Sponsor: oxylabs.io

Businesses increasingly prefer data-driven decision-making, leaving intuition-based decisions to lesser tasks. Today, artificial intelligence (AI) can locate and extract data from unstructured sources with nearly 95% accuracy. And yet, most organizations struggle to analyze the ocean of data they collect, as nearly 90% of data is unstructured or has no defined schema.

With competitive intelligence (CI), businesses can connect data collection and analysis capabilities into a single system bringing all the existing know-how and adopting it in-house.

CI practices yield a range of transformational changes that fuel growth with areas of impact found at all levels of an organization.

Whereas manual rule-based data extraction is a long and tedious process, the introduction of AI enabled maintenance-free approaches. Besides its primary purpose of data extraction for business insights, web scraping is also used to accumulate training material for AI-based adaptive parsing.

With the help of machine learning models, AI-assisted web scrapers can retrieve and process content from hundreds of thousands of pages in seconds to generate business strategies and forecasts without being explicitly programmed to do so.

This white paper provides a comprehensive overview of how AI and its subfield, machine learning, shape the current trends in web data extraction and processes that precede it. AI assistance is just as valuable in bypassing anti-scraping measures (such as in our own Web Unblocker) as it is instrumental in the subsequent data structuring.

Cyber threats are increasingly becoming a huge issue in the digital world. Malicious entities find various ways to access sensitive companies’ or individual data. Data breaches, phishing, social engineering, malware, ransomware, and many more threats are evolving rapidly and becoming more dangerous every year.

Understanding the seriousness of cyber threats and taking action to fight against them is a massive step toward a safer digital environment. One of the cybersecurity practices that modern companies use to avoid potential dangers is threat intelligence.

Threat intelligence enables businesses to make faster and data-backed security decisions and be proactive in the fight against threat actors.

The automation of price monitoring is the only way to stay on top of the price intelligence challenges. Either keeping up with price changes, uncovering competitor strategies, or observing historical pricing data, price monitoring reveals applicable business patterns that catalyze growth.

This white paper provides an action chain for price monitoring, from collecting target URLs to data parsing, along with tips and explanations on the most important elements and processes.