100+ datasets found
  1. Top challenges for big data analytics implementation in companies worldwide...

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Top challenges for big data analytics implementation in companies worldwide 2017 [Dataset]. https://www.statista.com/statistics/933143/worldwide-big-data-implementation-problems/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2017
    Area covered
    Worldwide
    Description

    The statistic shows the problems that organizations face when using big data technologies worldwide as of 2017. Around ** percent of respondents stated that inadequate analytical know-how was a major problem that their organization faced when using big data technologies as of 2017.

  2. d

    Data from: Problems in dealing with missing data and informative censoring...

    • catalog.data.gov
    • odgavaprod.ogopendata.com
    Updated Jul 24, 2025
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    National Institutes of Health (2025). Problems in dealing with missing data and informative censoring in clinical trials [Dataset]. https://catalog.data.gov/dataset/problems-in-dealing-with-missing-data-and-informative-censoring-in-clinical-trials
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    Dataset updated
    Jul 24, 2025
    Dataset provided by
    National Institutes of Health
    Description

    A common problem in clinical trials is the missing data that occurs when patients do not complete the study and drop out without further measurements. Missing data cause the usual statistical analysis of complete or all available data to be subject to bias. There are no universally applicable methods for handling missing data. We recommend the following: (1) Report reasons for dropouts and proportions for each treatment group; (2) Conduct sensitivity analyses to encompass different scenarios of assumptions and discuss consistency or discrepancy among them; (3) Pay attention to minimize the chance of dropouts at the design stage and during trial monitoring; (4) Collect post-dropout data on the primary endpoints, if at all possible; and (5) Consider the dropout event itself an important endpoint in studies with many.

  3. R

    Data from: Problem Dataset

    • universe.roboflow.com
    zip
    Updated Dec 23, 2024
    + more versions
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    jin (2024). Problem Dataset [Dataset]. https://universe.roboflow.com/jin-cthqm/problem-tqqcx
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    zipAvailable download formats
    Dataset updated
    Dec 23, 2024
    Dataset authored and provided by
    jin
    License

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

    Variables measured
    Problem Bounding Boxes
    Description

    Problem

    ## Overview
    
    Problem is a dataset for object detection tasks - it contains Problem annotations for 2,923 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  4. d

    Data from: Peer-to-Peer Data Mining, Privacy Issues, and Games

    • catalog.data.gov
    • data.nasa.gov
    • +2more
    Updated Apr 10, 2025
    + more versions
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    Dashlink (2025). Peer-to-Peer Data Mining, Privacy Issues, and Games [Dataset]. https://catalog.data.gov/dataset/peer-to-peer-data-mining-privacy-issues-and-games
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    Dataset updated
    Apr 10, 2025
    Dataset provided by
    Dashlink
    Description

    Peer-to-Peer (P2P) networks are gaining increasing popularity in many distributed applications such as file-sharing, network storage, web caching, sear- ching and indexing of relevant documents and P2P network-threat analysis. Many of these applications require scalable analysis of data over a P2P network. This paper starts by offering a brief overview of distributed data mining applications and algorithms for P2P environments. Next it discusses some of the privacy concerns with P2P data mining and points out the problems of existing privacy-preserving multi-party data mining techniques. It further points out that most of the nice assumptions of these existing privacy preserving techniques fall apart in real-life applications of privacy-preserving distributed data mining (PPDM). The paper offers a more realistic formulation of the PPDM problem as a multi-party game and points out some recent results.

  5. Problems of poor data quality for enterprises in North America 2015

    • statista.com
    Updated Jan 26, 2016
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    Statista (2016). Problems of poor data quality for enterprises in North America 2015 [Dataset]. https://www.statista.com/statistics/520490/north-america-survey-enterprise-poor-data-quality-problems/
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    Dataset updated
    Jan 26, 2016
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2015
    Area covered
    United States, Canada
    Description

    The statistic shows the problems caused by poor quality data for enterprises in North America, according to a survey of North American IT executives conducted by 451 Research in 2015. As of 2015, ** percent of respondents indicated that having poor quality data can result in extra costs for the business.

  6. H

    Political Analysis Using R: Example Code and Data, Plus Data for Practice...

    • dataverse.harvard.edu
    • search.dataone.org
    Updated Apr 28, 2020
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    Jamie Monogan (2020). Political Analysis Using R: Example Code and Data, Plus Data for Practice Problems [Dataset]. http://doi.org/10.7910/DVN/ARKOTI
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 28, 2020
    Dataset provided by
    Harvard Dataverse
    Authors
    Jamie Monogan
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Each R script replicates all of the example code from one chapter from the book. All required data for each script are also uploaded, as are all data used in the practice problems at the end of each chapter. The data are drawn from a wide array of sources, so please cite the original work if you ever use any of these data sets for research purposes.

