Data engineers see 70% productivity increase with Matillion

Manchester (UK), Denver, CO (US) - February 13, 2024

A new research study released today reveals that data engineers saved 70% of their time managing and maintaining pipelines when using Matillion Data Productivity Cloud.

The Forrester Total Economic Impact™ study also showed a three-year 271% return on investment for users choosing the modern data pipeline platform, whilst engineers were also found to save 60% of their time spent building pipelines.

Matthew Scullion, CEO at Matillion, said: “We’ve long described Matillion as the data productivity platform, it is literally in the name of the Data Productivity Cloud.

“This study shows the substance behind that name and the material productivity gains for data engineering teams who choose to make their data business ready for analytics and AI with Matillion Data Productivity Cloud. I'm particularly delighted that this research has been done by Forrester, who are renowned for their rigour with work like this."

“Particularly in this economic climate, and particularly at a time when innovating with data is not just a desire but a visceral competitive need, enabling data engineers to ‘achieve so more with less’, whilst freeing up precious resource and time to innovate is game changing.”

The commissioned study conducted by Forrester Consulting, part of a leading research and advisory firm, on behalf of Matillion, interviewed five anonymised sources within data engineering from four customers and compiled their results into one composite organization. 

One such source, a data scientist for a global financial services organisation, said: “I’m now willing to take on more ambitious data projects. If we didn’t have a modern data stack, I would never start fine-tuning our own large language model. 

“The work required to get the data ready to do that would have been an absolute nightmare. Now, [with Matillion and more,] the upfront expertise costs of data acquisition and engineering no longer scare me away from any project.”

Increasing demand on data teams has been a growing issue, particularly as the age of AI dawns. In 2023, research by Vanson Bourne highlighted that 90% of data experts seek to alleviate workload increases from fragmented pipelines and overwhelming business demands, with 84% of respondents describing the volume of their workload as exceeding their capacity.

Scullion added: “The role of the data engineer is always shifting and evolving, and at greater pace than ever with the advent of AI. Removing the heavy lifting of data engineering and materially boosting productivity in this way, frees up engineering time to solve more business problems and innovate, including leveraging new technologies like AI.”

The full study is available at Matillion.com

ENDS

Media contact:

Alice Gibson [email protected]

Notes to editor:

Forrester Consulting Total Economic Impact(™) Study 2024 commissioned by Matillion.

Summary of key finding from the study:

• Three-year 271% ROI
• 60% time saved building pipelines
• 70% time saved maintaining and managing pipelines
• 25% lower compute and infrastructure costs
• Stronger data culture
• Increased data analyst productivity by fulfilling data requests 60% faster.
• 4 X data requests fulfilled in 3 years

About Matillion

Matillion is the productivity platform for data teams.

Matillion makes data work more productive by empowering the entire data team – coders and non-coders alike – to move, transform, and orchestrate data pipelines faster. Its Data Productivity Cloud empowers the whole team to deliver quality data at a speed and scale that matches the business’s data ambitions.

Thousands of enterprises including Cisco, DocuSign, Slack, and TUI trust Matillion to move, transform, and orchestrate their data for a wide range of use cases from insights and operational analytics, to data science, machine learning, and AI. 

Native integration with popular cloud data platforms such as Snowflake, Databricks, Amazon Redshift and Google BigQuery lets data teams at every skill level automate management, refinement, and data delivery for every data integration need.