The death of DIY data pipelines
How building data pipelines decelerates your data team
July 23, 2024
10 a.m. BST
Virtual
Dominic Orsini
Explore the scalability conundrum of DIY data pipelines in modern data architectures
Weigh the pros and cons of build vs. buy, from control to costs
Unveil the cutting-edge alternative to DIY pipelines, and how to make the switch seamlessly
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Traditionally, organizations constructed their own data pipelines, which proved effective in an era with fewer data sources. However, in today's data-rich landscape, an average organization aggregates data from over 400 sources. Scaling with do-it-yourself (DIY) pipelines poses a significant challenge.
While DIY pipelines may offer surface-level benefits like control and customization, they come at the expense of scalability, reliability, and maintenance costs. A data integration platform is the modern-day solution to a classic problem — nailing the sweet spot between best practices, customization and most importantly, mitigating security risks.
Explore the scalability conundrum of DIY data pipelines in modern data architectures
Weigh the pros and cons of build vs. buy, from control to costs
Unveil the cutting-edge alternative to DIY pipelines, and how to make the switch seamlessly
Dominic Orsini
Dominic Orsini
Traditionally, organizations constructed their own data pipelines, which proved effective in an era with fewer data sources. However, in today's data-rich landscape, an average organization aggregates data from over 400 sources. Scaling with do-it-yourself (DIY) pipelines poses a significant challenge.
While DIY pipelines may offer surface-level benefits like control and customization, they come at the expense of scalability, reliability, and maintenance costs. A data integration platform is the modern-day solution to a classic problem — nailing the sweet spot between best practices, customization and most importantly, mitigating security risks.