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Top 20 Synthetic Data Use Cases & Applications in 2025
Synthetic data offers solutions to common challenges in data science, including data privacy concerns and limited dataset sizes. Synthetic data is gaining widespread popularity and applicability across industries, including machine learning, deep learning, generative AI (GenAI), and large language models. We listed the capabilities and most common use cases of synthetic data in different industries and departments/business units.
Web Scraping with RPA: Tips and Techniques in 2025
Web scraping is the act of collecting data from websites to understand what information the web pages contain. The extracted data is used in multiple applications such as competitor research, public relations, trading, etc.
Top 10+ Workload Automation Use Cases in 2025
When asked, “Which automation technologies are the key drivers of enterprise digital transformation?” 47% of business and IT leaders identified workload automation (WLA) as their top choice, with robotic process automation (RPA) following closely behind.
Bot As A Service (Baas): What It Means And Platforms in 2025
Technology as a service represents the concept of delivering the benefits of technology to a business without on-premise existence of the tool or a long term investment.
Synthetic Data for Computer Vision: Benefits & Examples
Advancements in deep learning techniques have paved the way for successful computer vision and image recognition applications in fields such as automotive, healthcare, and security. Computers that can derive meaningful information from visual data enable numerous applications such as self-driving cars and highly accurate detection of diseases.
![Web Scraping for Machine Learning: From HTML to ML ['25]](https://research.aimultiple.com/wp-content/uploads/2021/08/machine-learning-web-scraping-190x143.png.webp)
Web Scraping for Machine Learning: From HTML to ML ['25]
~54.7 billion people around the world have been recorded to use the internet, creating 1.7MB of data every second. Crawling this exponentially growing volume of data could provide many opportunities for breakthroughs in data science.
6 Main Web Scraping Challenges & Practical Solutions ['25]
Web scraping, the process of extracting required data from web sources, is an essential tool in today’s data-centric world, yet it’s a technique fraught with challenges.
AI Fail: 4 Root Causes & Real-life Examples in 2025
Whether it’s a self-driving car crash, a biased algorithm, or a breakdown in a customer service chatbot, failures in deployed AI systems can have serious consequences and raise important ethical and societal questions.
Web Scraping for Recruiters: Top Tools & Techniques [2025]
Bright Data’s Data collector automatically extracts publicly available data from LinkedIn for recruiters.
Web Scraping for Finance in 2025: Top Tools & Pricing
Scraping tools for finance can be divided into four types based on your programming expertise and the scope of your project: What are the best tools for extracting financial data? Table features explained: What kind of financial data can be collected via web scrapers? Below are various types of data that can be extracted using