  7. H

    Data from: Randomly generated problems for the complexity resolution problem...

    • dataverse.harvard.edu
    • dataone.org
    Updated Apr 6, 2020
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    Mohamed Ossama Hassan; Antoine Saucier; Soumaya Yacout; Francois Soumis (2020). Randomly generated problems for the complexity resolution problem in a multi sector planning context [Dataset]. http://doi.org/10.7910/DVN/II5JZG
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 6, 2020
    Dataset provided by
    Harvard Dataverse
    Authors
    Mohamed Ossama Hassan; Antoine Saucier; Soumaya Yacout; Francois Soumis
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    All the randomly generated problems in this data set involve a number A of aircraft passing through a square multi-sector area (MSA) of side 600 km. This MSA is composed of four square adjacent sectors of side 300 km. The aircraft use four different flight levels that belong to the same MSA. The aircraft trajectories are randomly generated in such a way that all aircraft are either flying from bottom to upper MSA borders, or from left to right borders. Taking the origin at the bottom left corner of the MSA, the distance between the first waypoint and the origin is randomly generated using the continuous uniform distribution U[75 km, 595 km]. Each trajectory is composed of three waypoints located on the MSA edges. The first waypoint is located on either the bottom or the left MSA border. The other two waypoints are generated randomly along the opposing sector borders using a uniform distribution. The cruise speeds of the aircraft are randomly generated using the continuous uniform distribution U[458 knots, 506 knots]. The time at which the aircraft enters the MSA follows the continuous uniform distribution U[20 min, 90 min]. The flight level used for each trajectory is randomly generated using a discrete uniform distribution U{1, K}. A constant flight level is used by 90% of the aircraft. The others undergo one flight level change at the internal boundary. For these aircraft, the second flight level is randomly generated using U{1, K} while excluding the first sector flight level.

  8. R

    Data Baru Fix Dataset

    • universe.roboflow.com
    zip
    Updated May 30, 2023
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    IT Del (2023). Data Baru Fix Dataset [Dataset]. https://universe.roboflow.com/it-del/data-baru-fix
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    zipAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset authored and provided by
    IT Del
    License

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

    Variables measured
    Pin Del Mahasiswa Bounding Boxes
    Description

    Data Baru FIx

    ## Overview
    
    Data Baru FIx is a dataset for object detection tasks - it contains Pin Del Mahasiswa annotations for 711 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  9. D

    Replication Data for: Constraint-aware neural networks for Riemann problems

    • darus.uni-stuttgart.de
    Updated Jan 11, 2024
    + more versions
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    Jim M. Magiera (2024). Replication Data for: Constraint-aware neural networks for Riemann problems [Dataset]. http://doi.org/10.18419/DARUS-3869
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 11, 2024
    Dataset provided by
    DaRUS
    Authors
    Jim M. Magiera
    License

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

    Dataset funded by
    DFG
    Description

    Data sets of the article "Constraint-aware neural networks for Riemann problems", consisting of training and test data sets for Riemann solutions of the cubic flux model, an isothermal two-phase model, and the Euler equations for an ideal gas. You can find detailed information in the README.md.

  10. Sign Problems - All Incidents - Dataset - data.gov.uk

    • ckan.publishing.service.gov.uk
    Updated May 10, 2021
    + more versions
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    ckan.publishing.service.gov.uk (2021). Sign Problems - All Incidents - Dataset - data.gov.uk [Dataset]. https://ckan.publishing.service.gov.uk/dataset/sign-problems-all-incidents
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    Dataset updated
    May 10, 2021
    Dataset provided by
    CKANhttps://ckan.org/
    Description

    This dataset contains all sign incidents in York recorded in City of York Council’s customer relationship management (CRM) tool from January 2021 onwards. Please note the dataset excludes incidents created in the last 14 days and that incidents with no end date are currently unresolved. For further information about sign problems and reporting sign problems please see the City of York Council’s website. *Please note that the data published within this dataset is a live API link to CYC's GIS server. Any changes made to the master copy of the data will be immediately reflected in the resources of this dataset. The date shown in the "Last Updated" field of each GIS resource reflects when the data was first published.

