68 datasets found
  1. d

    Website Analytics

    • catalog.data.gov
    • data.brla.gov
    • +2more
    Updated Jul 26, 2025
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    data.brla.gov (2025). Website Analytics [Dataset]. https://catalog.data.gov/dataset/website-analytics-89ba5
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    Dataset updated
    Jul 26, 2025
    Dataset provided by
    data.brla.gov
    Description

    Web traffic statistics for the several City-Parish websites, brla.gov, city.brla.gov, Red Stick Ready, GIS, Open Data etc. Information provided by Google Analytics.

  2. d

    Website Analytics

    • catalog.data.gov
    • data.nola.gov
    • +4more
    Updated Jun 28, 2025
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    data.nola.gov (2025). Website Analytics [Dataset]. https://catalog.data.gov/dataset/website-analytics
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    Dataset updated
    Jun 28, 2025
    Dataset provided by
    data.nola.gov
    Description

    This data about nola.gov provides a window into how people are interacting with the the City of New Orleans online. The data comes from a unified Google Analytics account for New Orleans. We do not track individuals and we anonymize the IP addresses of all visitors.

  3. Web analytics software market share worldwide 2024

    • statista.com
    Updated Jul 1, 2025
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    Statista (2025). Web analytics software market share worldwide 2024 [Dataset]. https://www.statista.com/statistics/1258557/web-analytics-market-share-technology-worldwide/
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    Dataset updated
    Jul 1, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    World
    Description

    Google dominated the web analytics industry in 2024, with ***** of its web analytics technologies maintaining the top three positions in the global market. Google Global Site Tag was first with a market share of over ** percent, followed by Google Analytics and Google Universal Analytics who had market shares of approximately ** and ** percent, respectively. When all ***** technologies were combined, Google maintained more than ** percent of the total market share.

  4. Google Analytics Sample

    • kaggle.com
    zip
    Updated Sep 19, 2019
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    Google BigQuery (2019). Google Analytics Sample [Dataset]. https://www.kaggle.com/bigquery/google-analytics-sample
    Explore at:
    zip(0 bytes)Available download formats
    Dataset updated
    Sep 19, 2019
    Dataset provided by
    Googlehttp://google.com/
    BigQueryhttps://cloud.google.com/bigquery
    Authors
    Google BigQuery
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    The Google Merchandise Store sells Google branded merchandise. The data is typical of what you would see for an ecommerce website.

    Content

    The sample dataset contains Google Analytics 360 data from the Google Merchandise Store, a real ecommerce store. The Google Merchandise Store sells Google branded merchandise. The data is typical of what you would see for an ecommerce website. It includes the following kinds of information:

    Traffic source data: information about where website visitors originate. This includes data about organic traffic, paid search traffic, display traffic, etc. Content data: information about the behavior of users on the site. This includes the URLs of pages that visitors look at, how they interact with content, etc. Transactional data: information about the transactions that occur on the Google Merchandise Store website.

    Fork this kernel to get started.

    Acknowledgements

    Data from: https://bigquery.cloud.google.com/table/bigquery-public-data:google_analytics_sample.ga_sessions_20170801

    Banner Photo by Edho Pratama from Unsplash.

    Inspiration

    What is the total number of transactions generated per device browser in July 2017?

    The real bounce rate is defined as the percentage of visits with a single pageview. What was the real bounce rate per traffic source?

    What was the average number of product pageviews for users who made a purchase in July 2017?

    What was the average number of product pageviews for users who did not make a purchase in July 2017?

    What was the average total transactions per user that made a purchase in July 2017?

    What is the average amount of money spent per session in July 2017?

    What is the sequence of pages viewed?

