Snowflake Analytics Reviews

We use it for our full application operational analytics, including building, storing, and analyzing the data. It provides us with detailed insight, making it easy to extract needed reports. Everything related to business intelligence, whether it's reporting or analytical modules, is stored on the Snowflake Analytics platform.

It's an intuitive platform that allows organizations to rapidly adapt, providing the ability to quickly analyze and make data-driven decisions. It ensures the optimization of the application development while maintaining the user-friendly nature of its UI.

Machine learning should be improved. Some of the solutions, such as Databricks, offer an option to directly write and integrate Python code on the spot, but Snowflake doesn't have that feature yet. Adding it would be useful, as it would facilitate building models.

I have been working with Snowflake Analytics for a year.

It is a stable platform.

It offers good scalability.

I am highly satisfied with their level of customer service and support. I would rate it nine out of ten.

The initial setup was done seamlessly.

There was no requirement for installation. They provided us with a link, giving us access to the cloud.

It is an expensive solution, but the kind of usability and flexibility it proactively provides for the organizations justify the price.

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.

In my company, we use Snowflake Analytics for the data lake process and data mining and not for data analytics. We use the solution for reporting and management capabilities.

My team describes Snowflake Analytics as a good solution, and our clients are also satisfied with the tool. Developers also find the product to be good since they have been able to do what we have received as a request till now.

Considering everything I have accessed, the product's dashboard is good since it provides multiple good options, including customization options. We can create the permissions or roles allowing us to give what we want to someone else.

I cannot comment on the product's stability because we are still struggling with its performance. The issues with its performance might possibly be due to how its setup phase got carried out by our company, but I am unsure about it. I cannot blame Snowflake and its architecture or application since our side might have caused the issues because we are new to the tool.

Snowflake can consider the aforementioned details for improvement.

I have been using Snowflake Analytics for six months. I am using the solution's latest version.

Scalability-wise, I rate the solution an eight out of ten.

Direct users of the tool in our company are around 12 percent to 15 percent of the employees since we use one of our background services for data load.

There has not been much interaction from my end with the solution's technical support. I rate the technical support an eight out of ten.

Positive

The solution is deployed on the cloud. We have our own cloud, like a SaaS model, and it is a private cloud.

Snowflake Analytics is a good tool based on the PoC phase and how we have implemented it in our company. Based on the comments and feedback from many, it looks like a good tool. Any company can use Snowflake Analytics, and it can be helpful.

The product is good, depending on how the developer can make it usable.

Overall, I rate the tool a nine out of ten.

Snowflake replaces enterprise data warehouses that have traditionally been on-premise and had to be managed by the enterprises themselves. We are a services company and we create these data platforms for our enterprise customers in a variety of industries including health care, education, travel and tourism. We create and build services around Snowflake and part of my job is to assess its suitability for our enterprise customers. We are partner of Snowflake. 

The solution is completely managed and that's fantastic. Its a true SaaS kind of Data platform. You can create analytical products as a SaaS offering, nothing needs to be installed and no licenses needed. The solution can run on AWS, Azure and on Google Cloud and you can choose the underlying cloud on which Snowflake creates your databases, uses different services, stores your accounts and stores your data. It offers high flexibility. It offers computation completely decoupled from the storage so you pay fees for computation cost only, and storage is very very cheap. For example, within the enterprise data warehouse, if the total compute time is two hours a day but the traditional setup has to be maintained and managed round the clock, and the data also has to be permanently stored, them moving to Snowflake would ensure that the enterprise pay much less for storage, and pay for only 2 hours of computation. Performance-wise also it's a good solution. 

In your data platform, if you have a lot of computations, Snowflake can becomes costlier with. There can be some complexity when designing your warehouses or enterprise data, but that is based on your requirements and not the underlying warehouse that you choose.

I've been using this solution for about 4-5 years.

It's extremely stable because it's backed up, load-balanced and has the elasticity that the underlying cloud (AWS, Azure, GCP) provides. 

The solution is scalable and has the concept of creating virtual resources, so as an example, I can buy 10 gigabytes of data capacity, then decide to process that data every day, Snowflake then takes care of creating multiple databases/storages, and scales by itself. I don't need any calculations of load or throughput worked out beforehand. For most other similar products, such as RedShift or Azure Synapse, you have to work out your average load and peak loads beforehand , and provision the warehouse and other services. In Snowflake, you don't need to do that, it auto-scales up and down.

Customer service has and support are at par with any professional Data Platform service.

Positive

The initial setup is straightforward. You buy an account, and add the number of accounts you need, and that's it. It takes about five minutes. 