  11. Housing Maintenance Code Complaints and Problems

    • data.cityofnewyork.us
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • +2more
    application/rdfxml +5
    Updated Aug 31, 2025
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    Department of Housing Preservation & Development (HPD) (2025). Housing Maintenance Code Complaints and Problems [Dataset]. https://data.cityofnewyork.us/Housing-Development/Housing-Maintenance-Code-Complaints-and-Problems/ygpa-z7cr
    Explore at:
    xml, tsv, csv, application/rssxml, application/rdfxml, jsonAvailable download formats
    Dataset updated
    Aug 31, 2025
    Dataset provided by
    New York City Department of Housing Preservation and Development
    Authors
    Department of Housing Preservation & Development (HPD)
    Description

    The Department of Housing Preservation and Development (HPD) records complaints that are made by the public for conditions which violate the New York City Housing Maintenance Code (HMC) or the New York State Multiple Dwelling Law (MDL).

  12. U

    Data from: Dataset of the study: "Chatbots put to the test in math and logic...

    • researchdata.bath.ac.uk
    • explore.openaire.eu
    Updated May 20, 2023
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    Vagelis Plevris; George Papazafeiropoulos; Alejandro Jimenez Rios (2023). Dataset of the study: "Chatbots put to the test in math and logic problems: A preliminary comparison and assessment of ChatGPT-3.5, ChatGPT-4, and Google Bard" [Dataset]. http://doi.org/10.5281/zenodo.7940781
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    Dataset updated
    May 20, 2023
    Dataset provided by
    Zenodo
    Authors
    Vagelis Plevris; George Papazafeiropoulos; Alejandro Jimenez Rios
    Dataset funded by
    Oslo Metropolitan University
    Description

    This dataset contains the 30 questions that were posed to the chatbots (i) ChatGPT-3.5; (ii) ChatGPT-4; and (iii) Google Bard, in May 2023 for the study “Chatbots put to the test in math and logic problems: A preliminary comparison and assessment of ChatGPT-3.5, ChatGPT-4, and Google Bard”. These 30 questions describe mathematics and logic problems that have a unique correct answer. The questions are fully described with plain text only, without the need for any images or special formatting. The questions are divided into two sets of 15 questions each (Set A and Set B). The questions of Set A are 15 “Original” problems that cannot be found online, at least in their exact wording, while Set B contains 15 “Published” problems that one can find online by searching on the internet, usually with their solution. Each question is posed three times to each chatbot.

    This dataset contains the following: (i) The full set of the 30 questions, A01-A15 and B01-B15; (ii) the correct answer for each one of them; (iii) an explanation of the solution, for the problems where such an explanation is needed, (iv) the 30 (questions) × 3 (chatbots) × 3 (answers) = 270 detailed answers of the chatbots. For the published problems of Set B, we also provide a reference to the source where each problem was taken from.

  13. d

    EMS - Top Ten Dispatch Problems by Fiscal Year

    • catalog.data.gov
    • data.austintexas.gov
    Updated Apr 25, 2025
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    data.austintexas.gov (2025). EMS - Top Ten Dispatch Problems by Fiscal Year [Dataset]. https://catalog.data.gov/dataset/ems-top-ten-dispatch-problems-by-fiscal-year
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    Dataset updated
    Apr 25, 2025
    Dataset provided by
    data.austintexas.gov
    Description

    This table shows the 10 most frequently recorded incident problem types as recorded by communications personnel for each fiscal year presented.

  14. B

    BPI Challenge 2013, closed problems

    • data.4tu.nl
    zip
    + more versions
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    Ward Steeman, BPI Challenge 2013, closed problems [Dataset]. http://doi.org/10.4121/uuid:c2c3b154-ab26-4b31-a0e8-8f2350ddac11
    Explore at:
    zipAvailable download formats
    Dataset provided by
    Ghent University
    Authors
    Ward Steeman
    License

    https://doi.org/10.4121/resource:terms_of_usehttps://doi.org/10.4121/resource:terms_of_use

    Description

    Log of Volvo IT problem management (closed problems) Parent item: BPI Challenge 2013 Logs of Volvo IT incident and problem management

  15. U

    United States SBOI: sa: Most Pressing Problem: A Year Ago: Others

    • ceicdata.com
    Updated Mar 21, 2021
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    CEICdata.com (2021). United States SBOI: sa: Most Pressing Problem: A Year Ago: Others [Dataset]. https://www.ceicdata.com/en/united-states/nfib-index-of-small-business-optimism/sboi-sa-most-pressing-problem-a-year-ago-others
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    Dataset updated
    Mar 21, 2021
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Mar 1, 2024 - Feb 1, 2025
    Area covered
    United States
    Variables measured
    Business Confidence Survey
    Description