  5. C

    City Website Analytics

    • data.ccrpc.org
    csv, json, rdf, xml
    Updated Aug 3, 2022
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    City of Urbana (2022). City Website Analytics [Dataset]. https://data.ccrpc.org/am/dataset/city-website-analytics
    Explore at:
    rdf, xml, json, csvAvailable download formats
    Dataset updated
    Aug 3, 2022
    Dataset provided by
    data.urbanaillinois.us
    Authors
    City of Urbana
    Description

    Information about pages on the City's website including their age and their Google Analytics data (everything from "PageViews" and to the right). If the Google Analytics fields are empty, the page hasn't been visited recently at all.

  6. Data from: Google Analytics & Twitter dataset from a movies, TV series and...

    • figshare.com
    • portalcientificovalencia.univeuropea.com
    txt
    Updated Feb 7, 2024
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    Víctor Yeste (2024). Google Analytics & Twitter dataset from a movies, TV series and videogames website [Dataset]. http://doi.org/10.6084/m9.figshare.16553061.v4
    Explore at:
    txtAvailable download formats
    Dataset updated
    Feb 7, 2024
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Víctor Yeste
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Author: Víctor Yeste. Universitat Politècnica de Valencia.The object of this study is the design of a cybermetric methodology whose objectives are to measure the success of the content published in online media and the possible prediction of the selected success variables.In this case, due to the need to integrate data from two separate areas, such as web publishing and the analysis of their shares and related topics on Twitter, has opted for programming as you access both the Google Analytics v4 reporting API and Twitter Standard API, always respecting the limits of these.The website analyzed is hellofriki.com. It is an online media whose primary intention is to solve the need for information on some topics that provide daily a vast number of news in the form of news, as well as the possibility of analysis, reports, interviews, and many other information formats. All these contents are under the scope of the sections of cinema, series, video games, literature, and comics.This dataset has contributed to the elaboration of the PhD Thesis:Yeste Moreno, VM. (2021). Diseño de una metodología cibermétrica de cálculo del éxito para la optimización de contenidos web [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/176009Data have been obtained from each last-minute news article published online according to the indicators described in the doctoral thesis. All related data are stored in a database, divided into the following tables:tesis_followers: User ID list of media account followers.tesis_hometimeline: data from tweets posted by the media account sharing breaking news from the web.status_id: Tweet IDcreated_at: date of publicationtext: content of the tweetpath: URL extracted after processing the shortened URL in textpost_shared: Article ID in WordPress that is being sharedretweet_count: number of retweetsfavorite_count: number of favoritestesis_hometimeline_other: data from tweets posted by the media account that do not share breaking news from the web. Other typologies, automatic Facebook shares, custom tweets without link to an article, etc. With the same fields as tesis_hometimeline.tesis_posts: data of articles published by the web and processed for some analysis.stats_id: Analysis IDpost_id: Article ID in WordPresspost_date: article publication date in WordPresspost_title: title of the articlepath: URL of the article in the middle webtags: Tags ID or WordPress tags related to the articleuniquepageviews: unique page viewsentrancerate: input ratioavgtimeonpage: average visit timeexitrate: output ratiopageviewspersession: page views per sessionadsense_adunitsviewed: number of ads viewed by usersadsense_viewableimpressionpercent: ad display ratioadsense_ctr: ad click ratioadsense_ecpm: estimated ad revenue per 1000 page viewstesis_stats: data from a particular analysis, performed at each published breaking news item. Fields with statistical values can be computed from the data in the other tables, but total and average calculations are saved for faster and easier further processing.id: ID of the analysisphase: phase of the thesis in which analysis has been carried out (right now all are 1)time: "0" if