Research has found that enterprise data engineers spend 44% of their time building and maintaining ETL pipelines, costing on average $520,000 USD per year. Complexity of data pipelines and infrastructures brings challenges every step of the way for data engineers, including siloed data, slow performance, and high-maintenance needs, resulting in cost and performance issues and blocking business opportunities.
Watch this fireside chat discussion between guest speaker Noel Yuhanna, VP, Principal Analyst at Forrester, and David Libesman, VP of Data Analytics at iPipeline. We will discuss the top challenges and trends we see in the data engineering world. And you will also learn how modern data engineering can not only improve productivity and performance for data engineering teams, but also drive beneficial impact to the entire business, from improving operational efficiency to driving new business outcomes.
Watch this on-demand webinar to learn:
- The top challenges and trends in data engineering
- How data engineers’ productivity can be improved by 66%
- What benefits modern data engineering practices can bring to the entire organization
- How businesses achieved 616% ROI in three years
“We’ve consolidated 10 ETL processes into one straightforward process using all native AWS tools that loads and transforms JSON data in Snowflake.“ – Greg Wellbrock, AVP of Data Operations, iPipeline