Data Preparation & Labeling for AI 2020



Document ID: CGR-DLP20 | Last Updated: Jan. 31, 2020

Report Overview

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:

  • The market for AI and machine learning relevant data preparation solutions is over $1.5B in 2019 growing to $3.5B by the end of 2024.
  • Data preparation and engineering tasks represent over 80% of the time consumed in most AI and Machine Learning projects.
  • The market for third-party Data Labeling solutions is $1.7B in 2019 growing to over $4.1B by 2024.
  • An increasingly greater amount of workload requirements are becoming more domain-specific in nature as machine learning tasks become increasingly more specialized
  • The increasing proliferation of pre-trained models and models-as-a-service will move an increasing amount of data labeling to automation over time or shift humans to more complex tasks,
  • AI projects relating to object / image recognition, autonomous vehicles, and text and image annotation are the most common workloads for data labeling efforts.
  • Within the next two years, all competitive data preparation tools will have machine learning augmented intelligence as a core part of the offering.
  • By 2024, over30% of current labeling tasks will be automated or performed by AI systems. However, the human in the loop is not going away any time soonfor labeling and quality control.

Key Vendors Included in this Report:

  • AI Data Innovations
  • Alegion
  • Altair Knowledge Works (formerly DataWatch)
  • Alteryx
  • Amazon Mechanical Turk
  • Amazon Sagemaker Ground Truth
  • Appen
  • CapeStart
  • Clay Sciences
  • ClickWorker
  • CloudFactory
  • CloverDX
  • Dataloop
  • DataMeer
  • Datapure
  • DataTurks
  • DataWatch
  • Deep Vision Data
  • Defined Crowd
  • Figure Eight
  • (Acquired by Lionbridge)
  • Heartex
  • Hitachi Vantara (Pentaho)
  • Hive
  • Hivemind
  • iMerit
  • Labelbox
  • Lionbridge
  • Melissa
  • Mighty AI
  • Paxata (Acquired by DataRobot)
  • Playment
  • Q Analysts
  • Samasource
  • Scale AI
  • Supahands
  • Superannotate
  • Supervisely
  • Talend
  • Tamr
  • Taskware
  • Trifacta
  • Welocalize

Report Details:

  • 37 Pages
  • 3 Tables
  • 18 Charts

[wpdm_package id=’6217′]

Price: $995

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 7
    • Data Labeling and Annotation Use Cases 8
    • Data Labeling Solution Provider Requirements 9
    • Data Labeling Solution Provider Considerations 10
    • Use of Automation and Machine Learning in Data Labeling 11
    • Cognilytica Classification 13
      • About the Cognilytica Vendor Classification System 13
  • Market Size Estimates and Growth Projections 14
    • Data Preparation Market Size and Growth Projections 14
    • Data Labeling Market Size and Growth Projections 15
    • Data Labeling Vendor Landscape 16
  • Key Vendors 17
    • Data Preparation Vendors 17
    • Data Preparation Vendor Profiles 17
    • Data Labeling Vendors 22
    • Data Labeling Vendor Profiles 22
    • Notes on Vendor Inclusion 33
  • Future Market Trends and Predictions 34
    • Data Preparation Market Predictions and Trends 34
    • Data Labeling Market Predictions and Trends 34
    • Related Research 35
  • About Cognilytica 35
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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