What advice do you have for others considering Snowflake Analytics?

Snowflake facilitates AI-driven projects for our customers. Overall, I would rate it a ten out of ten, without a doubt. I think when it gets to cloud data warehouse and data sharing, it's the best.

If you're using a service like Redshift, the pricing would likely be comparable to Snowflake. With Snowflake, you're paying for the service and the underlying cloud infrastructure since these are separate costs. Snowflake operates as a software package that must be installed on a cloud platform like Azure, GCP, or AWS, meaning you also need to use their computing, clustering, and storage services. This makes the total cost dependent on both Snowflake and the cloud provider. Snowflake offers extensive features with a data warehouse background, including full SQL support and compatibility with T-SQL; other systems, like Redshift, also provide many similar features. That said, Snowflake has continued to grow in functionality and market appeal, making it more widespread. To thoroughly compare the two, you must look closely at the latest features Redshift has added, as it may offer comparable capabilities depending on your requirements. Overall, I rate the solution a nine out of ten.

I rate the overall solution an eight out of ten.

I would recommend you don't go for Snowflake every time. It depends on your use case. Analyze the use case and then decide whether to go with Snowflake or another database. For structured and semi-structured data, Snowflake is a good choice. Overall, I would rate it an eight out of ten.

I'd recommend the solution to other users. I would rate the solution nine out of ten.

The organization is completely focused on moving its processes and data to Snowflake. Once this is done and the business starts consuming and extracting data from Snowflake, value realization will occur. Initially, we began with our SaaS platform on AWS. When transitioning data from AWS to Snowflake, we found a seamless integration between the two platforms, making it easier to access data from Snowflake. This integration retrieves and uses data, contributing to the wide acceptance and adoption of Snowflake Analytics. The data creation and consumption teams have separate roles, allowing for a clear delineation of responsibilities. This ensures the consuming team only accesses the products or data relevant to their tasks. We maintain efficient data management and security by creating roles for the consumer team and providing access accordingly. Data-driven decisions have improved significantly. Previously, we had multiple small copies of the data scattered across different locations. With Snowflake, we've consolidated everything into one golden copy of the data. Someone who needs a subset of that data can create views or access specific subsets directly. This setup allows us to track who has access to the data and its origin. Consumers don't need to go to multiple places to get the data. They know the central location to access or request the data and the available data products. This centralization will help in making more informed, data-driven decisions. I recommend Snowflake Analytics if you are looking for a reliable and well-regarded solution. It has gained significant traction in the market. Snowflake is an excellent choice for analytics purposes. While companies need to research other available tools, Snowflake is a good option. Overall, I rate the solution an eight out of ten.

Snowflake Analytics’s technical and domain aspects are crucial. Both are the most important for improving other products and adding customer value. In such cases, even a few customized elements can take us far. We have some use cases in the requirements we implemented in the process. So, we are using various technologies. The most important things we need to build are customer tools. Many new features have been added to Snowflake, making it a completely cloud-based system. It's a modern data warehousing solution that incorporates many new technological aspects. I recommend Snowflake. If you opt for the red chip, you'll have to spend more on storage. You can avoid these additional costs. It supports data injection and retrieval from various sources, ensuring rapid integration. It offers seamless transition support if users migrate to other platforms like Azure or AWS. There are no limitations on promoting various concepts. Overall, I rate the solution a seven out of ten.

Since Snowflake primarily functions as a data warehouse, it is well-suited for OLAP solutions. Despite incorporating some OLTP features, Snowflake remains best suited for OLAP purposes. My advice to anyone considering Snowflake is to carefully evaluate the cost in comparison to their current solution. They should assess whether they would derive significant benefits from switching to Snowflake, especially if they are currently using platforms like Databricks or BigQuery. Comparing costs beforehand is crucial before making the transition to Snowflake. Overall, I would rate it seven out of ten.

