government Licence with specific amendments for Transport for London (the "Licence"). TfL may at any time revise this Licence without notice. It is up to you ("You") to regularly review the Licence, which will be available on this website, in case there are any changes. Your continued use of the transport data feeds You have opted to receive ("Information") after a change has been made to the Licence will be treated as Your acceptance of that change.

Using Information under this Licence TfL grants You a worldwide, royalty-free, perpetual, non-exclusive Licence to use the Information subject to the conditions below (as varied from time to time).

This Licence does not affect Your freedom under fair dealing or fair use or any other copyright or database right exceptions and limitations.

This Licence shall apply from the date of registration and shall continue for the period the Information is provided to You or You breach the Licence.

Rights You are free to:

Copy, publish, distribute and transmit the Information Adapt the Information and Exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in Your own product or application Requirements You must, where You do any of the above:

Acknowledge TfL as the source of the Information by including the following attribution statement 'Powered by TfL Open Data' Acknowledge that this Information contains Ordnance Survey derived data by including the following attribution statement: 'Contains OS data © Crown copyright and database rights 2016' and Geomni UK Map data © and database rights [2019] Ensure our intellectual property rights, including all logos, design rights, patents and trademarks, are protected by following our design and branding guidelines Limit traffic requests up to a maximum of 300 calls per minute per data feed. TfL reserves the right to throttle or limit access to feeds when it is believed the overall service is being degraded by excessive use and Ensure the information You provide on registration is accurate These are important conditions of this Licence and if You fail to comply with them the rights granted to You under this Licence, or any similar licence granted by TfL, will end automatically.

Exemptions This Licence does not:

Transfer any intellectual property rights in the Information to You or any third party Include personal data in the Information Provide any rights to use the Information after this Licence has ended Provide any rights to use any other intellectual property rights, including patents, trade marks, and design rights or permit You to: Use data from the Oyster, Congestion Charging and Santander Cycles websites to populate or update any other software or database or Use any automated system, software or process to extract content and/or data, including trawling, data mining and screen scraping in relation to the Oyster, Congestion Charging and Santander Cycles websites, except where expressly permitted under a written licence agreement with TfL. These are important conditions of this Licence and, if You fail to comply with them, the rights granted to You under this Licence, or any similar licence granted by TfL, will end automatically.

Non-endorsement This Licence does not grant You any right to use the Information in a way that suggests any official status or that TfL endorses You or Your use of the Information.

Context

The purpose is to try predict the future bike shares.

Content

The data is acquired from 3 sources:
- Https://cycling.data.tfl.gov.uk/ 'Contains OS data © Crown copyright and database rights 2016' and Geomni UK Map data © and database rights [2019] 'Powered by TfL Open Data'
- freemeteo.com - weather data
- https://www.gov.uk/bank-holidays
From 1/1/2015 to 31/12/2016

The data from cycling dataset is grouped by "Start time", this represent the count of new bike shares grouped by hour. The long duration shares are not taken in the count.

Metadata:

"timestamp" - timestamp field for grouping the data
"cnt" - the count of a new bike shares
"t1" - real temperature in C
"t2" - temperature in C "feels like"
"hum" - humidity in percentage
"wind_speed" - wind speed in km/h
"weather_code" - category of the weather
"is_holiday" - boolean field - 1 holiday / 0 non holiday
"is_weekend" - boolean field - 1 if the day is weekend
"season" - category field meteorological seasons: 0-spring ; 1-summer; 2-fall; 3-winter.

"weathe_code" category description:
1 = Clear ; mostly clear but have some values with haze/fog/patches of fog/ fog in vicinity
2 = scattered clouds / few clouds
3 = Broken clouds
4 = Cloudy
7 = Rain/ light Rain shower/ Light rain
10 = rain with thunderstorm
26 = snowfall
94 = Freezing Fog

--- Original source retains full ownership of the source dataset ---

TagX Web Browsing Clickstream Data: Unveiling Digital Behavior Across North America and EU Unique Insights into Online User Behavior TagX Web Browsing clickstream Data offers an unparalleled window into the digital lives of 1 million users across North America and the European Union. This comprehensive dataset stands out in the market due to its breadth, depth, and stringent compliance with data protection regulations. What Makes Our Data Unique?

Extensive Geographic Coverage: Spanning two major markets, our data provides a holistic view of web browsing patterns in developed economies. Large User Base: With 300K active users, our dataset offers statistically significant insights across various demographics and user segments. GDPR and CCPA Compliance: We prioritize user privacy and data protection, ensuring that our data collection and processing methods adhere to the strictest regulatory standards. Real-time Updates: Our clickstream data is continuously refreshed, providing up-to-the-minute insights into evolving online trends and user behaviors. Granular Data Points: We capture a wide array of metrics, including time spent on websites, click patterns, search queries, and user journey flows.

