Events /

Watch On-Demand: Data Modeling Workshop with Cube

Learn how to design and implement the data model in your semantic layer with Cube

Key Takeaways from the Data Modeling Workshop

1. Data modeling with Python, YAML, and Jinja

The workshop focused on familiarizing data engineers and application developers with data modeling using Python, YAML, and Jinja. This approach allows for managing and connecting data sources and data-hungry applications at a centralized position in the data pipeline.

2. The Data-Centric Approach with Cube

Igor elaborated on the importance of understanding the difference between metric-centric and data-centric models. Using Cube's data-centric approach, engineers can logically view and correlate datasets to the Cube's data modeling layer entities. Distinctive tools such as dimensions (quantitative properties), measures (qualitative properties), and views (exposing subsets from specific cubes) provide a holistic approach to fetching, analyzing, and interpreting data.

3. Concept of Cubes in Data Modeling The webinar also dissected the concept of cubes, as described by Artyom. Cubes, the fundamental elements of Cube's data analytic layer, map directly to datasets. This mapping capability allows for more efficient, organized, and vertically integrated data processing, management, and utilization.

4. Cube's Data Modeling with Cube Cloud

The Cube Cloud demo onstage showcased the practical application of data modeling. Igor displayed the model folder with the data model graph, cubes, and views. The demo underscored that Cube definitions are expressed in YAML, emphasizing the ease and flexibility of adopting the Cube Cloud tool within their projects and businesses.

5. Data Read from Various Sources

Lastly, the workshop highlighted the versatility of Cube in managing and reading data from various sources: CSV and Parquet files, to name a few. With DuckDB set as the data source for the workshop, Artyom illustrated how the SQL property in the cubes definitions selected data from the S3 bucket. This capability to handle and manage diverse data sources underscores Cube's comprehensive approach to data management.

The webinar extensively showcased Cube's capabilities and offered learners a unique insight into data-centric modeling. Each part of the webinar was filled with practical examples and explanations that will allow attendees to apply these teachings to their perspective data modeling challenges. The workshop ended with a Q&A session, allowing the participants to delve deeper into the details of the Cube's data-centric approach. Attendees are encouraged to rewatch the workshop, which is now available on demand.