Should a digital marketer learn how to web crawl using Python? If yes, should he learn SQL next? If no, is there a better alternative or a reason no to pursue learning web crawling, Python, or SQL?

I never developed a web crawler (yet) so I can't help on that. But on the SQL side: if you already know the technology fine, otherwise if you have some knowledge of javascript you may want to try http://www.mongodb.org/ since it's easier to learn (for javascript developers). It has a Python library as well of course (http://docs.mongodb.org/ecosystem/drivers/python/).

I am always of the opinion that if one can, one SHOULD learn how to accomplish seminal tasks ones self.  Then you become a MASTER of your computer army. And Python and SQL are powerful tools well worth mastering.  Web crawling is also a very worthwhile talent to pursue.  So I absolutely can't fault you for investigating these tools, and I applaud your curiosity and determination. That having been said, there are easier ways to accomplish your information seeking goals which will not require you to learn Python and SQL.  For a quick and dirty solution which will accomplish your marketing requirements (though they will not give you the power and control and ancillary benefits of leaning Python and SQL), take a llok at: Yahoo Pipes Scrapy Mechanize BeautifulSoup Twill

Try Udacity "Intro to computer science", the first 1-3 units are dedicated on how to build a crawler using Python. I am on mobile otherwise would have posted link to the course.

If a significant amount of your work involves web crawling, and you have some familiarity with Python already, I would recommend using a framework like Scrapy [1] to scrape web pages. As for learning SQL, I don't think it's necessary in this case. Scrapy allows you to save data in a number of common formats including CSV and JSON without any additional code, and I can't think of any common scenarios where you would need to use a database if you aren't accessing the data programmatically. Alternatively, if you want to avoid writing code, you should look into using an annotation based scraping tool such as Portia [2]. Portia allows you to visually create templates of pages you want to extract by clicking on elements on the page and mapping them to fields. Portia will take the templates you created and will generate a spider to crawl similar pages on the website. See the video below for an idea of how Portia works. Scrapy Cloud [3] integrates Portia into its platform, so you can run the spiders you create from the dashboard and download the results when the crawling job is finished. Here's a post demonstrating how Portia works with Scrapy Cloud: http://blog.scrapinghub.com/2015/04/07/scrape-data-visually-with-portia-and-scrapy-cloud/ There are also other services such as importio [4] and Kimono [5] which let you scrape websites through a clean user interface. You can see some examples of how Kimono is used here: http://builtwith.kimonolabs.com/ [1] http://scrapy.org [2] https://github.com/scrapinghub/portia [3] http://scrapinghub.com/platform [4] http://import.io [5] https://www.kimonolabs.com Disclaimer: I work for Scrapinghub.