Data Sourcing: Ethical and Transparent Our web browsing clickstream data is sourced through a network of partnered websites and applications. Users explicitly opt-in to data collection, ensuring transparency and consent. We employ advanced anonymization techniques to protect individual privacy while maintaining the integrity and value of the aggregated data. Key aspects of our data sourcing process include:

Voluntary user participation through clear opt-in mechanisms Regular audits of data collection methods to ensure ongoing compliance Collaboration with privacy experts to implement best practices in data anonymization Continuous monitoring of regulatory landscapes to adapt our processes as needed

Primary Use Cases and Verticals TagX Web Browsing clickstream Data serves a multitude of industries and use cases, including but not limited to:

Digital Marketing and Advertising:

Audience segmentation and targeting Campaign performance optimization Competitor analysis and benchmarking

E-commerce and Retail:

Customer journey mapping Product recommendation enhancements Cart abandonment analysis

Media and Entertainment:

Content consumption trends Audience engagement metrics Cross-platform user behavior analysis

Financial Services:

Risk assessment based on online behavior Fraud detection through anomaly identification Investment trend analysis

Technology and Software:

User experience optimization Feature adoption tracking Competitive intelligence

Market Research and Consulting:

Consumer behavior studies Industry trend analysis Digital transformation strategies

Integration with Broader Data Offering TagX Web Browsing clickstream Data is a cornerstone of our comprehensive digital intelligence suite. It seamlessly integrates with our other data products to provide a 360-degree view of online user behavior:

Social Media Engagement Data: Combine clickstream insights with social media interactions for a holistic understanding of digital footprints. Mobile App Usage Data: Cross-reference web browsing patterns with mobile app usage to map the complete digital journey. Purchase Intent Signals: Enrich clickstream data with purchase intent indicators to power predictive analytics and targeted marketing efforts. Demographic Overlays: Enhance web browsing data with demographic information for more precise audience segmentation and targeting.

By leveraging these complementary datasets, businesses can unlock deeper insights and drive more impactful strategies across their digital initiatives. Data Quality and Scale We pride ourselves on delivering high-quality, reliable data at scale:

Rigorous Data Cleaning: Advanced algorithms filter out bot traffic, VPNs, and other non-human interactions. Regular Quality Checks: Our data science team conducts ongoing audits to ensure data accuracy and consistency. Scalable Infrastructure: Our robust data processing pipeline can handle billions of daily events, ensuring comprehensive coverage. Historical Data Availability: Access up to 24 months of historical data for trend analysis and longitudinal studies. Customizable Data Feeds: Tailor the data delivery to your specific needs, from raw clickstream events to aggregated insights.

Empowering Data-Driven Decision Making In today's digital-first world, understanding online user behavior is crucial for businesses across all sectors. TagX Web Browsing clickstream Data empowers organizations to make informed decisions, optimize their digital strategies, and stay ahead of the competition. Whether you're a marketer looking to refine your targeting, a product manager seeking to enhance user experience, or a researcher exploring digital trends, our cli...

Salutary Data is a boutique, B2B contact and company data provider that's committed to delivering high quality data for sales intelligence, lead generation, marketing, recruiting / HR, identity resolution, and ML / AI. Our database currently consists of 148MM+ highly curated B2B Contacts ( US only), along with over 4M+ companies, and is updated regularly to ensure we have the most up-to-date information.

We can enrich your in-house data ( CRM Enrichment, Lead Enrichment, etc.) and provide you with a custom dataset ( such as a lead list) tailored to your target audience specifications and data use-case. We also support large-scale data licensing to software providers and agencies that intend to redistribute our data to their customers and end-users.

What makes Salutary unique? - We offer our clients a truly unique, one-stop aggregation of the best-of-breed quality data sources. Our supplier network consists of numerous, established high quality suppliers that are rigorously vetted. - We leverage third party verification vendors to ensure phone numbers and emails are accurate and connect to the right person. Additionally, we deploy automated and manual verification techniques to ensure we have the latest job information for contacts. - We're reasonably priced and easy to work with.

Products: API Suite Web UI Full and Custom Data Feeds

Services: Data Enrichment - We assess the fill rate gaps and profile your customer file for the purpose of appending fields, updating information, and/or rendering net new “look alike” prospects for your campaigns. ABM Match & Append - Send us your domain or other company related files, and we’ll match your Account Based Marketing targets and provide you with B2B contacts to campaign. Optionally throw in your suppression file to avoid any redundant records. Verification (“Cleaning/Hygiene”) Services - Address the 2% per month aging issue on contact records! We will identify duplicate records, contacts no longer at the company, rid your email hard bounces, and update/replace titles or phones. This is right up our alley and levers our existing internal and external processes and systems.