AIMultiple ResearchAIMultiple ResearchAIMultiple Research

Data

Top No-Code ML Platforms: ChatGPT Alternatives in 2025

We benchmarked 4 no-code machine learning platforms across key metrics: data processing (handling missing values, outliers), model setup and ease of use, accuracy metrics output, availability of visualizations, and any major limitations or notes observed during testing.

Jun 106 min read

Top Open-Source Vector Databases: FAISS vs. Chroma & More

At AIMultiple, we develop and evaluate Generative AI technologies, including custom GPTs, AI agents, and cloud GPUs. A key enabler of these advancements is vector databases, which optimize high-dimensional data storage and retrieval for AI applications.

Apr 88 min read
Top 10 Data as a Service Companies in 2025

Top 10 Data as a Service Companies in 2025

Data fuels generative AI and enterprise innovation. Data as a Service (DaaS) is a cloud computing model that provides data on demand to users, usually on a subscription basis. This streamlines data collection and management.

Mar 246 min read

Data Transformation: Real-life examples & Best Practice

Data is the cornerstone in many sectors, underpinning decision-making processes in business, government, health, and more. The advent of generative AI has heightened the importance of data and its various applications. Organizations must understand and proficiently implement data transformation processes to unlock the full potential of it.

Jun 47 min read

Machine Learning in Data Integration: 8 Use Cases & Challenges

Integrating and analyzing data from disparate sources effectively has become paramount. Data integration often presents challenges, ranging from managing AI data quality to ensuring security. As organizations grapple with these obstacles, Artificial Intelligence (AI) and Machine Learning (ML) are emerging as transformative technologies, offering innovative solutions to simplify and enhance data integration processes.

May 275 min read

Data Quality in AI: Challenges, Importance & Best Practices

Poor data quality hinders the successful deployment of AI and ML projects. Even the most advanced AI algorithms can yield flawed results if the underlying data is of low quality. We explain the importance of data quality in AI, the challenges organizations encounter, and the best practices for ensuring high-quality data.

Jun 125 min read
Guide To Machine Learning Data Governance in 2025

Guide To Machine Learning Data Governance in 2025

In this article, we explain machine learning data governance. We explain its key principles, benefits, use cases, best practices, and our future expectations of data governance.

Jun 134 min read
7 Master Data Management Use Cases in 2025

7 Master Data Management Use Cases in 2025

In this article, we explain 7 master data management use cases. Master data management has been frequently searched since the 2020s.

Jul 235 min read

7 Key Data Fabric Use Cases in 2025

In this article, we explain 7 key data fabric use cases such as data integartion, data analytics, data governance, and data virtualization.

Jun 134 min read

Top 10 Data Center Automation Tools & Real-Life Case Studies

In this article, we will go over seven innovative data center automation tools.

Jun 138 min read