Web Scraping
Technically, whatever data that do exist over the internet can be scraped when required. This method is used by companies to extract useful data such as text, images, videos, and other valuable information to enhance productivity. Details could be customer reviews, surveys, polls, etc. Companies of every level (from small to large) are actively practicing this method (under a limitation as per law) and using certain tools and software for this method can simplify this process by handling data on large scale. When it’s all about data everywhere, web scraping has been in huge demand among data scientists.
If you don’t know about it, let’s read What is Web Scraping and How to Use It?
Some of the most popular tools used for data scraping are:
- BeautifulSoup: It’s a python library that is used by data science experts to extract and parse data from the websites directly to local or database. To get started with this library, you are required to install it using the terminal refer to this article: BeautifulSoup Installation
- Scrapy: Commonly used for data mining, and gathering useful content from any particular website as and when required. Besides the fact, that it was introduced back in 2008 for the purpose of web scraping but today, it is widely used for data extraction using APIs (such as AWS)
- Pandas: A python library that can be used to manipulate data for data extraction and can be exported in the form of Excel or CSV.
To read more about Web Scraping, refer to this article: “Web Scraping Tutorial with Python”
Top 7 Skills Required to Become a Data Scientist
For the past 5 years, data scientists have been one of the most desired and hottest jobs in the world. As soon as companies started realizing the importance of data in their businesses, the demand started growing in every sector. Today data science has become the core that supports businesses for analytics, mining or extraction, NLP, ML, AI, etc.
The decisions that they (businesses) take are now solely dependent on the proposed data (by data scientists or their relevant hierarchy) and they’re helping them (companies) to take helpful decisions. This has triggered the huge jump of such professionals over the past few years and is still dominating the industry. Due to this, the pay scale is pretty decent for data scientists and that’s one of the major reasons why people are paving their way toward this domain.
But the path to becoming a successful data scientist is not easy as it may sound, it requires a set of skills that companies do look for. To ace your career in this field, you’re required to master a handful of tools and languages along with statistical computations (besides strong communications and interpersonal skills). So, to help you with that let’s discuss the top 7 Skills Required to Become a Successful Data Scientist.