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75%

reduced

Snowflake processing costs

20

data sources

migrated within 5 months

3X

increased

data accessed

About

Musti Group is the leading Nordic pet care specialist operating in Finland, Sweden and Norway. Their mission is to make the life of pets and their parents easier, safer and more fun. Their concept is built around trust and expert advice, high-quality assortment, omni-channel business model and growing suite of services.

Musti Group’s net sales were EUR 340.9 million in the fiscal year 2021. At the end of the fiscal year 2021 the company had close to 1400 employees, 1.3 million loyal customer, and 312 stores.

Challenge

Musti began its initial project to migrate their on-premises data to Snowflake in 2020. By early 2021, they had migrated some of their data to Snowflake, but were not really making much use of this data due to a multitude of reasons.

First, the legacy tool they were using for data migration and transformation (building of business logic) required extensive hand coding. Their data team did not have the bandwidth or the resources required to move all of their data and build the business logic necessary for their needs. In addition, the migrations that were completed and the business logic within the data jobs had too much code and required extensive processing within Snowflake to get any results. Data jobs were running several hours a day in Snowflake, which ended up becoming very costly for Musti.

As a result, after almost a year, Musti had migrated only a small portion of their data to Snowflake, and they were not doing a lot of analysis on the data that was migrated. They were still primarily relying on their legacy on-premises data stack for analysis

Solution

In 2021, Musti decided that they needed a cloud native data integration and transformation solution to overcome their migration challenges and make their Snowflake implementation a success. After considering a number of solutions, Musti chose Matillion ETL for Snowflake to essentially restart and optimize their Snowflake Data Cloud migration project from scratch.

Musti used Matillion to migrate their data from legacy internal and external data sources to Snowflake and rebuild the business logic without impacting any of the existing systems. Essentially, they were able to ingest data to existing Snowflake tables without impacting the performance or integrity of the existing on prem or new Snowflake systems. Ultimately, once all the data pipelines and business logic workflows were set up within Matillion, Musti was able to shut down their old legacy integration infrastructure.

With Matillion, Musti was able to rebuild all business logic, migrate the majority of their data to Snowflake, and get into production within 5 months. Not only were they able to incorporate more data sources then before, they were doing it much more efficiently and at a lower cost.

Results

  • Migrated 20 data sources (internal and external) Snowflake within 5 months
  • Increased the amount of data accessed by 3x
  • Was able to complete the initial phase of the Snowflake migration project within 5 months
  • Shut down two legacy, on-premises data warehouses
  • Low code business logic resulted in reducing Snowflake processing costs by 75%

Benefits

For Musti, the Snowflake migration project, once it restarted with Matillion, went very smoothly. Matillion’s visual business logic and low code capabilities ensured that Musti was able to get more data into their Snowflake Data Cloud, with less effort, and run more data jobs within Snowflake – conduct more analysis, get more value from their data – more efficiently, at a lower cost.

First, Musti set up Matillion to reload their data to Snowflake. Matillion’s visual business logic made it easy to ensure data integrity and also see any errors in the business logic. They were also able to reduce the amount of code within the business logic of data jobs considerably with Matillion’s low-code transformations (prior code was 3,000 – 4,000 lines, which resulted in data jobs requiring significant processing time and costs within Snowflake).

With Matillion, not only was the amount of code significantly reduced, the visual business logic also made it easier to optimize queries, ultimately making it easier for Musti to provide analytics-ready data to the business users.

What's next?

With Matillion, Musti does not foresee any additional significant cloud migration challenges and plans to migrate all of their data to Snowflake and shut down the existing on-premises environment entirely. They are also in the process of rebuilding their Snowflake reporting engine to improve how data is accessed and used by the business. Matillion has made this worthwhile project possible by affording Musti’s data team more time to work on such value-based projects rather than spend all their time putting out fires. Finally, Musti is also planning to move their Snowflake environment from AWS in Ireland to AWS in Stockholm to improve latency and make it easier to comply with GDPR and other data privacy and sovereignty requirements. Matillion makes such a move easy as it is deployed within a customer’s own public cloud instance. In fact, Musti currently deploys Matillion within AWS in Stockholm.

Prior to Matillion, all my time was spent putting out fires and fixing errors within the system. Now, with Matillion, I have time to actually provide more information and more value to the business. Michael Boucht Lead Data Engineer| Musti Group