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Özge Aykaç

Özge Aykaç

Industry Analyst
35 Articles
Stay up-to-date on B2B Tech
Özge is an industry analyst at AIMultiple focused on data loss prevention, device control and data classification.

She is a member of the AIMultiple DLP benchmark team and evaluates the effectiveness of the top DLP providers.

Latest Articles from Özge

DataJun 27

Top 6 Data Collection Methods for AI and Machine Learning

While some companies rely on AI data collection services, others gather their data using scraping tools or other methods. See the top 6 AI data collection methods and techniques to fuel your AI projects with accurate data: Overview of AI data collection methods 1. Crowdsourcing Online talent platforms, such as crowdsourcing platforms, have various benefits.

DataJun 18

10-Point Retail Audit Checklist with Case Studies in 2026

Retail audits are essential for consumer product goods (CPG) or fast-moving consumer goods (FMCG) companies to ensure success at their retail end. While some brands use retail and planogram audit services, others handle these audits internally. This article presents a 10-point checklist to help CPG brands in executing comprehensive retail audits.

DataJun 16

10 Open Source Data Labeling Platforms

Data labeling, the process of annotating raw data (such as images, text, or audio), is essential for training ML models to perform tasks like classification and recognition. While pre-built solutions exist, they may not always meet specific needs, making open-source platforms a more flexible and customizable alternative. See the top 10 open-source data labeling tools.

Enterprise SoftwareJun 16

12 Digital Transformation Trends & Use Cases in Education

The COVID-19 pandemic has accelerated digital transformation in education as nearly 1.5 billion students worldwide became distanced from their classrooms. However, online education is not the only way digital technologies transform the teaching and learning experience. We explore how digital transformation affects education with key technologies and trends.

DataMay 21

Human Generated Data with Methods in 2026

Despite the rise of generative AI tools like ChatGPT and Gemini, human-generated data remains crucial for AI developers. Companies like OpenAI invest heavily in obtaining human-generated data to train their large language models (LLMs). Whether through data collection services or in-house efforts, AI developers require a steady stream of human-generated data.

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