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Top 20+ Synthetic Data Use Cases in 2025
Synthetic data offers solutions to challenges such as data privacy concerns and limited dataset sizes. Synthetic data is gaining widespread popularity and applicability across industries, including machine learning, deep learning, and generative AI (GenAI). It is estimated that synthetic data will be preferred over real data in AI models by 2030.
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. Web scraping is not an illegal act.
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): Definition & Platforms in 2025
Technology as a service delivers tech benefits to businesses without on-premise tools or long-term investments. BaaS providers let businesses use chatbots or RPA bots on a pay-as-you-go basis, avoiding licensing and extensive training. Bot-as-a-Service (BaaS) has been gaining popularity, and businesses that adapt will have increasing advantages over those that don’t.
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 Web Scraping Challenges & Practical Solutions in 2025
Web scraping, the process of extracting required data from web sources, is an essential tool; however, it is a technique fraught with challenges. See below the most common web scraping challenges and practical solutions to address them.
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.
Scraping Financial Data Without Coding in 2025
While official financial data providers do offer APIs, these are often limited in scope, access, or flexibility especially for real-time or niche data needs. As a result, financial data scraping has become a common approach to collecting such information, typically using technologies like web scrapers, headless browsers, and HTML parsers.