Data modeling is a key component of any analytical or operational data processing initiative. It’s critical to how data is both processed and governed in areas such as gaining data insights, data quality management, and data literacy. The most succinct description of Data Modeling (in my opinion) is as David C. Hay states:

“We model data to provide a (usually graphical) representation of a set of data in a domain”.

Data modeling can be used in conjunction with the workloads that the Snowflake Data Cloud powers, such as : 

Snowflake specific considerations

Irrespective of the data processing platform, Data Modeling principles persist. However:

  • The technical specifics of a given platform can vary  e.g. the implementation strategy in relation to ISO standards for SQL
  • Platforms such as the Snowflake Data Cloud offer a wide variety of additional data processing features such as Zero Copy Cloning, Time Travel, and Data SharingThese features are typically influenced by data modeling.
  • How can we ensure successful solution delivery, following industry standard data modeling methodologies such as Kimball Dimensional Modeling?
  • How can AI augmented data modeling be applied to the Snowflake Data Cloud?

 

Background to designing the training

Having worked with Snowflake clients since 2019, this is a gap I continually see. That’s why I designed a corporate training course for experienced data modelers, with Snowflake as the target environment.  

I’ve been designing databases since 1999. For the last decade, this has been in a leadership role across a wide variety of data modeling initiatives such as: 

  • Enterprise data model delivery using the Teradata Financial Services Logical Data Model (FSLDM) for Irish and pan-European initiatives
  • Enterprise data model delivery for the Irish National Healthcare Product Regulation 
  • Primary Healthcare cloud-based analytics (Ireland)

It’s also been very fulfilling to share my expertise as Associated Faculty Lecturer in Data Management at the National College of Ireland

All of the above, in addition to my Data Modeling community contributions, were the ingredients I used for training preparation. The following are examples of my data community contributions:

  • Livestream interview : Generative AI, at the Snowflake Data Cloud Summit, Las Vegas
  • Session title: Generative AI augmented Data Modeling on Snowflake, The #KnowledgeGap Conference 2023
  • World Wide Data Vault Consortium 2022 : Hands-on-Lab
  • Session title: Snowflake Data Cloud Data Modeling with the SqlDBM (Webinar)
  • Session title: Optimizing Data Vault architecture on the Snowflake Data Cloud, Data Modeling Meetup Munich (Webinar, inspired by Kent Graziano)

 

The courses

 

SummaryQuote - from Steve Hoberman regarding data modeling training delivery

If your organisation is already well-versed in terms of data modeling, but eager to enhance it’s in-house skillset in the context of Snowflake, then this training is a great way to level up!. It covers a variety of areas for example:

  • The Snowflake object hierarchy
  • The data lifecycle
  • Data Modeling and Data Governance 
  • Data Modeling & cost optimization 
  • DevOps integration
  • Methodologies
  • AI augmented data modeling on Snowflake

For more details, do get in touch!

This training offers a unique opportunity to delve into the important data modeling aspects of one of the most powerful and innovative cloud data platforms available today.

 

© Dan Galavan 2024

 

 

 

Snowflake SnowPro Advanced Architect Certification Certified Data Vault 2.0 Practitioner