About Customer: Global Clothing Retailer

This case study is of a global lifestyle brand that continues to design clothes, fragrance, watches, footwear and more, with real life in mind. Building on a heritage, simultaneously INNOVATING and challenging to have a FRESH and RELEVANT outlook, so they can create a VERSATILE and adaptable wardrobe.


About Intricity

Intricity is a team of specialized Data Management, Data Warehousing, and Business Intelligence experts. The team members at Intricity have been handpicked over the course of 20 years, and represent the top talent globally in Data oriented disciplines.


Challenge and Wins




Navigating Constraints

The customer had deployed many stored procedures in Netezza which required work to be migrated, thus they wanted to avoid creating any native stored procedures to their future platform. Snowflake also was not ready to have their private preview of stored procedures used for such a complex production scenario. This introduced a major roadblock as the stored procedures were highly elaborate, and depended heavily on nested procedures. Additionally, the people that wrote the stored procedures were no longer employed by the customer. Thus, Intricity had to reverse engineer all the code which contained all the business logic. The customer also had many shell scripts that called the Netezza Stored Procedures.

Every step in the stored procedures was logged in the Netezza deployment, and this level of logging was something that the customer insisted be kept in the future Snowflake deployment. This was because the people who wrote the stored procedures no longer worked for the customer. However, they could read the results of the logs and determine what to fix.


Win 1:

The customer was looking for assurance, and Intricity provided a fixed priced migration from Netezza to Snowflake. This gave the customer confidence that the migration could occur within the desired timeline and on a fixed budget. Intricity delivered the “lift and shift” of the migration before the November 1st 2018 deadline.


Win 2:

Intricity replicated the look and feel of customers’s stored procedure calls by storing the SQL code in tables and allowing it to iterate through a controlled python processing pipeline. This allowed every stored procedure to work in the same way without actually using a stored procedure, as they had requested. This also allowed the customer to maintain the integrity of the extensive business logic from the original stored procedures.

Intricity leveraged the existing shell scripts which controlled Netezza’s loading orchestration by inserting Intricity’s pseudo-stored procedures, which looked and acted the same. This reduced the required code changes which further enabled the customer to finish its “lift and shift” on time.


Win 3:

With the replication of the stored procedures in python, a critical requirement was the ability to manage transaction control with full rollback, should there be a failure. In developing the pseudo-stored procedures Intricity had to produce a method of delivering transaction control which supported nesting. Intricity developed a python processing pipeline which straddled multiple active sessions in Snowflake to ensure integrity during rollback and logging.


Call to Action

Intricity has created a repeatable framework for conducting these migrations which has a proven track record. This framework is used not just for Netezza migrations but for any source system to Snowflake. For a short description of how this framework is specifically used with Netezza see Intricity’s Netezza to Snowflake Migration slick.


To review the Intricity migration from Teradata to Snowflake in more detail reach out to specialist@intricity.com to review your specific use case.