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Voxxed Days Ioannina 2024 - Data warehousing reinvented for today's needs
Explore the evolution of data warehousing and learn how to gain insights from large datasets with AWS Glue and Redshift.
- Data warehousing is evolving to meet modern needs, including addressing data variety, velocity, and veracity.
- AWS Glue is a fully managed extract, transform, and load (ETL) service that can handle large datasets and scale automatically.
- Redshift is a data warehouse solution that allows for fast querying and analysis of large datasets.
- Data engineers can write code in Python or Scala, while data analysts can use a visual interface to prepare data without writing code.
- ETL jobs can be created using AWS Glue Studio, which provides a visual interface for designing ETL workflows.
- Data can be loaded into Redshift from various sources, including S3, DynamoDB, and Amazon Aurora.
- AWS Glue provides a data catalog that allows for easy discovery and querying of data.
- Data warehousing can be used to gain insights from large datasets, such as predicting customer behavior and identifying trends.
- Modern data warehouses must address the challenges of big data, including data variety, velocity, and veracity.
- AWS provides a range of tools and services for building and managing data warehouses, including Redshift, Glue, and QuickSight.
- Data warehousing can be used to support business intelligence and analytics, such as reporting and dashboards.
- AWS provides a scalable and secure infrastructure for data warehousing, with features such as automatic scaling and encryption.
- Data engineers can use AWS Glue to automate ETL workflows and scale data processing to meet changing demands.
- Data analysts can use AWS QuickSight to create interactive dashboards and reports without writing code.
- Data warehousing can help organizations make better decisions by providing insights from their data.