Snowflake has improved our organization by powering company-wide dashboards that functions use to understand and manage their business. We also have dashboards that go up to our board of directors and our C-suite. Snowflake allows us to have up-to-date, consistent, and useful reporting for the entire company.

We are able to consolidate multiple databases into one unified table for more complete reporting. That wasn't possible in our legacy tool that we were using because the query time was just too long. Now we're able to create this unified view of our entire organization and refresh it every 15 minutes; using the power of Snowflake's query is pretty much our biggest use case there.

The product has impacted collaboration across our teams. The correlation is quite easy. We use the solution because most of our life sciences and healthcare customers prefer it. Their preferences directly impact us as vendors and partners. We have to promote the same tools and technology they are familiar with.

This solution has helped our organization by being easy to maintain and having good technical support.

The core feature of the platform is everything works, and that's what I like about it. Our time to market is faster, it requires less maintenance, and I can build and deploy a product exceptionally quickly.

It helped us to build MVP (minimum viable product) for our idea of building a data warehouse model for small businesses. 

About ten years ago, force.com from salesforce.com offered a similar platform for us to build data warehouses. However, our staff with a data engineering background found it easier to build the data warehouse in Snowflake, with the easy-to-use SQL interface and RBAC models (role-based access control). The platform saved us money as it automatically shuts down the compute engines after about five minutes of idle time. Per second billing (above the first minute) is great. 

We are working with a TV advertising agency and they were able to set up a Snowflake data share to share ad spend with us and it was very quick to integrate.

It has improved the way our organization functions. However, we're still pretty elementary in our understanding of how it all works and the complete capabilities of Snowflake.

It's definitely for compute. The best use case of Snowflake is massive compute. With the parallel reads that we can do from Snowflake, we can combine data from disparate sources, consolidate it, and provide it to end clients through custom stored procedures.

The productivity across the teams that use Snowflake I believe is higher than it would be without the solution.

We were able to implement the entire data eco-system in less than five months, from data integration, data warehousing, ELT, producing fact and dimensional tables, and finally reports.

There are so many features that Snowflake offers to address the challenges that people have been facing in the traditional data warehouses for a long time. It allows us to have a single repository for all the data. Currently, we have data repositories all over the place, and we want to bring everyone onto one platform so that it can be utilized across the organization. Currently, we need database administrators and SAP administrators to manage multiple databases and platforms. With Snowflake, we don't need any admin, and there is zero maintenance. All we need is a platform architect who can just manage the Snowflake platform to create databases and security roles, and then you can share the data. By integrating everything into a single Snowflake platform, we have lowered the total cost of ownership quite a bit.

With Snowflake, productivity can be increased. Snowflake is faster than on-premise systems and allows for variable compute power based on need. We are currently experimenting with ways to reduce processing time from eight hours to six hours or even less.

One small company I worked with had a MySQL RTS based instance and were using AWS RDS with MySQL on top of that. As a result they were unable to scale their database because there were around half a million queries being run per second as well as data querying and data updating. The migration to Snowflake helped the company because there are no limitations in the cloud and no longer restrictions on the queries. Performance for end users improved whether they were internal or external clients. They used to sell the data through APIs so this migration helped to grow their business overall as well as the ML team efficiency and the productivity of users who previously used the data platform. 

It had definitely improved the way our organization functioned at the time.

Snowflake has improved my organization because of its high performance compared to the old way we used to operate with Microsoft SQL Server. We are migrating everything from SQL Server to Snowflake. It used to take a lot of time to query the database but now it is done a lot faster, we receive millions and billions of reports. This is a major benefit because it is our major use case.

Snowflake helped us to improve query performance as the data was growing. Also, we could store and process JSON and XML using Snowflake, which was not possible with RDBMS solutions. This also helped us to store huge amounts of data in Snowflake as a single source of truth and we could also use it as DWH. It is a single technology for multiple use cases.

Snowflake also helped us improve query performance to a great extent. The inserts of large JSON objects are very quick and processing them is very easy.

One of example of how Snowflake has improved a client's organization is the democratization, it makes information available to more of the users.

• Excellent performance
• Very easy to use
• Amazing UI

We were using MySQL and MongoDB for our regular operations but when we grew, we were forced to handle a huge number of datasets. We could have petabytes of data in and out on a regular basis. We struggled a lot to complete the operations in a timely manner. With Amazon Redshift, we gained a lot in terms of timing, as well as project completion. Even-through we are happy with Redshift, in terms of pricing and availability of nodes, I am more comfortable with Snowflake. Some of the scoring mechanism really works well in the distributed architecture of Snowflake.

We don't have a metric, but I would say that the processing time was a key benefit and value-add. It provided on-time processing.

Snowflake solves many of the challenges that traditional data warehousing tools have such as a lack of agility, scalability and fine-tuning.

We mainly used SQL scripts and provided a solution for different owners who want to query a database but have several tables. Typically, it is not an easy task to read several tables, so we provided our client with a very crisp data model where they can get results in a very quick manner. We implemented distribution as well as weekly partitioning.