Likelihood to Recommend For [a] data scientist require[d] to build a machine learning model, so he/she didn't worry about infrastructure to maintain it.
All kind of feature[s] such as train, build, deploy and monitor the machine learning model available in a single suite.
If someone has [their] own environment for ML studio, so there [it would] not [be] useful for them.
Read full review I am over our HR data, and we use Workday for our HR management system. I have a script in place that runs reports on Workday and saves the results as CSVs. I can then use stages in Snowflake to insert these CSVs into Snowflake, then I can insert or truncate and replace these staged tables into a final schema. Then once these are in a schema I can reference them and build out my data models. In addition to ingesting CSVs, Snowflake has the ability to write a CSV file to our Amazon S3 bucket. Ingesting these CSVs, transforming the data, then delivering it to a destination would've involved so much more coding than my current process if we were on any other platform.
Read full review Pros User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared! Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch! Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free. Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there! Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files. Read full review Snowflake scales appropriately allowing you to manage expense for peak and off peak times for pulling and data retrieval and data centric processing jobs Snowflake offers a marketplace solution that allows you to sell and subscribe to different data sources Snowflake manages concurrency better in our trials than other premium competitors Snowflake has little to no setup and ramp up time Snowflake offers online training for various employee types Read full review Cons It would be great to have text tips that could ease new users to the platform, especially if an error shows up Scenario-based documentation Pre-processing of modules that had been previously run. Sometimes they need to be re-run for no apparent reason Read full review This tool is very much technical and proper knowledge is required, so mostly you have to hire an IT team. I wish if various videos could be available for basic quires like its initiation, then I think it would act as a guideline and would help the beginners a lot. Read full review Likelihood to Renew SnowFlake is very cost effective and we also like the fact we can stop, start and spin up additional processing engines as we need to. We also like the fact that it's easy to connect our SQL IDEs to Snowflake and write our queries in the environment that we are used to
Read full review Usability Easy and fastest way to develop, test, deploy and monitor the machine learning model.
- Easy to load the data set
-Drag and drop the process of the Machine learning life cycle.
Read full review The interface is similar to other SQL query systems I've used and is fairly easy to use. My only complaint is the syntax issues. Another thing is that the error messages are not always the easiest thing to understand, especially when you incorporate temp tables. Some of that is to be expected with any new database.
Read full review Support Rating Support is nonexistent. It's very frustrating to try and find someone to actually talk to. The robot chatbots are just not well trained.
Read full review We have had terrific experiences with Snowflake support. They have drilled into queries and given us tremendous detail and helpful answers. In one case they even figured out how a particular product was interacting with Snowflake, via its queries, and gave us detail to go back to that product's vendor because the Snowflake support team identified a fault in its operation. We got it solved without lots of back-and-forth or finger-pointing because the Snowflake team gave such detailed information.
Read full review Implementation Rating Not sure
Read full review Alternatives Considered It is easier to learn, it has a very cost effective license for use, it has native build and created for Azure cloud services, and that makes it perfect when compared against the alternatives. As a Microsoft tool, it has been built to contain many visual features and improved usability even for non-specialist users.
Read full review I have had the experience of using one more database management system at my previous workplace. What Snowflake provides is better user-friendly consoles, suggestions while writing a query, ease of access to connect to various BI platforms to analyze, [and a] more robust system to store a large amount of data. All these functionalities give the better edge to Snowflake.
Read full review Return on Investment Productivity: Instead of coding and recoding, Azure ML helped my organization to get to meaningful results faster; Cost: Azure ML can save hundreds (or even thousands) of dollars for an organization, since the license costs around $15/month per seat. Focus on insights and not on statistics: Since running a model is so easy, analysts can focus more on recommendations and insights, rather than statistical details Read full review Positive impact: we use Snowflake to track our subscription and payment charges, which we use for internal and investor reporting Positive impact: 3 times faster query speed compared to Treasure Data means that answers to stakeholders can be delivered quicker by analysts Positive impact: recommender systems now source their data from Snowflake rather than Spark clusters, improving development speed, and no longer require maintainence of Spark clusters. Read full review ScreenShots