How Implementing a Data Catalog Optimizes Your Snowflake Data Cloud Migration

[jrineakter]

During a cloud migration to Snowflake’s Data Cloud, businesses often struggle to know what data they have on premises, what they should migrate, and in what order. And because of this, many organizations fall into a “lift and shift” approach, where everything is simply copied over—as it messily stands—to the cloud.

This is a less-than-desirable outcome, as your organization is simply moving technical debt from one place to another, kicking the can down the road until it becomes someone else’s problem. Or worse, until minor technical annoyances become major problems, and their fixes steal development time that could be spent improving performance or designing new features that could ultimately increase revenue and decrease costs.

A Data Cloud migration is like moving to a new house
When you move into a new home or condo, you don’t grab the dusty boxes in your garage and dump them in the corner of your new place without knowing what goes where. Instead, you take stock of what items you currently have, decide where they belong, or whether they’re worth moving at all. (Maybe it’s time for a garage sale?)

Just as you wouldn’t fill your shiny, new home with clutter you no longer use, you shouldn’t migrate data that’s outdated or not delivering business value to the cloud.

A data catalog empowers you to inventory your on-premises data and see what you’re working with. You can make sense out of everything in your legacy, on-premises systems and set your organization up for post-migration success.

If you adopt a cloud-native data catalog indonesia whatsapp number data during your migration to Snowflake’s Data Cloud, you’re better able to accelerate, govern, and optimize your migration, improving the process from a basic “lift and shift” into a “lift, upgrade, and shift”—an opportunity to catalog, organize, prioritize, and optimize your data.

A successful post-migration world means that Snowflake’s Data Cloud will consist of data that provides business value. The migration plan defined through the data catalog provides the reason why the data should be in the cloud. Furthermore, by prioritizing you can migrate data in an iterative manner, thus enabling data teams to start using data quickly instead of waiting for a long “boil the ocean” migration process. Finally, you are guaranteeing that the expenses are justified.

Not all data catalogs are created equal
For your migration to deliver a true upgrade, you need an enterprise data catalog with certain key capabilities.

A fully complete data catalog is essential to a successful migration, and to catalog all your legacy data, you need an enterprise data catalog with a collector that can be pushed onto on-premises systems and send what it finds back to the cloud. On-premises collectors are paramount because more often than not, the data you want to migrate comes from legacy non-modern, non-cloud, on-premises data sources. Without on-premises collectors, you will be missing out on all the on-premises data that needs to be migrated.

You also need a data catalog built on a knowledge graph, which enables you to catalog and understand whatever type of data you discover during your migration, and that shows you how it relates to your other data. A knowledge graph-based data catalog provides your data model with limitless extensibility, allowing it to grow to include resources and relationships from proprietary and legacy systems, which may have not been defined before your migration, without costly and time-consuming infrastructure changes. Without this capability, you may not understand the legacy landscape of your organization, potentially leading to uninformed decisions on what needs to be migrated.