Hive vs Iceberg Tables in AWS Athena
Choosing the Best Option for Your Data Pipelines with dbt
More and more organizations are switching from traditional data warehouses to a modern data platform, serverless and without using databases. The traditional data warehouses lack the ability to add semi-structured and unstructured data, and SQL databases do not allow for a cost-optimized setup. And while decoupling data storage and processing is a good thing by itself, it adds significant complexity and unwanted delays because data is copied from one component to another.
In this training
After this training
This training is for
Business Analytics
Full day
750
Mechelen
Choosing the Best Option for Your Data Pipelines with dbt
Envision a situation where you're tasked with managing clickstream data received via Snowplow. In this blog post, we'll guide you through our solution, step by step.
As much as off-the-shelf Customer Data Platforms promise to offer a click-and-play solution, they cannot magically crack every intricate data engineering challenge.
Let’s dive into how we troubleshooted such performance issues and how Hyperscale came to the rescue.