The Snowflake data warehouse is particularly useful for companies looking for a platform that offers unique solutions for them that a conventional data platform cannot. In addition, their convenience and capability have made it all but unnecessary for enterprises to set up their own data warehouses.
The Snowflake schema in a data warehouse enables various financial, insurance, media and technology, and healthcare IT solutions for major industries.
Pros of Using Snowflake Data Warehouse
Let’s look at some of the many benefits that using Snowflake data warehouses can provide.
Snowflake can run on Microsoft’s Azure, a cloud-based storage blob that's affordable, scalable, and user-friendly. It also has a high storage capacity, making it ideal for use by businesses that handle a large amount of data.
While Microsoft Azure is a preference among many organizations, you can also host Snowflake on the other popular cloud platforms, like Google Cloud and Amazon Web Services. With these three hosting options, integration with Snowflake provides a great data warehouse solution for companies across many industries.
While legacy data warehouses needed significant investment in servers and other hardware, Snowflake offers a much greater capacity without needing to update equipment. With Snowflake, everything is cloud-based, meaning you can deploy it on a minute scale that can later get scaled up or down based on the company’s needs.
Many organizations handle sensitive data and require it to be adequately protected. Snowflake’s background offers IP whitelisting to limit the access of data to only trusted, authorized users. Coupled with two-factor authentication, SSO authentication, and AES 256 encryption, along with the fact that it encrypts both data in transit and at rest, Snowflake offers high-quality data security.
Snowflake databases are as user-friendly as they get and allow users to organize data in any manner they wish. Snowflake is designed to be a highly responsive platform that performs optimally on its own—there’s no need for a specialist to keep an eye on it constantly.
Some organizations worry about not having physical server access to where that data gets stored in the event of a failure. Snowflake databases have contingencies for disaster recovery and ensure that multiple data centers replicate and provide easy access to your data if disaster recovery is needed.
It’s not uncommon for businesses to have periods where they suddenly have more users on their network or a higher workload than usual. Snowflake clusters help cope with those fluctuations because they are scalable up and down depending on demand, ensuring that the database can comfortably accommodate the number of additional users.
Snowflake schema in the data warehouse is an extension of the star schema design methodology. The Snowflake and star schema offer their own variety of unique benefits in data warehouse design.
Analytics calls for large databases running off of a multidimensional schema, and Snowflake schema is a multidimensional schema that is arranged in such a way that resembles a snowflake’s design. The Snowflake schema is an upgrade to the basic star schema.
The star schema is a simple design that makes for easy navigation and fast cube processing. However, the Snowflake schema is better optimized for MOLAP modeling tools, and it has a structure that, although more complex, provides users with better storage savings.
Cons of Using Snowflake Data Warehouse
As you have seen, there are many Snowflake benefits. Snowflake data warehouses do have a few downsides, but that doesn’t mean users should discount them as being a top data warehouse system.
Unstructured Data Support
Currently, Snowflake caters to semi-structured and structured data. However, we expect unstructured data support sometime in the future.
Bulk Data Load
When you want to migrate data to Snowflake it can be a challenge. Snowflake provides Snowpipe for continuous loading of data, but it isn't the best choice in most cases. For example, a more robust solution is the Mitto from Zuar. Mitto gets data flowing from hundreds of potential sources into Snowflake, and everything can be automated.
No Data Constraints
While Snowflake is highly scalable and allows users to pay for only what they need, there are no data limits, which applies to both computing and storage. For many organizations, it can be too easy to exceed the use of their services only to realize the problem during billing.
Why Organizations Are Using Snowflake Data Warehouses
Many modern organizations are making the change and shifting from traditional in-house data platforms to cloud-based storage. This change is driven by:
Data Protection and Security
Organizations store their important, sensitive data on computers, leaving it potentially vulnerable to cyberattacks. Third-party solutions like Snowflake data warehouses offer security features to help mitigate the risks of data breaches by offering affordable, secure solutions.
By migrating data to cloud databases from in-house servers, businesses get access to modern computing capabilities that they never had before. Snowflake lets organizations make better use of their data when performing analysis and finding insights to guide their decisions and operations.
Operational Performance and Cost
For an organization to have the storage capabilities and computing power that Snowflake provides in-house, it would have to make a significant investment into IT equipment and expertise. Snowflake allows these businesses to access their services to the extent they need without worrying about the hardware and maintenance costs. The benefits of cloud computing outweigh the subscription costs for most businesses.
There’s an obvious need for companies in various industries to make upgrades to their data platforms to leverage their new and upcoming tools and apps. With Snowflake, they gain better access to their data and modern analytics that can help take their company to the next level.
However, planning and executing a major change can be a challenge. It requires support and guidance from professionals with expertise in cloud-based computing solutions. To ensure a successful cloud migration journey, organizations should:
- Define the goals they want to achieve with the change
- Determine any gaps in talent and expertise within the company
- Choose software tools that will be beneficial in the long-term, safeguard their data, and be easy to use.
From Snowflake to Full-on Blizzard
Zuar is a technology company that connects the services you use. With our Mitto solution, automate the process of pulling data from a wide selection of sources and into Snowflake. On the way the data is fully prepped, ensuring it’s ready for whatever analytics tool you’re utilizing. You can learn more about Mitto here.
Get your free data strategy assessment from Zuar to see how we can help!