This case study shows how iWeb Data Scraping has helped a financial company with its web scraping requirements.
A financial research company having investment options requires real-time financial data feeds.
The client must blend social and market data to create a financial recommendation, which could provide proprietary signals about systematic equity investment. It had the subscribed audience based on which that might send the trading signals every day. The company needed all the probable data from finance to run the solution, which was hot in the news, articles, blogs, or on social media. This data might help the intelligence the client was internally building to generate final outputs on a customized basis. The scale was the main attribute in the picture as the total sources associated were massive, with a range of over 30,000 websites! Data availability and coverage were essential for the given vitality of the financial market.
iWeb Data Scraping DaaS platform, with its vast scale and lower-latency crawling offering, was utilized to address the problem. The system was used to fit at this scale and adaptively scrape sources depending on the ones who were active against the latent ones. Alerts were used to notify dead resources so that crawling results were precise and the entire system became more effective. Some components were added to address lower latency requirements within 5 to 10 minutes, which might live up to multiplication power. The scraped data got indexed with hosted indexing components, and a search API was given that the client might query in a few minutes to get the results. The last results were presented in JSON format.
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