{"id":29256,"date":"2020-12-03T12:04:08","date_gmt":"2020-12-03T11:04:08","guid":{"rendered":"https:\/\/www.intellias.com\/?p=29256"},"modified":"2022-11-27T22:18:05","modified_gmt":"2022-11-27T21:18:05","slug":"data-acquisition-for-a-proptech-innovator","status":"publish","type":"post","link":"https:\/\/intellias.com\/automated-data-acquisition\/","title":{"rendered":"Automated Data Acquisition for a PropTech Innovator"},"content":{"rendered":"
Our client provides technology and data science solutions to real estate investors and leading financial institutions worldwide. As the company specializes in advanced data analytics<\/a> and asset intelligence, its business model relies significantly on data acquisition.<\/p>\n Our client\u2019s platform captures massive data sets, consolidates all available information, and transforms unstructured data into business insights. To do this, our client\u2019s company needed to reimagine traditional methods of data acquisition strategy and enhance the processing of large data sets. To that end, they decided to scale the capacity of their data science team with dedicated data acquisition specialists.<\/p>\n <\/p>\n The Intellias team started off by analyzing our client\u2019s current data acquisition strategy to reveal best practices and bottlenecks. Based on the results, we developed a framework as a preliminary solution for acquiring, accumulating, and storing data in a data lake. This framework works for web pages and APIs.<\/p>\n The data acquisition software comprises two types of scraping algorithms: basic and emulated. Based on Chromedp technology, the emulated scraping algorithm imitates the activity of a real user to get relevant and valid data. Next, CSS selectors find and retrieve the needed data from websites.<\/p>\nSolution delivered<\/h2>\n