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Context-aware Big Data Quality Assessment: A Scoping Review
16 references·1 citing·40 second hop
Context-aware Big Data Quality Assessment: A Scoping Review (2023)Context-aware Big Data Quality Assessment…Uncertainty in big data analytics: survey, opportunities, and challenges (2019)Uncertainty in big data analy…Data lake management (2019)Data lake managementData Cleaning (2019)Data CleaningAn Overview of Data Quality Frameworks (2019)An Overview of Data Quality F…Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach (2018)Systematic review or scoping …Automating large-scale data quality verification (2018)Automating large-scale data q…Machine Learning With Big Data: Challenges and Approaches (2017)Machine Learning With Big Dat…Machine learning on big data: Opportunities and challenges (2017)Machine learning on big data:…The Challenges of Data Quality and Data Quality Assessment in the Big Data Era (2015)The Challenges of Data Qualit…Reference Architecture and Classification of Technologies, Products and Services for Big Data Systems (2015)Reference Architecture and Cl…Deep learning applications and challenges in big data analytics (2015)Deep learning applications an…Data quality: The other face of Big Data (2014)Data quality: The other face …Data quality assessment (2002)Data quality assessmentA product perspective on total data quality management (1998)A product perspective on tota…Data quality in context (1997)Data quality in contextBeyond Accuracy: What Data Quality Means to Data Consumers (1996)Beyond Accuracy: What Data Qu…An Automated Big Data Quality Anomaly Correction Framework Using Predictive Analysis (2023)An Automated Big Data Quality…Out of the Crisis (1982)Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation (1991)Information Systems Success: The Quest for the Dependent Variable (1992)AIMQ: a methodology for information quality assessment (2002)Anchoring data quality dimensions in ontological foundations (1996)Modeling Information Manufacturing Systems to Determine Information Product Quality (1998)Information quality benchmarks (2002)Benefits, Adoption Barriers and Myths of Open Data and Open Government (2012)Data governance: Organizing data for trustworthy Artificial Intelligence (2020)Beyond the hype: Big data concepts, methods, and analytics (2014)Big Data Deep Learning: Challenges and Perspectives (2014)A survey towards an integration of big data analytics to big insights for value-creation (2018)Big Data Analytics in Building the Competitive Intelligence of Organizations (2020)A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts (2022)Big data: The next frontier for innovation, competition, and productivity (2011)Data-intensive applications, challenges, techniques and technologies: A survey on Big Data (2014)ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module (2018)Social media big data analytics: A survey (2018)Forecasting: theory and practice (2022)Scoping studies: towards a methodological framework (2005)The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration (2009)PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation (2018)Updated methodological guidance for the conduct of scoping reviews (2020)Updated methodological guidance for the conduct of scoping reviews (2021)Recommendations for the extraction, analysis, and presentation of results in scoping reviews (2022)Fuzzy sets (1965)Fuzzy sets (1996)Comprehensive review of text-mining applications in finance (2020)Digital Transformation and SMART-The Analytics factor (2022)A review of predictive uncertainty estimation with machine learning (2024)Addressing big data issues in Scientific Data Infrastructure (2013)Big data: Issues, challenges, tools and Good practices (2013)Leveraging internet of things and big data analytics initiatives in European and American firms: Is data quality a way to extract business value? (2019)How to address data privacy concerns when using social media data in conservation science (2021)E-government success factors: Mapping practical tools to theoretical foundations (2005)Consumer trust, perceived security and privacy policy (2006)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)Methodologies for data quality assessment and improvement (2009)A systematic review of open government data initiatives (2015)Big Data technologies: A survey (2017)
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References

  • 2018Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach11,351 cited
  • 1996Beyond Accuracy: What Data Quality Means to Data Consumers4,663 cited
  • 2015Deep learning applications and challenges in big data analytics2,597 cited
  • 2002Data quality assessment1,724 cited
  • 1997Data quality in context1,298 cited
  • 2017Machine learning on big data: Opportunities and challenges1,234 cited
  • 2017Machine Learning With Big Data: Challenges and Approaches1,023 cited
  • 2015The Challenges of Data Quality and Data Quality Assessment in the Big Data Era1,015 cited
  • 1998A product perspective on total data quality management911 cited
  • 2019Uncertainty in big data analytics: survey, opportunities, and challenges618 cited
  • 2014Data quality: The other face of Big Data262 cited
  • 2019Data lake management253 cited
  • 2018Automating large-scale data quality verification245 cited
  • 2019An Overview of Data Quality Frameworks244 cited
  • 2015Reference Architecture and Classification of Technologies, Products and Services for Big Data Systems241 cited

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2019
Data Cleaning
199 cited

Cited by

  • 2023An Automated Big Data Quality Anomaly Correction Framework Using Predictive Analysis27 cited