at the time of publication, "1" if 14 days laterstart_date: date and time of measurement on the day of publicationend_date: date and time when the measurement is made 14 days latermain_post_id: ID of the published article to be analysedmain_post_theme: Main section of the published article to analyzesuperheroes_theme: "1" if about superheroes, "0" if nottrailer_theme: "1" if trailer, "0" if notname: empty field, possibility to add a custom name manuallynotes: empty field, possibility to add personalized notes manually, as if some tag has been removed manually for being considered too generic, despite the fact that the editor put itnum_articles: number of articles analysednum_articles_with_traffic: number of articles analysed with traffic (which will be taken into account for traffic analysis)num_articles_with_tw_data: number of articles with data from when they were shared on the media’s Twitter accountnum_terms: number of terms analyzeduniquepageviews_total: total page viewsuniquepageviews_mean: average page viewsentrancerate_mean: average input ratioavgtimeonpage_mean: average duration of visitsexitrate_mean: average output ratiopageviewspersession_mean: average page views per sessiontotal: total of ads viewedadsense_adunitsviewed_mean: average of ads viewedadsense_viewableimpressionpercent_mean: average ad display ratioadsense_ctr_mean: average ad click ratioadsense_ecpm_mean: estimated ad revenue per 1000 page viewsTotal: total incomeretweet_count_mean: average incomefavorite_count_total: total of favoritesfavorite_count_mean: average of favoritesterms_ini_num_tweets: total tweets on the terms on the day of publicationterms_ini_retweet_count_total: total retweets on the terms on the day of publicationterms_ini_retweet_count_mean: average retweets on the terms on the day of publicationterms_ini_favorite_count_total: total of favorites on the terms on the day of publicationterms_ini_favorite_count_mean: average of favorites on the terms on the day of publicationterms_ini_followers_talking_rate: ratio of followers of the media Twitter account who have recently published a tweet talking about the terms on the day of publicationterms_ini_user_num_followers_mean: average followers of users who have spoken of the terms on the day of publicationterms_ini_user_num_tweets_mean: average number of tweets published by users who spoke about the terms on the day of publicationterms_ini_user_age_mean: average age in days of users who have spoken of the terms on the day of publicationterms_ini_ur_inclusion_rate: URL inclusion ratio of tweets talking about terms on the day of publicationterms_end_num_tweets: total tweets on terms 14 days after publicationterms_ini_retweet_count_total: total retweets on terms 14 days after publicationterms_ini_retweet_count_mean: average retweets on terms 14 days after publicationterms_ini_favorite_count_total: total bookmarks on terms 14 days after publicationterms_ini_favorite_count_mean: average of favorites on terms 14 days after publicationterms_ini_followers_talking_rate: ratio of media Twitter account followers who have recently posted a tweet talking about the terms 14 days after publicationterms_ini_user_num_followers_mean: average followers of users who have spoken of the terms 14 days after publicationterms_ini_user_num_tweets_mean: average number of tweets published by users who have spoken about the terms 14 days after publicationterms_ini_user_age_mean: the average age in days of users who have spoken of the terms 14 days after publicationterms_ini_ur_inclusion_rate: URL inclusion ratio of tweets talking about terms 14 days after publication.tesis_terms: data of the terms (tags) related to the processed articles.stats_id: Analysis IDtime: "0" if at the time of publication, "1" if 14 days laterterm_id: Term ID (tag) in WordPressname: Name of the termslug: URL of the termnum_tweets: number of tweetsretweet_count_total: total retweetsretweet_count_mean: average retweetsfavorite_count_total: total of favoritesfavorite_count_mean: average of favoritesfollowers_talking_rate: ratio of followers of the media Twitter account who have recently published a tweet talking about the termuser_num_followers_mean: average followers of users who were talking about the termuser_num_tweets_mean: average number of tweets published by users who were talking about the termuser_age_mean: average age in days of users who were talking about the termurl_inclusion_rate: URL inclusion ratio

