Data Labeling Market: Research Snapshot Dec. 2021



In order for machine learning systems to be able to create accurate generalizations, they must be trained on data. Advanced forms of machine learning, especially deep learning neural networks, require significant volumes of data to be able to create models with desired levels of accuracy. Customers often don’t have the resources to label large data sets, nor do they have a mechanism to ensure accuracy and quality of data labeling. Labeling projects involve multiple steps as well as requiring human subjective decision making. Third party managed labeling solution providers and an increasing rate of data labeling tools address this gap by providing the labor to do the labeling combined with tools & expertise in large-scale data labeling efforts and an infrastructure for managing labeling workloads and achieving desired quality levels. In this latest snapshot of Cognilytica Market Intelligence, Cognilytica evaluates data labeling solutions across key market segments that provide needed annotations for machine learning training.

In this Research Snapshot of Cognilytica’s Market intelligence, we cover:

  • The Data Labeling Market Overview
  • Data Labeling market segments:
    • Crowdsourced Data Labeling
    • Managed Labeling Services
    • Full Service Data Labeling Solutions
    • Labeling Tools & Software
    • Synthetic Data Labeling
  • Data Labeling Market Forecasts and Trends across all market segments
  • Data Labeling Vendor Profiles covering 133 vendors with detailed profiles on “established” vendors
  • Decision Factors for Buyers of Data Labeling Solutions
  • Guided Questions to help Buyers interact with Data Labeling vendors
Statement of Opinion & Terms and Conditions of Sale
Although Cognilytica believes that the results, conclusions, and analysis produced in support of this report are well informed, comprehensive, and reasonable, Cognilytica cannot guarantee future results, accuracy of market predictions, or applicability of conclusions to report purchaser or reader’s business. Moreover, Cognilytica does not assume responsibility for the accuracy and completeness of such statements. The information derived in this report are statements of opinion only, and Cognilytica shall not be held liable in any manner for any conclusions or actions taken pursuant to this report. The information contained herein has been obtained from sources believed to be reliable. Cognilytica shall have no liability for errors, omissions, or inadequacies in the information contained herein or for interpretations thereof. Report purchaser and/or reader assumes sole responsibility for the selection of these materials to achieve its intended results. The opinions expressed herein are subject to change without notice. Cognilytica does not make open its research methods, underlying data, sources, or means and methods of analysis for inquiry, evaluation, or examination.

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