Document ID: CGR-DLP20 | Last Updated: Jan. 31, 2020
| Report Overview | ||
| Abstract: Garbage in is garbage out in computing, and it is especially the case with regards to machine learning data. In this report, Cognilytica evaluates the requirements for data preparation solutions that aim to clean, augment, and otherwise enhance data for machine learning purposes, data engineering solutions that aim to give organizations a way to move and handle large volumes of data, and data labeling solutions that aim to augment data with the required annotations that are necessary to be used in machine learning training models. This report is an update to the previous research (CGR-DE100) concluded in 2019 with new data, vendors, and updates to market sizing and segmentation. Key Findings:
Key Vendors Included in this Report:
Report Details:
Data Preparation & Labeling for AI 2020 [CGR-DLP20] 1.75 MBGarbage in is garbage out in computing, and it is especially the case with regards... |
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| Table of Contents | ||
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Data Preparation & Labeling for AI 2020 [CGR-DLP20] 1.75 MBGarbage in is garbage out in computing, and it is especially the case with regards... | ||
| 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. | ||