  7. Z

    Network Traffic Analysis: Data and Code

    • data.niaid.nih.gov
    • zenodo.org
    Updated Jun 12, 2024
    + more versions
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    Homan, Sophia (2024). Network Traffic Analysis: Data and Code [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_11479410
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    Dataset updated
    Jun 12, 2024
    Dataset provided by
    Ferrell, Nathan
    Homan, Sophia
    Moran, Madeline
    Chan-Tin, Eric
    Honig, Joshua
    Soni, Shreena
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Code:

    Packet_Features_Generator.py & Features.py

    To run this code:

    pkt_features.py [-h] -i TXTFILE [-x X] [-y Y] [-z Z] [-ml] [-s S] -j

    -h, --help show this help message and exit -i TXTFILE input text file -x X Add first X number of total packets as features. -y Y Add first Y number of negative packets as features. -z Z Add first Z number of positive packets as features. -ml Output to text file all websites in the format of websiteNumber1,feature1,feature2,... -s S Generate samples using size s. -j

    Purpose:

    Turns a text file containing lists of incomeing and outgoing network packet sizes into separate website objects with associative features.

    Uses Features.py to calcualte the features.

    startMachineLearning.sh & machineLearning.py

    To run this code:

    bash startMachineLearning.sh

    This code then runs machineLearning.py in a tmux session with the nessisary file paths and flags

    Options (to be edited within this file):

    --evaluate-only to test 5 fold cross validation accuracy

    --test-scaling-normalization to test 6 different combinations of scalers and normalizers

    Note: once the best combination is determined, it should be added to the data_preprocessing function in machineLearning.py for future use

    --grid-search to test the best grid search hyperparameters - note: the possible hyperparameters must be added to train_model under 'if not evaluateOnly:' - once best hyperparameters are determined, add them to train_model under 'if evaluateOnly:'

    Purpose:

    Using the .ml file generated by Packet_Features_Generator.py & Features.py, this program trains a RandomForest Classifier on the provided data and provides results using cross validation. These results include the best scaling and normailzation options for each data set as well as the best grid search hyperparameters based on the provided ranges.

    Data

    Encrypted network traffic was collected on an isolated computer visiting different Wikipedia and New York Times articles, different Google search queres (collected in the form of their autocomplete results and their results page), and different actions taken on a Virtual Reality head set.

    Data for this experiment was stored and analyzed in the form of a txt file for each experiment which contains:

    First number is a classification number to denote what website, query, or vr action is taking place.

    The remaining numbers in each line denote:

    The size of a packet,

    and the direction it is traveling.

    negative numbers denote incoming packets

    positive numbers denote outgoing packets

    Figure 4 Data

    This data uses specific lines from the Virtual Reality.txt file.

    The action 'LongText Search' refers to a user searching for "Saint Basils Cathedral" with text in the Wander app.

    The action 'ShortText Search' refers to a user searching for "Mexico" with text in the Wander app.

    The .xlsx and .csv file are identical

    Each file includes (from right to left):

    The origional packet data,

    each line of data organized from smallest to largest packet size in order to calculate the mean and standard deviation of each packet capture,

    and the final Cumulative Distrubution Function (CDF) caluclation that generated the Figure 4 Graph.

  8. c

    Google Analytics www cityofrochester gov

    • data.cityofrochester.gov
    Updated Dec 11, 2021
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    Open_Data_Admin (2021). Google Analytics www cityofrochester gov [Dataset]. https://data.cityofrochester.gov/datasets/google-analytics-www-cityofrochester-gov/about
    Explore at:
    Dataset updated
    Dec 11, 2021
    Dataset authored and provided by
    Open_Data_Admin
    Description

    Data dictionary: Page_Title: Title of webpage used for pages of the website www.cityofrochester.gov Pageviews: Total number of pages viewed over the course of the calendar year listed in the year column. Repeated views of a single page are counted. Unique_Pageviews: Unique Pageviews - The number of sessions during which a specified page was viewed at least once. A unique pageview is counted for each URL and page title combination. Avg_Time: Average amount of time users spent looking at a specified page or screen. Entrances: The number of times visitors entered the website through a specified page.Bounce_Rate: " A bounce is a single-page session on your site. In Google Analytics, a bounce is calculated specifically as a session that triggers only a single request to the Google Analytics server, such as when a user opens a single page on your site and then exits without triggering any other requests to the Google Analytics server during that session. Bounce rate is single-page sessions on a page divided by all sessions that started with that page, or the percentage of all sessions on your site in which users viewed only a single page and triggered only a single request to the Google Analytics server. These single-page sessions have a session duration of 0 seconds since there are no subsequent hits after the first one that would let Google Analytics calculate the length of the session. "Exit_Rate: The number of exits from a page divided by the number of pageviews for the page. This is inclusive of sessions that started on different pages, as well as “bounce” sessions that start and end on the same page. For all pageviews to the page, Exit Rate is the percentage that were the last in the session. Year: Calendar year over which the data was collected. Data reflects the counts for each metric from January 1st through December 31st.

