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Data quality: Experiences and lessons from operationalizing big data

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1038/nature14539openalex-snapshot
Deep learning
inferredcites →https://doi.org/10.1109/tpami.2008.277openalex-snapshot
Convex and Semi-Nonnegative Matrix Factorizations
inferredcites →https://doi.org/10.1109/tvcg.2012.219openalex-snapshot
Enterprise Data Analysis and Visualization: An Interview Study
inferredcites →https://doi.org/10.1111/j.2517-6161.1951.tb00088.xopenalex-snapshot
The Interpretation of Interaction in Contingency Tables
inferredcites →https://doi.org/10.1111/rssb.12050openalex-snapshot
A Scalable Bootstrap for Massive Data
inferredcites →https://doi.org/10.1145/1165389.945450openalex-snapshot
The Google file system
inferredcites →https://doi.org/10.1145/1272996.1273005openalex-snapshot
Dryad
inferredcites →https://doi.org/10.1145/1294261.1294281openalex-snapshot
Dynamo
inferredcites →https://doi.org/10.1145/1327452.1327492openalex-snapshot
MapReduce
inferredcites →https://doi.org/10.1145/1807167.1807184openalex-snapshot
Pregel
inferredcites →https://doi.org/10.1145/2043556.2043566openalex-snapshot
CryptDB
inferredcites →https://doi.org/10.1145/2465351.2465355openalex-snapshot
BlinkDB
inferredcites →https://doi.org/10.1145/2517349.2522737openalex-snapshot
Discretized streams
inferredcites →https://doi.org/10.1145/2670979.2670985openalex-snapshot
Tachyon
inferredcites →https://doi.org/10.1145/2882903.2912574openalex-snapshot
Data Cleaning
inferredcites →https://doi.org/10.1145/2939502.2939511openalex-snapshot
Towards reliable interactive data cleaning
inferredcites →https://doi.org/10.1145/872757.872875openalex-snapshot
Data quality and data cleaning
inferredcites →https://doi.org/10.1145/945449.945450openalex-snapshot
The Google file system
inferredcites →https://doi.org/10.14778/2212351.2212354openalex-snapshot
Distributed GraphLab
inferredcites →https://doi.org/10.1561/1900000045openalex-snapshot
Trends in Cleaning Relational Data: Consistency and Deduplication
inferredcites →https://doi.org/10.1561/9781680830231openalex-snapshot
Trends in Cleaning Relational Data: Consistency and Deduplication
inferredcites →https://doi.org/10.2307/1268828openalex-snapshot
Robust Regression and Outlier Detection
inferredcites →https://doi.org/10.2307/2289958openalex-snapshot
Robust Regression and Outlier Detection.
inferredcites →https://doi.org/10.48550/arxiv.1603.04467openalex-snapshot
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.3097911openalex-extracted
The Effective Use of Analytics in Public Administration: The Australian Taxation Office Experience
inferred← citeshttps://doi.org/10.1007/978-981-99-5142-0_8openalex-snapshot
Comparing Critical Factors for Big Data Analytics (BDA) Adoption Among Malaysian Manufacturing and Construction SMEs
inferred← citeshttps://doi.org/10.1109/bigdata.2017.8258015openalex-snapshot
Data context informed data wrangling
inferred← citeshttps://doi.org/10.20396/rdbci.v16i1.8650412openalex-snapshot
A produção científica sobre qualidade de dados em big data
inferred← citeshttps://doi.org/10.2196/19612openalex-snapshot
Amplifying Domain Expertise in Clinical Data Pipelines
inferred← citeshttps://doi.org/10.55640/ijdsml-03-01-01aopenalex-snapshot
The Role of Multi-Domain MDM in Modern Enterprise Data Strategies
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.