Data Data Data!

Data serves as the foundation for any project. When embarking on a new project, acquiring the right data can be an exhilarating experience, akin to a thrilling roller coaster ride (albeit without the physical motion). In today's session, we will delve into some of the most effective approaches employed by Data Scientists worldwide to obtain high-quality data for their work. By exploring these methods, you will gain valuable insights into the best practices for acquiring data and setting yourself up for success in your projects.

What is data?

Data simply can be defined as raw facts and figures that have implicit meaning(s) and can be used for analytical and/or other purposes.

Ways to get big data:

• Questionnaires
• Surveys
• Web Scraping
• Downloading from available sources i.e (**Kaggle, data.gov)**

I will omit discussing questionnaires and surveys since I assume you already possess a basic understanding of these concepts. In case you need more information, a quick Google search will provide you with ample resources. Today's focus will be on two specific methods of data collection: Web Scraping and Kaggle. These techniques offer valuable avenues for gathering data, and we will explore them in detail during our session.

Web Scraping

Here is an article on data scraping with Python and excel that explains how to scrape data easily.

Web Scraping with MS Excel and Python: Static Site Contents.

Kaggle