The solution can become expensive when you increase your computation. So one has to design the solution very carefully and optimally. Leverage it heavily for Storage, but for compute, make sure the resources (e.g. Virtual Warehouses, Snowpipe, Streams, Tasks etc.) as well as the transformations are used in the most optimum way. For example, during the design time, the technical team has to wisely think if your data marts can be Views or Tables (View consumes compute, but Tables consume Storage), how frequently your data marts need an update, whether you should write lesser but complex queries of more but simpler transformation queries and stored procedures and many other things. But its ease of use, decoupling of Compute from Storage, ability to share data, and highly managed behavior make it worth the money.

I highly recommend Snowflake wherever possible. 

I rate this solution 9 out of 10. 

Our customer use cases vary. Some are doing AI models to pick up trends in the telco, finance, or insurance sectors. Our insurance clients use it more as a data warehouse or data lake for their customer data.

It's the ease of use and the speed with which you can get access to the data. That's really what's added a lot of the value.

It's cloud-based technology, so they can spin it up a lot faster. It's quick and easy to use, quite flexible, and meets all the requirements for a data lake and data warehouse. You don't have to go through the old-school, long process to get a data lake or data warehouse going. I think the main important thing is that you can easily share data from Snowflake.

The elasticity and the scalability are quite valuable. And also, the ability to manage the cost.

Snowflake Analytics should probably have more built-in tools for master data management, data purification, and enhancement. Instead of using third-party tools, it would probably be good if it could be internal to Snowflake.

So, to have integrated capabilities for master data management.

I have been using it since 2021. I work with the latest enterprise edition, AWS version.

I would rate the stability a ten out of ten, where one is low and ten is high stability.

I would rate the scalability a ten out of ten, from one to ten, where one is low, and ten is high scalability.

We've got four clients in South Africa that are using it. One is medium, and the other two are enterprise.

The internal support is really good. They do obviously rely on partners like us to service the client. So it's a good mix of partner and Snowflake to provide the support.

Positive

I would rate my experience with the initial setup of Snowflake Analytics nine out of ten, where one is difficult, and ten is easy to set up.

If your models are not set up efficiently, you could end up with performance and cost issues. So, you need to use the Snowflake expert reviews to ensure your models are optimal. So you have to be wary of that.

It's only on cloud. It takes a few hours to deploy it, regardless of the size of the company. 

We do follow the Snowflake guidelines and process, but our approach to our use cases and projects is an agile methodology.

It's value for money.

I would rate the pricing of Snowflake Analytics a two out of ten, where one is cheap, and ten is expensive.

Especially when compared to competitors and what they offer, the pricing is good.

Users pay for credits. It's on a consumption basis.

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.

In one project, the vendor also uses Snowflake for analytics, housing the data within their Snowflake instance. Previously, we retrieved this data via FTP and then employed a Python program to read and load it into our tables. However, by leveraging Snowflake, we can now directly access this data.

Snowflake provides multiple development tools. You can build applications with Snowflake and integrate them with Java and Python. You can write code in Python and Java and use secure features.

Some functionalities available through SQL are inaccessible in Python or Java within Snowflake. Snowflake must enhance its support for these programming languages to offer full flexibility and capacity, allowing developers to use them.

Currently, there are restrictions. For example, using Spark Engine with Snowflake allows you to write code but not call external functions or packages. Snowflake must improve its programmatic capabilities to support better engineers and developers, especially those transitioning from big data technologies.

I have been using Snowflake Analytics for two years.

Snowflake Analytics offers scalable data warehousing solutions that can effectively handle large volumes of data. Increasing the capacity of the data warehouse can enhance its scalability, making it more adept at capturing and managing big data.

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.

I like the integrations available in the product. We can send the data to our data warehouse if we want to transform it. I like the cloud solution. It's not necessary to use a physical server.

The UI must be improved. It would be pretty helpful to have some images showing what we are doing and how we use the tool.

I have been using the solution for two years.

I rate the tool’s stability a nine out of ten. We don't have any problem with data orchestration or data transformation. It’s pretty good.

I rate the tool’s scalability a nine out of ten. The tool is dedicated to the data team. Around 20 to 30 people use the product in our organization.

I have used Redshift and other data warehouses from Google. I used them to extract data in Oracle for 18 years while working in a telecom company. I prefer Snowflake over the others.