  9. A

    ‘Website Analytics’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Feb 13, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘Website Analytics’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-website-analytics-e2f0/efa1110a/?iid=003-677&v=presentation
    Explore at:
    Dataset updated
    Feb 13, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘Website Analytics’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/ecee4df3-8149-4b74-8927-428ea920b758 on 13 February 2022.

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

    Web traffic statistics for the several City-Parish websites, brla.gov, city.brla.gov, Red Stick Ready, GIS, Open Data etc. Information provided by Google Analytics.

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

  10. E

    Enterprise Website Analytics Software Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated May 21, 2025
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    Data Insights Market (2025). Enterprise Website Analytics Software Report [Dataset]. https://www.datainsightsmarket.com/reports/enterprise-website-analytics-software-1968768
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    ppt, pdf, docAvailable download formats
    Dataset updated
    May 21, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global Enterprise Website Analytics Software market is experiencing robust growth, driven by the increasing need for businesses to understand their online presence and optimize their digital strategies. The market's expansion is fueled by several key factors, including the rising adoption of cloud-based solutions offering scalability and cost-effectiveness, the proliferation of mobile devices and diverse digital channels requiring sophisticated analytics, and a growing focus on data-driven decision-making across all departments. Large enterprises are leading the adoption, leveraging these tools for detailed customer journey mapping, performance optimization, and enhanced ROI on marketing investments. However, the market faces challenges such as the complexity of integrating various analytics platforms and the need for specialized expertise to effectively interpret and utilize the vast amounts of data generated. The segment showing the fastest growth is likely cloud-based solutions due to their flexibility and accessibility. We estimate the 2025 market size to be around $15 billion, based on observable growth trends in related software markets and considering the increasing adoption of analytics solutions across various industries. A Compound Annual Growth Rate (CAGR) of 12% is projected for the forecast period (2025-2033), indicating substantial market expansion over the coming years. The competitive landscape is highly dynamic, with both established tech giants (Google, IBM) and specialized analytics providers (Adobe, SEMrush, Mixpanel) vying for market share. The ongoing trend towards mergers and acquisitions further shapes the industry. Companies are continually innovating to offer more comprehensive solutions, incorporating features like artificial intelligence (AI) for predictive analytics, real-time data visualization, and seamless integration with CRM systems. Geographic growth will vary, with North America and Europe expected to maintain significant market share due to high technological adoption rates. However, Asia-Pacific is projected to witness substantial growth driven by increasing digitalization and economic expansion. The market's future trajectory hinges on continuous innovation within analytics capabilities, addressing the challenges of data privacy and security, and fostering greater user-friendliness within these sophisticated platforms.

  11. b

    Corporate Website — Analytics — Top 100 search terms

    • data.brisbane.qld.gov.au
    csv, excel, json
    Updated Jul 29, 2025
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    (2025). Corporate Website — Analytics — Top 100 search terms [Dataset]. https://data.brisbane.qld.gov.au/explore/dataset/corporate-website-analytics-top-100-search-terms/
    Explore at:
    json, csv, excelAvailable download formats
    Dataset updated
    Jul 29, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Monthly analytics reports for the Brisbane City Council website

    Information regarding the sessions for Brisbane City Council website during the month including search terms used.

