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.

Key takeaways

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.

Voxxed Days Ioannina 2024 - Data warehousing reinvented for today's needs

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