The initial setup was a little bit hard. It was especially hard to create a connection with the product team. The product team generated the data, and we had to create some tasks before they were sent to Snowflake. It was difficult because everyone was pretty new to the solution and did not have the necessary knowledge then. The setup was not intuitive. By the end, we understood how to deploy it. The product is deployed on the cloud. The initial deployment took one or two weeks. Later, it takes two or three days to change or update things.

We implemented the product in-house.

Using the product is more about our perception and technical skills in data modeling and querying. If we use it well, the tool runs well more than 90% of the time. It’s easy to use the solution because it has everything that we need. It performs well. People who want to use the solution must create a demo account and try using it. We must optimize our SQL queries. It is helpful to understand the volume of our data before writing codes. Overall, I rate the tool a ten out of ten.

We use Snowflake Analytics as the main data source for a project.

The most valuable feature of Snowflake Analytics is the ability to control and manage the cost.

The solution’s scalability could be improved.

I have been using Snowflake Analytics for about two and a half years.

The solution's stability is pretty good. I rate Snowflake Analytics a nine out of ten for stability.

Around 1,000 users use the solution in our organization.

I rate Snowflake Analytics a six out of ten for scalability because we faced some issues on big projects.

The solution's technical support team responds on time, but some complicated issues take time to be resolved.

Snowflake Analytics is not an expensive solution, and its pricing is average.

Overall, I rate Snowflake Analytics an eight out of ten.

My company uses Snowflake Analytics for data lake, data warehouse, data mart, and other related stuff.

Features like the fact that the solution is very fast and available on the cloud are some of the valuable attributes of the solution.

We are satisfied with the solution since Snowflake brings in a lot of new features now and then.

The solution's high price can be an area of concern that needs improvement.

I have been using Snowflake Analytics for four years. My company has a partnership with Snowflake Analytics. I am using the solution's latest version.

Scalability-wise, I rate the solution a nine out of ten.

Around 50 users use the solution in my company.

Our company's clients consist of medium and enterprise-sized businesses.

The support provided by Snowflake is fine since they are fast and helpful. I rate the technical support an eight out of ten.

Positive

I rate the setup phase a nine or ten on a scale of one to ten, where one is difficult and ten is easy. The solution's setup phase was easy.

The solution is deployed on the cloud.

The deployment time taken for the solution was six months.

There was nothing much involved in the deployment process. The deployment process involved just exporting the base objects.

On a scale of one to ten, where one is a low price, and ten is a high price, I rate the pricing a seven. The solution's pricing is high.

There are no costs in addition to its standard licensing price.

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.

We use the product to generate insights. 

I am impressed with the product's data-sharing feature. 

The tool should support EIM use cases. I guess the product is already working on it. I look forward to seeing inbuilt AI generative tools in the solution's future releases. The tool's price can be a little lower. The solution's on-premises support is also very limited. We have to rely on other support services to deploy it on-premises. 

I have been working with the solution for four years. 

I would rate the product's stability a nine out of ten since it is stable and reliable. 

I would rate the tool's scalability a nine out of ten. My company has more than 1000 users for the tool. 

The solution's support responds fast. 

Positive

I would rate the solution's setup a nine out of ten. Being a SaaS product, the setup is straightforward. The solution's setup becomes complex only when you need to create a specific cloud platform which is virtual or public. If you have a CI/CD pipeline ready, then deployment can be automated. The tool's deployment doesn't take more than a day to complete. 

The solution's price is high and I would rate it an eight 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. 

Snowflake Analytics is used for data warehousing, reporting, and analytics. 

The most valuable feature of Snowflake Analytics is its performance.

Snowflake Analytics can improve the integration with machine learning tools and AI and it will make the solution more usable.

In a future release of Snowflake Analytics, transactional processing should be supported natively within the solution. The transactional process means, for example, you go to a bank, you draw money, you deposit money. These are all real-time transactions. Thousands or millions of people who draw money and deposit money participate in using transactional systems, such as ATM withdrawals. We want this to be supported by the Snowflake system.

I have been using Snowflake Analytics for approximately five years.

Snowflake Analytics has high availability.

The scalability of Snowflake Analytics is excellent.

We have approximately 1,000 users using this solution.

The technical support from Snowflake Analytics is outstanding.

The initial setup of Snowflake Analytics is easy. It took three to six months to do the entire deployment.

I rate the initial setup of Snowflake Analytics an eight out of ten.

There are 10 to 15 people required for the implementation of Snowflake Analytics. We did the implementation ourselves.

We use two to three people that support the solution. However, we have full support from Snowflake.

The cost of Snowflake Analytics is low, any small organization can use it.

I rate the price of Snowflake Analytics a four out of five.

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.