  12. d

    Website Analytics

    • catalog.data.gov
    • data.somervillema.gov
    • +1more
    Updated Feb 7, 2025
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    data.somervillema.gov (2025). Website Analytics [Dataset]. https://catalog.data.gov/dataset/somerville-analytics
    Explore at:
    Dataset updated
    Feb 7, 2025
    Dataset provided by
    data.somervillema.gov
    Description

    Contains view count data for the top 20 pages each day on the Somerville MA city website dating back to 2020. Data is used in the City's dashboard which can be found at https://www.somervilledata.farm/.

  13. Google analytics - 3 years evidence of impact tracking my website which...

    • dro.deakin.edu.au
    • researchdata.edu.au
    Updated Sep 22, 2024
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    Anne Wilson (2024). Google analytics - 3 years evidence of impact tracking my website which contains a biography, catalogues, writings and video and photography work [Dataset]. https://dro.deakin.edu.au/articles/dataset/Google_analytics_-_3_years_evidence_of_impact_tracking_my_website_which_contains_a_biography_catalogues_writings_and_video_and_photography_work/20896387
    Explore at:
    Dataset updated
    Sep 22, 2024
    Dataset provided by
    Deakin Universityhttp://www.deakin.edu.au/
    Authors
    Anne Wilson
    License

    https://www.rioxx.net/licenses/all-rights-reserved/https://www.rioxx.net/licenses/all-rights-reserved/

    Description

    Google analytics - 3 years evidence of impact tracking my website which contains a biography, catalogues, writings and video and photography work

  14. A

    ‘Website Analytics’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Feb 15, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘Website Analytics’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-website-analytics-fb4d/0461f557/?iid=001-795&v=presentation
    Explore at:
    Dataset updated
    Feb 15, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘Website Analytics’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/38f017ae-e1ec-4bab-9c49-592ba0c385c0 on 13 February 2022.

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

    Contains view count data for the top 20 pages each day on the Somerville MA city website dating back to 2020. Data is used in the City's dashboard which can be found at https://www.somervilledata.farm/.

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

  15. a

    Website Analytics

    • opendata.atlantaregional.com
    Updated Jan 14, 2020
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    City of Johns Creek, GA (2020). Website Analytics [Dataset]. https://opendata.atlantaregional.com/datasets/JohnsCreekGA::website-analytics/explore
    Explore at:
    Dataset updated
    Jan 14, 2020
    Dataset authored and provided by
    City of Johns Creek, GA
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This table is an extract of the data collected within Google Analytics for the domain www.JohnsCreekGA.gov.Some data has been parsed to make analysis of web traffic easier to perform and interpret. Data is updated into this hosted table once a month.

  16. Website Statistics

    • data.wu.ac.at
    • data.europa.eu
    csv, pdf
    Updated Jun 11, 2018
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    Lincolnshire County Council (2018). Website Statistics [Dataset]. https://data.wu.ac.at/schema/data_gov_uk/M2ZkZDBjOTUtMzNhYi00YWRjLWI1OWMtZmUzMzA5NjM0ZTdk
    Explore at:
    csv, pdfAvailable download formats
    Dataset updated
    Jun 11, 2018
    Dataset provided by
    Lincolnshire County Councilhttp://www.lincolnshire.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    This Website Statistics dataset has four resources showing usage of the Lincolnshire Open Data website. Web analytics terms used in each resource are defined in their accompanying Metadata file.

    • Website Usage Statistics: This document shows a statistical summary of usage of the Lincolnshire Open Data site for the latest calendar year.

    • Website Statistics Summary: This dataset shows a website statistics summary for the Lincolnshire Open Data site for the latest calendar year.

    • Webpage Statistics: This dataset shows statistics for individual Webpages on the Lincolnshire Open Data site by calendar year.

    • Dataset Statistics: This dataset shows cumulative totals for Datasets on the Lincolnshire Open Data site that have also been published on the national Open Data site Data.Gov.UK - see the Source link.

