Matillion ETL Primary Use Case

Chris Hastie - PeerSpot reviewer
Data Lead at InterWorks

We primarily use Matillion ETL to effectively manage data's movement, ingestion, and transformation through pipelines. We have specific use cases that involve different types of data, but they all fall under the general bracket of data movement.

View full review »
PH
Senior Data Engineer Consultant at a tech company with 201-500 employees

We use the solution for the ETL pipelines.

View full review »
AntonHaupt - PeerSpot reviewer
Data Architect at Capitec

We use it primarily for transferring data into our cloud data warehouse and conducting research. We rely on Matillion ETL for our data integration and transformation needs, finding its user-friendly interface and robust capabilities highly effective. Essentially, we've built a cloud-based data platform using Matillion ETL to seamlessly extract data from various sources, perform necessary transformations, and store it in our cloud environment.

In our finance-focused projects, we predominantly utilize Matillion for data warehousing tasks, particularly in the realms of finance and micro-lending. While our projects may not involve big data volumes, they often entail handling intricate datasets that require sophisticated processing.

View full review »
Buyer's Guide
Matillion ETL
March 2024
Learn what your peers think about Matillion ETL. Get advice and tips from experienced pros sharing their opinions. Updated: March 2024.
763,955 professionals have used our research since 2012.
MG
Director of IT Operations at a financial services firm with 10,001+ employees

We have some very unique use cases for the solution. We are interfacing between the on-premises database and on-cloud database– Oracle and Snowflake. It is a very complex process wherein we had to ask for help from Matillion’s engineers to build it out. We're looking up our on-premises database servers for information to build our cloud database. Once we get everything copied in Snowflake, we go back to Oracle on-premises. We have created this bridge to use till we switch to AWS full-time. But right now, we don't have that in the book. So the best way to move forward is to make sure we're taking a solution that could bridge that gap, and that's Matillion.

View full review »
Sunny Kumar - PeerSpot reviewer
Specialist Programmer at Infosys

While loading data into Snowflake, I encountered an issue with the key due to the file's large size and a record count in the billions. Loading the data with a Python script was taking a long time, so I decided to explore other options. This is when I discovered Matillion ETL, which I had not heard of before. I learned more about it and used some of its features, including the Material Data Loader, to load the data into Snowflake. Using Matillion ETL, I was able to load around 770 million records in just five to ten minutes. This was a successful use case, and I have also used Matillion ETL for loading data from Amazon S3 to Snowflake and for other data-loading tasks, including connectivity to on-premise servers and different cloud platforms.

I have used on-premise and cloud deployments of this solution.

View full review »
Shehab Saad - PeerSpot reviewer
Business Intelligence Manager & Data Analytics (Retail Business) at B.TECH

We use the solution to make data transfers between our source systems and Snowflake. It's our data analytics architecture.

View full review »
SK
Data Engineer

We are using Matillion ETL for extracting and integrating the data from different applications, such as SQL, and other data sources.

View full review »
Tomáš Hronek - PeerSpot reviewer
Data Engineer at Merck

I use Matillion ETL for wrangling or transforming data from sources like S3 and Databricks.

View full review »
David Carbery - PeerSpot reviewer
Data Analytics Consultant at Snap Analytics

My primary use case involves handling standard ETL tasks. I work on processing both our company's data and third-party data sources. While I focus on these standard ETL tasks, my colleagues excel in more advanced pipeline work.

View full review »
PT
Data analyst at a tech services company with 51-200 employees

The tool's primary use case is implementing Snowflake, including building a data warehouse atop our source systems and facilitating data exchange with customers and suppliers utilizing Snowflake.

View full review »
AH
Data Architect at Old Mutual Life Assurance Company (South Africa) Limited

It is cloud native and designed to run on cloud warehouses. There is compatibility with many of the cloud data warehouses, as well as Snowflake, and any SQL data warehouse. It is not compatible with other ETL products.

View full review »
Buyer's Guide
Matillion ETL
March 2024
Learn what your peers think about Matillion ETL. Get advice and tips from experienced pros sharing their opinions. Updated: March 2024.
763,955 professionals have used our research since 2012.