Greenlight’s modern data approach in biotech

#Cloud Migration

#500+ tables

About the company

Greenlight Biosciences is a biotechnology company headquartered in Medford, Massachusetts that specializes in RNA research. The data analytics management team recently decided to push full steam ahead into the cloud – replacing a legacy SQL Server data warehouse with Snowflake and adding a Synapse data lake.

To help speed up the migration and documentation process, Greenlight looked to replace their previous modeling tool – Erwin Data Modeler. It was an installable solution that didn’t afford the flexibility and convenience of the cloud. They needed a tool that would allow them to quickly iterate database designs and share them with the relevant stakeholders. That’s where SqlDBM comes in – Greenlight split the work across three teams – the architects, the data engineers, and the BI engineers – one of which designed the models, the other implemented the models, and the other referenced the models.

How did SqlDBM help?

Accelerate a cloud migration from SQL Server to Snowflake
Establish a modeling framework from design to implementation
Save time by eliminating repetitive tasks and meetings through features like impact analysis and concurrent collaboration and communication.
Provide visibility throughout the database landscape - from source systems all the way to the datawarehouse(s)

Features used

Automating a lift-and-shift migration

When GreenLight Biosciences decided to modernize its data landscape by migrating to the Snowflake Data Cloud, its first step was to look for a modeling tool that was intuitive and web-based, but still robust. SqlDBM ticked all those boxes by offering native support for both their SQL Server and Snowflake databases, allowing automated DDL conversion between the two.

SqlDBM’s project conversion feature saved GreenLight’s engineers weeks of labor by automatically converting their existing SQL Server model into Snowflake and achieving a 99% conversion success rate. Not only did SqlDBM accelerate the migration to Snowflake, it gave GreenLight’s team an all-in-one resource to scale future designs via an integrated data dictionary, version control, and a model deployment workflow.

There was no modeling before SqlDBM. It kicked off our cloud modeling journey. In no time, we had a documented model to help our data / BI engineers.

Karthikeyan Shanthakumar,
Senior Data Warehouse Architect

Establishing a new workflow

Following a successful migration, GreenLight’s data team continues to rely on SqlDBM to evolve their data model and leverage Snowflake’s cloud-native architecture to add value to the business. Through a visual design interface, the data team ensures accurate and consistent designs are generated every time. Automating repeatable and time-consuming tasks keeps the GreenLight’s team lean and focused on high-value work. They noted how Erwin’s many-step workflow prevented them from maximizing efficiency. “Everything took too long, and there were frequently errors. This kept us off the platform, and we instead iterated on our model in Excel until it was production-ready, before putting it in Erwin. With SqlDBM, the brainstorming and design is much, much faster.

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Maintain visibility and data discovery

Snowflake’s scalable architecture affords GreenLight’s data team the ability to keep tabs on all their data assets. But with that level of scale, comes a need for deliberate organization. Teams need to know what their database landscape consists of – that’s where SqlDBM comes in. Analysts and business users can now contribute to the same model – some use it to migrate databases, some use it to define and expand the business data model, some use it to troubleshoot a downstream data issue, and other use it to onboard new employees.

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Platform

Data Modeling

Model Governance

Snowflake Schema Monitoring

Integration

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Why SqlDBM?

Have questions?

Resources

Strategic advisors

Kent Graziano

Gordon Wong

For cloud data platforms

Try modeling now

Data Modeling

Model Governance

Snowflake Schema Monitoring

Integration

See all

Why SqlDBM?

Have questions?

Try modeling now

Pricing

Security

Greenlight’s modern data approach in biotech

#Cloud Migration

#500+ tables

About the company

How did SqlDBM help?

Features used

Direct Snowflake connection

Deployments

Documentation

Lineage

DB Conversion

Suggested relationships

Automating a lift-and-shift migration

Establishing a new workflow

Request Enterprise Trial

Maintain visibility and data discovery

Request Enterprise Trial

Related content

Info

Why SqlDBM?

Resources

Sign in

Sign up

Resources

Strategic advisors

Kent Graziano

Gordon Wong

For cloud data platforms

Try modeling now

Platform

Data Modeling

Model Governance

Snowflake Schema Monitoring

Integration

See all

Why SqlDBM?

Have questions?