- 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
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Telegram hopes to raise $1bn with a convertible bond private placement
The super secure UAE-based Telegram messenger service, developed by Russian-born software icon Pavel Durov, is looking to raise $1bn through a bond placement to a limited number of investors from Russia, Europe, Asia and the Middle East, the Kommersant daily reported citing unnamed sources on February 18, 2021.The issue reportedly comprises exchange bonds that could be converted into equity in the messaging service that is currently 100% owned by Durov and his brother Nikolai.Kommersant reports that the price of the conversion would be at a 10% discount to a potential IPO should it happen within five years.The minimum bond placement is said to be set at $50mn, but could be lowered to $10mn. Five-year bonds could carry an annual coupon of 7-8%.
