SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Automating large-scale data quality verification
8 references·10 citing·45 second hop
Automating large-scale data quality verification (2018)Automating large-scale data quality verif…DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)DeepAR: Probabilistic forecas…HoloClean (2017)HoloCleanM odel DB (2016)M odel DBData Cleaning (2016)Data CleaningMethodologies for data quality assessment and improvement (2009)Methodologies for data qualit…Conditional Functional Dependencies for Data Cleaning (2007)Conditional Functional Depend…Declarative Data Cleaning: Language, Model, and Algorithms (2001)Declarative Data Cleaning: La…Forecasting principles and practiceForecasting principles and pr…Data Readiness for AI: A 360-Degree Survey (2025)Data Readiness for AI: A 360-…On the Data Quality and Imbalance in Machine Learning-based Design and Manufacturing—A Systematic Review (2024)On the Data Quality and Imbal…Data smells (2022)Data smellsAction-oriented process mining: bridging the gap between insights and actions (2022)Action-oriented process minin…Data quality challenges in large-scale cyber-physical systems: A systematic review (2021)Data quality challenges in la…TensorFlow Data Validation: Data Analysis and Validation in Continuous ML Pipelines (2020)TensorFlow Data Validation: D…From Data to Models and Back (2020)From Data to Models and BackUni-Detect (2019)Uni-DetectRisk-based data validation in machine learning-based software systems (2019)Risk-based data validation in…Deducing certain fixes to graphs (2019)Deducing certain fixes to gra…An overview of data warehousing and OLAP technology (1997)Real-world Data is Dirty: Data Cleansing and The Merge/Purge Problem (1998)Data Cleaning: Problems and Current Approaches. (2000)TAILOR: a record linkage toolbox (2003)Record linkage (2006)NADEEF (2013)Reengineering the Corporation (1993)Reengineering the corporation: A manifesto for business revolution (1993)Beyond Accuracy: What Data Quality Means to Data Consumers (1996)Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications (2014)Open data quality measurement framework: Definition and application to Open Government Data (2016)Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda (2021)Potter's Wheel: An Interactive Data Cleaning System (2001)Discovering data quality rules (2008)Foundations of Data Quality Management (2012)Data quality: The other face of Big Data (2014)Scientific workflow management and the Kepler system (2005)VisTrails (2006)The Taverna workflow suite: designing and executing workflows of Web Services on the desktop, web or in the cloud (2013)Probabilistic demand forecasting at scale (2017)Accelerating Human-in-the-loop Machine Learning (2018)Artificial Intelligence Governance For Businesses (2022)CrowdER (2012)Data quality in internet of things: A state-of-the-art survey (2016)CleanML: A Study for Evaluating the Impact of Data Cleaning on ML Classification Tasks (2021)REFORMS: Consensus-based Recommendations for Machine-learning-based Science (2024)Forecasting with artificial neural networks: (1998)Designing and managing the supply chain : concepts, strategies, and case studies (2000)Automatic Time Series Forecasting: The forecast Package for R (2008)N-BEATS: Neural basis expansion analysis for interpretable time series forecasting (2019)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Forecasting: theory and practice (2022)Quality Is Free: The Art of Making Quality Certain (1979)Anchoring data quality dimensions in ontological foundations (1996)Data quality assessment (2002)An Integrative Theoretical Framework for Responsible Artificial Intelligence (2023)Technological capabilities in the era of the digital economy for integration into cyber-physical systems and the IoT using decision-making approach (2023)AIMQ: a methodology for information quality assessment (2002)Model Cards for Model Reporting (2019)A Survey on Bias and Fairness in Machine Learning (2021)Data Quality in the Age of AI: A Review of Governance, Ethics, and the FAIR Principles (2025)Data Cleaning (2019)Can Foundation Models Wrangle Your Data? (2022)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)
this work references cited by second hop

References

  • n.d.Forecasting principles and practice4,364 cited
  • 2019DeepAR: Probabilistic forecasting with autoregressive recurrent networks2,726 cited
  • 2009Methodologies for data quality assessment and improvement1,294 cited
  • 2016Data Cleaning488 cited
  • 2017HoloClean477 cited
  • 2007Conditional Functional Dependencies for Data Cleaning379 cited
  • 2001Declarative Data Cleaning: Language, Model, and Algorithms320 cited
  • 2016M odel DB157 cited

Cited by

  • 2024On the Data Quality and Imbalance in Machine Learning-based Design and Manufacturing—A Systematic Review111 cited
  • 2021Data quality challenges in large-scale cyber-physical systems: A systematic review68 cited
  • 2025Data Readiness for AI: A 360-Degree Survey47 cited
  • 2020TensorFlow Data Validation: Data Analysis and Validation in Continuous ML Pipelines45 cited
  • 2019Deducing certain fixes to graphs41 cited
  • 2019Uni-Detect41 cited
  • 2019Risk-based data validation in machine learning-based software systems40 cited
  • 2022Data smells

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

38 cited
  • 2022Action-oriented process mining: bridging the gap between insights and actions24 cited
  • 2020From Data to Models and Back7 cited