Sessions are categorized to help you find the technical level you are looking for. Mild sessions are less technical, while spicy sessions are very technical.
Data warehouses have commonly been built on relational databases which are optimized for transactional work loads. The performance and storage limitations of these systems required special data models such as star schemas. The latest wave of column-based data stores such as AWS Redshift are optimized for analytical work loads and no longer require these compromises to perform. Redshift also has an extensive group of partners which provide solutions to ease the loading, transformation and visualization of the source data. This presentation will examine a case study of how Field Nation built a data warehouse and financial dashboards in three months using Redshift. We will look at the tools in the data pipeline from data extraction to delivery. By the end of the presentation you will have a new understanding of how to turn both in-house and SaaS provider data into a coherent whole for your users.
