{"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":"

Business challenge<\/h2>\n

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

\"Automated<\/p>\n

Solution delivered<\/h2>\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>\n

After that, the data acquisition system triggers a validation algorithm to filter inappropriate data. This algorithm contains a level powered by NLP technology<\/a> to process the most difficult cases.<\/p>\n

Data normalization is performed using Google Maps and Location Services APIs.<\/p>\n

Finally, the system stores the data, aggregates it, and molds it into a highly consumable format for further analysis.<\/p>\n

Business outcome<\/h2>\n

As a result of their partnership with Intellias, our client has enhanced their data analytics and asset intelligence, which are a valuable part of their real estate solutions. The automated tools and techniques for data acquisition that Intellias developed help our client optimize their data acquisition strategy. They can now acquire a greater volume of data and from a larger number of sources with no need for increased resources.<\/p>\n

With data acquisition system, our client can easily produce insights by turning unstructured data into meaningful data points that have great potential to unlock new business opportunities.<\/p>\n","protected":false},"excerpt":{"rendered":"

We\u2019ve enhanced our client\u2019s data acquisition strategy with a framework comprising data scraping, validation, normalization, and storage<\/p>\n","protected":false},"author":17,"featured_media":50268,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[5],"tags":[75,84],"class_list":["post-29256","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-case-study","tag-data-analytics","tag-real-estate","technologies-bigquery","technologies-chromedp","technologies-gcp","technologies-go-colly","technologies-golang"],"acf":[],"yoast_head":"\nData Acquisition Strategy for a PropTech Innovator<\/title>\n<meta name=\"description\" content=\"Read a case study about data acquisition software, which Intellias team developed to enhance the client\u2019s data analytics and asset intelligence.\" \/>\n<meta name=\"robots\" content=\"index, follow, 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