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The business value of any web extraction project relies not only on data but on quality data. Given the importance of quality in determining the value of the whole project and justifying the use of company resources, we brought two Data Quality specialists together to show us how early QA starts in any web scraping project and how.
Learn how to evaluate the data's accuracy, completeness, consistency, and timeliness, and get helpful tips on regularly monitoring the crawlers for quick identification and resolution of any issues that may arise.
That’s what’s covered in the fourth episode of the 5-part webinar series On-demand Guide to Accessing Web Data, brought to you by Zyte and its host Neha Setia, Web Data Evangelist, and a body of public data extraction specialists around the globe.
How the right definition of data quality can improve the QA process.
When to use automation tools like the open-source Spidermon to track spiders’ quality.
Best practices to detect and avoid issues.
Post-development and post-processing ideas to ensure data quality.
Pierluigi Vinciguerra, Co-Founder, and CTO at Re Analytics - Databoutique.com
Artur Sarduski - Data Scientist at Zyte
Neha Setia Nagpal - Web Data Evangelist at Zyte