Transform Data in Snowflake
Low-code, no-code, SQL SaaS solution for data transformation in Snowflake.
Based on Datameer reviews from:
With Datameer Everyone in the Organization Can Transform Data
For rapid project execution: easy drag-and-drop modeling that lets non-technical analysts create base models specific to their needs.
A spreadsheet-like interface that allows analysts to enrich data or data engineers to dramatically improve productivity leveraging a large library of functions.
Full SQL coding that gives your data engineering teams the flexibility to create and deploy highly optimized data models with feature rich metadata management.
Everything Happens in Snowflake
From data storage, data transformation, and compute
Data Transformation SaaS
- Multi-persona data transformation (no-code, low-code, code)
- Let your team choose how they want to transform data with Datameer
- Collaboration across the data transformation and modeling lifecycle
Data Catalog and Metadata Management
- Self-service semantic layer
- Google like search of datasets
- Introspection of existing datasets and transformation assets
- Auto generated and user managed metadata
Data Governance and Audit Trails
- Data Lineage and Audit trails
- Business glossary and referencing
- Management of tags, properties, descriptions, and other metadata
- System and user managed rules for auto generated documentation
Industry Solutions
What Our Customers Say
One of the challenges and opportunities with the Internet of things is that there has been an explosion of stream data. Instead of having one row per customer, there may be thousands or millions of rows per customer. With its intuitive Excel-like user interface, Datameer made it extremely easy for my team to get up and running very quickly.
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The Datameer platform was a godsend. I was looking at hiring a team of data engineers to hand-code all our data pipelines in Python. In a week, we were able to complete all those complex ETL jobs with Datameer, which otherwise would have required a dozen data engineers to develop and maintain.
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Our SQL solution did not scale well with the growing volume of data we were getting, and it was becoming costly to maintain. The bigger the database got, the slower the queries became. Not only did Datameer solve that query performance and scalability issue, but it also managed to make it super easy for our researchers and analysts to use without having to write any code.
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Only Datameer could provide us with a product that offered a very fast no-code and low-code environment and could meet the needs of our extremely complex data pipelines and DataOps.
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Analytic cycle times covering the bank’s numerous marketing campaigns were reduced from five days to five hours. Thanks Datameer!
There are incredibly powerful things we can do within Datameer that allow the end-user analysts to really control what they are getting out of the data.
Books, Guides & Resources
Deep dive into Datameer data essentials about transformation, discovery, governance, and data pipelines.
How to Optimize Your Data Transformations for S...
The first building block of a cloud data stack starts with Snowflake. Your analytics engine and cloud data warehouse is always the core component by which your data stack revolves.
Read the White Paper
What is a Data Transformation SaaS Solution?
Data Transformation as a Service is an emerging solution model that provides a faster, easier way to perform data and analytics engineering and, as a result, delivers greater ROI on your cloud data...
Read the Article
How to Drive Analytics Adoption
Have you spent long evenings and weekends building a modern data infrastructure and still struggling to get the rest of the organization to adopt it? Here is a sure way to get wider business adopti...
Read the White Paper