Snowflake Analytics has supported our company's data warehousing and analytics part by helping us reduce our overall costs involved in such areas. The product also offers a better performance than the on-premises tools that are available. Snowflake Analytics has improved our company's data-driven decision-making processes since the go-to-market timeline has been reduced with the use of the product. Earlier, the go-to-market timeline was such that my company used to take over a month to get new data for the end users. My company can get the data within a week or before, allowing users to use it for their analytics. The tool has reduced the go-to-market timeline. The benefits from the product's scalability and performance features stem from the fact that it helps with the costs and reduced go-to-market timeline to get things up and ready for the end users, which is drastically much less than what the on-premises products offer. The product's maintenance can be taken care of by two people. The scalability of the product has impacted our company's data-driven decision-making since I have a lot of data with me currently. For initial loads, my company uses small warehouses, but after a while, it will be big warehouses. Based on the aforementioned details, my company makes data-driven decisions, like how much warehouse size we need or whether we need to scale up or scale out. Snowflake Analytics is better than the other platforms that work on either a cloud or an on-premises version. Snowflake Analytics can improve in areas like scalability and in the way the queries are written. Snowflake Analytics is pretty easy to use with the connectors for integration with the tools and systems in my company. Others who plan to use the solution can benefit from it. I recommend others consider or try out a PoC phase or exploration process of the product to see whether the tool fits their use cases. I rate the overall tool an eight out of ten.

Snowflake simplified our data warehousing and analytics workflow. We seamlessly integrated it with Azure Databricks, following straightforward documentation provided by Snowflake. With minimal technical effort, we created tables and loaded data, leveraging Snowflake's automatic optimization features for partitioning and clustering. Snowflake's scalability ensured seamless growth without compromising performance. With minimal worries about infrastructure, I focused on designing data models, confident in Snowflake's ability to handle our expanding needs. I would rate the ease of integrating Snowflake with our existing infrastructure between four and five out of ten. The technical team didn't take much time once we completed the POC. Within a month, we understood Snowflake, created tables, populated data, connected Power BI, and tested performance. After approval, discussions on data modeling took a couple of months, but integration remained seamless. Overall, I would rate Snowflake Analytics at an eight out of ten.

I rate Snowflake Analytics an eight out of ten. If there is a good amount of data sharing, Snowflake is the right platform. I advise others to start with a small amount of data and then optimize it to set up the right data size.

Overall, I would rate the solution a nine out of ten. I would definitely recommend using this solution.

People considering the solution must evaluate it against all the other options to see whether they need to use it. They must look at the alternatives depending on their cloud provider. If they're on Microsoft Azure, then Snowflake is the best option. However, if they're using Google Cloud, they should consider BigQuery. If they’re on AWS, they must consider Redshift. The tool has helped us with a few customer case studies. Overall, I rate the product a seven or eight out of ten.

Snowflake Analytics is a really good choice for organizations that are looking at a cloud analytics platform for reporting, data modeling, and advanced analytics without machine learning requirements.

I rate Snowflake Analytics a seven out of ten. It is a good and useful platform. I recommend it to others. We can automate data pipelines using it. I advise others to make sure it meets their business requirements.

After considering the pricing part of the solution, those planning to use it can start using it. The pricing of the solution falls on the higher side. Feature-wise, the solution is really good. If a company can afford the tool, the solution is good in its category. Overall, I rate the solution a seven out of ten.

I would rate it an eight out of ten. The solution is very easy to use. The tool is a SaaS product. You can leverage your overall data analytics strategy with the solution. It has a lot of features and you shouldn't consider it for data storage alone. In the future, we will be able to leverage the solution of ML-oriented used cases as well.

Using Snowflake, we can dump data through data pipelines and generate analytics. I do not belong to the sales team, so I do not know about the pricing information of Snowflake. I rate Snowflake an eight out of ten.

I rate this solution an eight out of ten. It is a wonderful tool. It easily organizes data, makes it accessible, loads it from the pipeline and helps with reporting.

I would recommend starting small and growing into it. Don't overbuy. If you're going to get discounts and you're going to buy a block of credits for the year, make sure you need those blocks because you're not going to peak until the second or third year of implementation. It's easier than a traditional environment and allows for focus on the value that can be provided. I rate this solution 10 out of 10.

I can advise using Snowflake Analytics only if you have your analytical use case or data warehousing need, where you have large data volumes. The use of Snowflake Analytics with smaller volumes and for transactional systems will not help organizations at this point in time. I rate Snowflake Analytics a nine out of ten.

We are partners with Snowflake. In the last four or five years, Snowflake has actually blown up. Before that, it was quite low in terms of visibility and potential. We have now done multiple engagements on Snowflake. Right now the snowflake is adding the multiple clients we using all editions. We're using a variety of clouds, including AWS and Azure. I'd rate the solution nine out of ten. While we've done many complex implementations, Snowflake always has a way of simplifying things.

Snowflake Analytics is more managed than other cloud offerings, which means I don't have to deal with anything happening in the backend. For those thinking of implementing Snowflake, I advise analyzing the cost, your volume of data, and the number of users. If you have a huge demand on these things, I would recommend choosing Snowflake. I rate Snowflake as seven out of ten.