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Octopus Energy cuts data costs 50x with Databricks pipeline overhaul

Octopus Energy has significantly reduced costs and improved efficiency in its data engineering processes by re-architecting its margin data pipelines. Facing a 48x increase in data volume due to new UK regulations (MHHS), the company's existing architecture was projected to incur substantial additional costs. By implementing a new system on Databricks, they achieved a 50x cost reduction per settlement date and processed 98.8% fewer rows, enhancing data freshness from weekly to daily. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Demonstrates how data engineering infrastructure can be optimized to handle massive data growth and reduce operational costs.

RANK_REASON Company implements significant infrastructure changes to handle regulatory data volume increase and achieve cost savings. [lever_c_demoted from significant: ic=1 ai=0.4]

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COVERAGE [1]

  1. Databricks Blog TIER_1 ·

    Scaling for MHHS: how Octopus Energy achieved a 50x cost reduction in margin data engineering

    The energy transition has a data problemThe UK's energy grid is in the middle of...