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Snowflake: a tool for all-level analysts
Updated July 16, 2023

Snowflake: a tool for all-level analysts

Anonymous | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with Snowflake

We use Snowflake to query data from AWS S3. SQL query is easy to use for all level of data analysts/data scientists and as a result, Python or R is not required to pull data from Snowflake. Snowflake is widely used in my organization from customer acquisition to customer management.
  • Query.
  • Easy to use.
  • Low requirements.
  • Data type.
  • Speed.
  • Integration.
  • Efficient.
  • Work together.
  • Lower the requirement.
Compared to Amazon Redshift, Snowflake is slightly easier and faster to achieve ROI but based on the user's perspective, the two tools have very little difference since both are leveraging SQL to pull data from AWS S3. Snowflake is also working with Microsoft Azure but it is not used in my organization.
All the questions you have with Snowflake on the coding level is just SQL for which you can get the support from any SQL tutorial website such as W3 schools; on the access level it's based on your organization's authorization and you cannot really require Snowflake to figure that out.

Do you think Snowflake delivers good value for the price?

Yes

Are you happy with Snowflake's feature set?

Yes

Did Snowflake live up to sales and marketing promises?

Yes

Did implementation of Snowflake go as expected?

Yes

Would you buy Snowflake again?

Yes

Snowflake works really well when you have all different levels of data analysts in one team. Snowflake can be the common tool to pull data and create tables since SQL is such a basic and easy-to-use data science language without the requirement of fully understanding the data type.