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Top 10 Training Data Platforms of 2024: In-depth Guide

Cem Dilmegani
Updated on Jan 13
1 min read

Data is an essential part of the decision-making processes in today’s enterprises. Supervised AI/ML models require high-quality data to make accurate predictions. Training data platform tools ensure effective use of data processing from start to finish of ML deployment.

What are training data platforms?

Training data platforms are software that automates the following processes for companies:

  • Labels Data: Training supervised ML models requires processes such as image, text, and audio annotations. Training data platforms provide automated labeling for enterprises.
  • Diagnostics: Training data platforms identify model errors and understand performance trends that help the IT team monitor models.
  • Prioritize: It is not optimal for organizations to spend time on labeling poor quality data. Training data platforms determine the most effective use of data.

Why are training data platforms important?

McKinsey argues that data-related issues are the biggest struggle in developing effective ML models. In this regard, training data platforms that provide solutions for reaching high-quality data directly impact the competitiveness of companies.

What are some examples of training data platforms?

Here is a list of the top ten training data labeling platforms:

Name of ToolOpen or Closed Source
Anaconda EnterpriseOpen
Databricks Unified Analytics PlatformOpen
Google Cloud AI PlatformClosed
H2O Driverless AIClosed
IBM Watson StudioOpen
Microsoft Azure Machine LearningOpen
SAS Visual Data Mining and Machine LearningOpen

You can check our Labeling/Annotation/Classification vendors, Top 10 Open Source Data Labeling Platforms and Top 20 Data Labeling Tools lists.

If you need help for choosing the right vendor that will improve your data quality, contact us:

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Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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