    United States SBOI: sa: Most Pressing Problem: A Year Ago: Others data was reported at 5.000 % in Mar 2025. This records a decrease from the previous number of 6.000 % for Feb 2025. United States SBOI: sa: Most Pressing Problem: A Year Ago: Others data is updated monthly, averaging 7.000 % from Jan 2014 (Median) to Mar 2025, with 131 observations. The data reached an all-time high of 11.000 % in May 2023 and a record low of 3.000 % in Jul 2024. United States SBOI: sa: Most Pressing Problem: A Year Ago: Others data remains active status in CEIC and is reported by National Federation of Independent Business. The data is categorized under Global Database’s United States – Table US.S042: NFIB Index of Small Business Optimism. [COVID-19-IMPACT]

  16. Main challenges affecting data analytics for CX in the U.S. 2021

    • statista.com
    Updated Jul 11, 2025
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    Statista (2025). Main challenges affecting data analytics for CX in the U.S. 2021 [Dataset]. https://www.statista.com/statistics/1196851/main-challenges-affecting-data-analytics-for-cx-in-the-us/
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    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 2021 - Jun 2021
    Area covered
    United States
    Description

    According to the results of a survey on customer experience (CX) among businesses conducted in the United States in 2021, the main challenge affecting data analysis capability for CX is the lack of reliability and integrity of available data. Data security followed, being chosen by almost ** percent of the respondents.

  17. a

    Citizen Problems (Open Data)

    • hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Oct 5, 2019
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    ArcGIS Solutions Demonstration organization (2019). Citizen Problems (Open Data) [Dataset]. https://hub.arcgis.com/maps/2e94dc541827461e9b5827f44b89ec4f
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    Dataset updated
    Oct 5, 2019
    Dataset authored and provided by
    ArcGIS Solutions Demonstration organization
    Area covered
    Description

    Problems reported, comments and satisfaction surveys submitted by the general public through focused citizen engagement applications.

  18. d

    Data from: PISA 2012 Assessment and Analytical Framework Mathematics,...

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Mar 30, 2021
    + more versions
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    U.S. Department of State (2021). PISA 2012 Assessment and Analytical Framework Mathematics, Reading, Science, Problem Solving and Financial Literacy [Dataset]. https://catalog.data.gov/dataset/pisa-2012-assessment-and-analytical-framework-mathematics-reading-science-problem-solving-
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    Dataset updated
    Mar 30, 2021
    Dataset provided by
    U.S. Department of State
    Description

    Are students well prepared to meet the challenges of the future? Can they analyse, reason and communicate their ideas effectively? Have they found the kinds of interests they can pursue throughout their lives as productive members of the economy and society? The OECD Programme for International Student Assessment (PISA) seeks to answer these questions through the most comprehensive and rigorous international assessment of student knowledge and skills. PISA 2012 Assessment and Analytical Framework presents the conceptual framework underlying the fifth cycle of PISA. Similar to the previous cycles, the 2012 assessment covers reading, mathematics and science, with the major focus on mathematical literacy. Two other domains are evaluated: problem solving and financial literacy. Students respond to a background questionnaire and, as an option, to an educational career questionnaire as well as another questionnaire about Information and Communication Technologies (ICTs). Additional supporting information is gathered from the school authorities through the school questionnaire and from the parents through a third optional questionnaire. Sixty-six countries and economies, including all 34 OECD member countries, are taking part in the PISA 2012 assessment.

  19. g

    Development Economics Data Group - Score on action when a problem arose |...

    • gimi9.com
    + more versions
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    Development Economics Data Group - Score on action when a problem arose | gimi9.com [Dataset]. https://gimi9.com/dataset/worldbank_wb_es_t_mgmt2/
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    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Score on Action When a Problem Arises represents a measurement of how establishments respond to issues during the production process, encompassing actions taken to rectify problems and prevent future occurrences.

  20. Data storage challenges in organizations worldwide 2016-2017

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Data storage challenges in organizations worldwide 2016-2017 [Dataset]. https://www.statista.com/statistics/822188/worldwide-data-storage-challenges/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    The statistic shows the challenges facing users of data storage and storage services in enterprise organizations worldwide, in 2016 and 2017. As of 2017, ** percent of respondents highlighted the handling of data growth as one of the largest storage challenges.

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Statista (2025). Top challenges for big data analytics implementation in companies worldwide 2017 [Dataset]. https://www.statista.com/statistics/933143/worldwide-big-data-implementation-problems/
Organization logo

Top challenges for big data analytics implementation in companies worldwide 2017

Explore at:
Dataset updated
Jul 10, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2017
Area covered
Worldwide
Description

The statistic shows the problems that organizations face when using big data technologies worldwide as of 2017. Around ** percent of respondents stated that inadequate analytical know-how was a major problem that their organization faced when using big data technologies as of 2017.

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