Item: Matillion
Rating: 9
Author: Verified User

Use Cases and Deployment Scope

Matillion is used to transform data from organizations transactional systems, sales and marketing systems and logistics. Data is transformed to create data assets that are easily consumed by users to take critical business decisions and also report operations and trend analytics. Matillion is also used to feed data into other systems that do not currently provide direct connectivity from various other applications. Matillion is also used to create and support a hub/spoke model for data assets that we have for self service reporting within different business units

Pros and Cons

Transformation of data
Efficient SQL query generation passed down to DB engine
Structured and unstructured data handling options
Data exploration and data transformation option availability

Monitoring and reporting on errors
Expansive API profile options
Data quality testing / monitoring options
Extended grid iterator limits

Key Insights

Do you think Matillion delivers good value for the price?

Yes

Are you happy with Matillion's feature set?

Yes

Did Matillion live up to sales and marketing promises?

Yes

Did implementation of Matillion go as expected?

Yes

Would you buy Matillion again?

Yes

Return on Investment

Reduced time taken from conceptualization to proof of concept
Robust data pipelines
Stable uptime and performance
Minimal maintenance required for Matillion itself.

Usability

Easy to follow steps in building a data pipeline. We have brought in people with minimal SQL experience and they have been able to quickly and successfully being able to pick up the skill set and contributing in reducing the time to market with various data assets. Matillion does provide a long array of components to select from to perform data transformation. But like any other tool, there are more than one way of doing the same thing. Some are more performant than the others, but easy to follow and easy to tweak to improve.

Time to Value

We were able to implement Matillion for our development environment in about a weeks time. There was some learning involved but the application was implemented within a weeks time. It took us about 2 more weeks to build some standards around and understanding how to use Matillion as an enterprise wide tool for data transformations.

Scalability

There are multiple options to connect with Matillion in terms of sources and targets and the connections have been robust.
There are also options for out of the box API that can be called through Matillion, but the list can be longer to cater for the more popular data providers. Matillion does also offer an option to build your own API profiles, but the information to do that can certainly be improved upon and on our talks with the vendor, it is in the works.

Alternatives Considered

Pentaho, AWS Glue and ThoughtSpot

Overall had a better value for money

Other Software Used

Qlik Replicate, Snowflake, Microsoft Power BI, AWS Single Sign-On

Likelihood to Recommend

It does a great job in data transformations with easy to understand and follow steps, if done correctly. It allows you to check data samples within each step and allows to analyze what query is going to be passed down to the engine to cater for performance improvements. Performance of going through millions of rows of data is quite amazing. So far we have had minimal down time and maintenance windows.

Matillion Transforms Data Quickly and is reliant

Overall Satisfaction with Matillion