      Note: Website and Webpage statistics (the first three resources above) show only UK users, and exclude API calls (automated requests for datasets). The Dataset Statistics are confined to users with javascript enabled, which excludes web crawlers and API calls.

    These Website Statistics resources are updated annually in January by the Lincolnshire County Council Business Intelligence team. For any enquiries about the information contact opendata@lincolnshire.gov.uk.

  17. O

    Site Analytics: Asset Access Derived View

    • opendata.usac.org
    application/rdfxml +5
    Updated Jul 27, 2025
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    (2025). Site Analytics: Asset Access Derived View [Dataset]. https://opendata.usac.org/w/gchg-x5ee/default?cur=n7n9qdMpmx-
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    xml, tsv, application/rssxml, csv, json, application/rdfxmlAvailable download formats
    Dataset updated
    Jul 27, 2025
    Description

    This dataset includes data on how all datasets, stories and derived views (tabular views, visualizations and measures) on a domain are being accessed by users.

    The following usage types are included in the Access Type column:
    • grid view
    • primer page view
    • download
    • api read access
    • story page view
    • visualization page view
    • measure page view
    Usage data are segmented into the following user types:
    • site member: users who have logged in and have been granted a role on the domain
    • community user: users who have logged in but do not have a role on the domain
    • anonymous: users who have not logged in to the domain

    Data are updated by a system process at least once a day.

    Please see Site Analytics: Asset Access for more detail.

  18. O

    Corporate Website — Analytics — Top 100 search terms

    • data.qld.gov.au
    • researchdata.edu.au
    html
    Updated Aug 2, 2025
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    Brisbane City Council (2025). Corporate Website — Analytics — Top 100 search terms [Dataset]. https://www.data.qld.gov.au/dataset/corporate-website-analytics-top-100-search-terms
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Aug 2, 2025
    Dataset authored and provided by
    Brisbane City Council
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset is available on Brisbane City Council’s open data website – data.brisbane.qld.gov.au. The site provides additional features for viewing and interacting with the data and for downloading the data in various formats.

    Monthly analytics reports for the Brisbane City Council website

    Information regarding the sessions for Brisbane City Council website during the month including search terms used.

  19. T

    CincyInsights Website Analytics

    • data.cincinnati-oh.gov
    application/rdfxml +5
    Updated Jul 17, 2025
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    City of Cincinnati (2025). CincyInsights Website Analytics [Dataset]. https://data.cincinnati-oh.gov/w/rcr9-82q7/default?cur=ReInOPKhrLv&from=EAbjCsQObGX
    Explore at:
    tsv, application/rdfxml, json, csv, xml, application/rssxmlAvailable download formats
    Dataset updated
    Jul 17, 2025
    Dataset authored and provided by
    City of Cincinnati
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    Data Description: This data set provides all usage information for all web pages on the City of Cincinnati's interactive dashboard portal, CincyInsights.

    Data Creation: This data set is maintained by the City of Cincinnati's Open Data host, Socrata.

    Data Created By: Socrata

    Refresh Frequency: Daily

    Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this data set.

    Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

    Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

  20. g

    Website Analytics Daily Page Views | gimi9.com

    • gimi9.com
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    Website Analytics Daily Page Views | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_website-analytics-daily-page-views
    Explore at:
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset is a direct export from DC government's Google Analytics report of daily page views on the https://www.dc.gov web portal. This shows daily page views, per year, on DC.gov from 2008 to March 2020. It is identified by the part of the URL after the dc.gov domain path where users have visited.

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data.brla.gov (2025). Website Analytics [Dataset]. https://catalog.data.gov/dataset/website-analytics-89ba5

Website Analytics

Explore at:
Dataset updated
Jul 26, 2025
Dataset provided by
data.brla.gov
Description

Web traffic statistics for the several City-Parish websites, brla.gov, city.brla.gov, Red Stick Ready, GIS, Open Data etc. Information provided by Google Analytics.

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