Snowflake is a robust data warehouse that has changed the data science game for many organizations. Snowflake lets you analyze your data using the most sophisticated query engine available today with its cloud-native architecture. But using Snowflake is not always as simple as using other products on the market. Below are nine expert tips to help you master the Snowflake platform.
Table of contents
- What Makes Snowflake Unique?
- 1. Dedicate Compute Warehouses by Use Case
- 2. Enable Auto-Suspend
- 3. Enable Auto-Resume
- 4. Use Multiple Data Models
- 5. Leverage Materialized Views
- 6. Drop Unused Tables
- 7. Apply Resource Monitors
- 8. Purge Dormant Users
- 9. Use a Snowflake ETL
- How Integrate.io Can Help
What Makes Snowflake Unique?
First, let's take a look at the Snowflake architecture to understand better why Snowflake is such a popular yet unique software.
Snowflake's architecture is unique from every previous database and cloud data warehouse. Snowflake has its own compute and storage infrastructure, both of which are very elastic. This enables Snowflake to eliminate many existing issues when dealing with cloud data warehouses, which were often due to CPU limitations.
There are many elements of Snowflake's unique design that make it one of the top storage solutions available, and it is available on platforms such as AWS and Azure. It connects easily with industry-leading saas products and apps and is one of the best options in terms of a cloud data platform.
However, you must be able to utilize the power of Snowflake effectively.
1. Dedicate Compute Warehouses by Use Case
Depending on the usage scenario, scaling out compute capacity (more concurrency) may be more cost-effective and beneficial than simply scaling up (more performance). Size each compute warehouse correctly, categorize by use cases, and have it auto-suspended as necessary. You want to avoid using compute warehouse resources for queries that do not require it.
2. Enable Auto-Suspend
Enabling auto-suspend allows you to configure your compute warehouse resources for either "On Demand" or "Per Request." This is extremely helpful because it will enable you to use the right amount of resources at the right time.
3. Enable Auto-Resume
If you enable auto-suspend, then turning on auto-resume is essential. Auto-resume is a feature that automatically turns off the compute warehouse when it's not being used and then uses any spare capacity to process other requests.
Auto-resume is enabled by default in Snowflake, so there is no reason not to take advantage of this!
4. Use Multiple Data Models
Data storage was too expensive to handle multiple data sets due to on-premise storage solutions. However, cloud-computed storage makes sense for different data types to be stored and utilized in different ways (for example, raw data to be kept in structured or variant format). The data that has been cleaned and conformed can be stored using a Data Vault model or in 3rd Normal Form. Finally, a Kimball Dimensional Data model can store the information ready for consumption.
5. Leverage Materialized Views
Materialized views are a great way to speed up query performance using precomputed data. This can be an easy fix if you notice that specific queries take longer than expected and may need extra help to speed things up.
Materialized views allow you to save time using already processed values instead of repeating the same process repeated for each request.
These five expert tips will get your Snowflake experience off on the right foot! Start using these suggestions today, so they become second nature in no time at all.
6. Drop Unused Tables
Dropping unused tables is a great way to keep your database clean and prevent excess storage usage. If you are using materialized views, they can be used as an excellent substitute for unused tables.
Dropping tables that aren't necessary is an excellent way of keeping things efficient when using Snowflake's architecture.
7. Apply Resource Monitors
Resource monitors are a great way to track your compute warehouse usage, including the total CPU and memory used over time. This information is available using Snowflake's built-in monitoring tools that leverage Amazon CloudWatch metrics.
When using Snowflake, resource monitors can help you keep an eye on your system as it scales up or down based on current workload demands, which helps avoid situations where queries take too long because there aren't enough resources for them.
Snowflake has automated scaling capabilities, so you don't have to worry about adding new tasks when high demand suddenly arises.
8. Purge Dormant Users
Purging dormant users are an excellent way to avoid using unnecessary resources.
This is an excellent way of keeping workloads efficient without having to worry about how much data or storage might be available on your system.
9. Use a Snowflake ETL
The process of ETL, which stands for Extraction, Transform, and Load, is used to put data into the Snowflake Data Warehouse. This involves extracting pertinent data from Data Sources, performing necessary changes to turn the data analysis-ready data into Snowflake format, and then loading it in.
A real-time ETL platform offers a great way to streamline the data transfer process using Snowflake's architecture and capabilities, which can help ensure no issues with connectivity or delays in transferring your most essential workloads. In an ever-changing ecosystem of data sources, ETL is more critical than ever. This ensures that the information can be streamlined for data analytics and engineering purposes. ETLs can help you organize your snowflake data and utilize different business intelligence strategies to optimize operations.
Integrate.io is one of the top ETL software available and can help transfer data using Snowflake's architecture.
How Integrate.io Can Help
When sending information to a data warehouse or data lake ecosystem, utilizing the power of an ETL can be very beneficial when trying to interpret the data at a later point.
Snowflake is a powerful data warehouse solution, but using it can be a challenge. Integrate.io is an ETL software that offers over 70 connectors and can help transfer your large datasets quickly using Snowflake's architecture right out of the box.
Integrate.io also has exceptional features like using Amazon SNS and utilizing APIs for notifications when importing new batches or checking up on ongoing processes to ensure everything runs smoothly.
Integrate.io has easy-to-use dashboards to assist with data management and data sharing. Using this service will offer you a way to get started using Snowflake without worrying about how you're going to manage to transfer all of your data in one go. They have a flexible pricing option to assist businesses of all sizes, so if you are ready to get started with Integrate.io, schedule a call today with an Integrate.io team member so you can receive a 7-day trial of the platform.