Working cost-effectively with Snowflake: More control, fewer costs

More control with workload management

A practical example: let's say you have a huge database with millions of records that you want to analyze. To come up with the right queries and algorithms, you can choose to first let your data analyst work with a smaller limited set. Only when successful, these queries and algorithms can be applied to the full dataset to see if they also yield the correct result.

Within Snowflake, this process is very fast and easy to manage. But it's also important to scale up in a timely manner. Let's say you want to apply the developed queries and algorithms to a massive dataset, then it's wise to significantly increase the deployed workloads.

Faster results, lower costs

In the demonstration we received, it became apparent that scaling up makes a huge difference and also saves costs. Running a heavy query on a large database with limited workload can take dozens of minutes or even hours. However, the same query executed on much heavier hardware can be completed within a minute. The costs of the heavier workload may be only three times higher per hour compared to the smaller workload. Therefore, choosing the right workload for the right query is essential for cost savings.

When Snowflake is deployed in a production environment where the database is used 24/7, it is important that the chosen workload can withstand the many requests. Fortunately, Snowflake also offers the possibility of scaling up and down, ensuring optimal performance at all times.

Data sharing and collaboration with Snowflake

Good data analysts are scarce, which is why many companies regularly hire external analysts to help them analyze crucial business data. Within Snowflake, it is possible to give external users access to the data, allowing precise configuration of user rights. This means that you can determine which data a user can access down to the row level. This means that an external analyst can work with a more limited dataset while shielding highly sensitive data. At the same time, an internal employee can apply their analyses to the entire dataset. In this way, certain compliance requirements can be better met in some cases.

Take advantage of Snowflake Data Exchange

Finally, it is good to know that Snowflake facilitates a Data Exchange. Here, users can share valuable datasets with other Snowflake users. This can be done for free or for a fee. For example, databases with information about IP addresses or weather forecasts per city worldwide are available. For application developers, the Snowflake Data Exchange can be a very valuable resource as it allows faster access to data and accelerates the development of applications.

With Snowflake, you not only implement a powerful cloud platform for data analysis, but also benefit from cost-effective work, more control over workloads, and collaboration with external analysts. Additionally, Snowflake offers the ability to share valuable datasets through the Data Exchange. Fully leverage the potential of Snowflake and prepare your organization for success in the data-driven era.