- Understand how data engineering supports data science workflows - Discover how to extract data from files and databases and then clean, transform, and enrich it - Configure processors for handling different file formats as well as both relational and NoSQL databases - Find out how to implement a data pipeline and dashboard to visualize results - Use staging and validation to check data before landing in the warehouse - Build real-time pipelines with staging areas that perform validation and handle failures - Get to grips with deploying pipelines in the production environment
- Understand how data engineering supports data science workflows - Discover how to extract data from files and databases and then clean, transform, and enrich it - Configure processors for handling different file formats as well as both relational and NoSQL databases - Find out how to implement a data pipeline and dashboard to visualize results - Use staging and validation to check data before landing in the warehouse - Build real-time pipelines with staging areas that perform validation and handle failures - Get to grips with deploying pipelines in the production environment
BY Python 🐍 Work With Data
Warning: Undefined variable $i in /var/www/tg-me/post.php on line 283
The S&P 500 slumped 1.8% on Monday and Tuesday, thanks to China Evergrande, the Chinese property company that looks like it is ready to default on its more-than $300 billion in debt. Cries of the next Lehman Brothers—or maybe the next Silverado?—echoed through the canyons of Wall Street as investors prepared for the worst.
What is Telegram?
Telegram is a cloud-based instant messaging service that has been making rounds as a popular option for those who wish to keep their messages secure. Telegram boasts a collection of different features, but it’s best known for its ability to secure messages and media by encrypting them during transit; this prevents third-parties from snooping on messages easily. Let’s take a look at what Telegram can do and why you might want to use it.
