Data Engineering, Preparation, and Labeling for AI 2019

Abstract: It has always been the case that garbage in is garbage out in computing, but 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.  
Premium PDF. Source: Copyright © Cognilytica LLC   Key Vendors Included in this Report:
  • CloudFactory
  • Figure Eight
  • iMerit
  • Melissa Data
  • Paxata
  • Trifacta
Report Details:
  • 24 Pages
  • 14 Charts
Table of Contents
  • Table of Contents
  • Executive Summary 2
    • Key Findings 2
  • Market Overview 3
    • Defining the Problem 3
      • Data Engineering 4
      • Data Preparation 5
        • AI-Relevant Data Preparation Solution Requirements 6
        • Data Preparation Use Cases 6
      • Data Labeling 6
        • Data Labeling Solution Provider Requirements 7
        • Data Labeling Use Cases 9
  • Cognilytica AI Vendor Classification 9
    • About the Cognilytica Vendor Classification System 10
  • Global Market Size for Data Preparation 10
  • Key Vendors 12
    • Key Data Preparation Vendors 12
      • Melissa Data 12
      • Paxata 14
      • Trifacta 16
    • Key Data Labeling Vendors 17
      • CloudFactory 17
      • Figure Eight 19
      • iMerit 20
    • Notes on Vendor Inclusion 22
  • Future Market Trends and Predictions 22
    • Data Preparation Market Predictions and Trends 22
    • Data Labeling Market Predictions and Trends 23
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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