- 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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The STAR Market, as is implied by the name, is heavily geared toward smaller innovative tech companies, in particular those engaged in strategically important fields, such as biopharmaceuticals, 5G technology, semiconductors, and new energy. The STAR Market currently has 340 listed securities. The STAR Market is seen as important for China’s high-tech and emerging industries, providing a space for smaller companies to raise capital in China. This is especially significant for technology companies that may be viewed with suspicion on overseas stock exchanges.
Importantly, that investor viewpoint is not new. It cycles in when conditions are right (and vice versa). It also brings the ineffective warnings of an overpriced market with it.Looking toward a good 2022 stock market, there is no apparent reason to expect these issues to change.
