Machine learning is coming to analytics but there are hurdles to overcome first

May 16, 2019, Denver, Colorado -

The sophistication of energy firms’ analytics has increased substantially in recent years, thanks to a ramp-up in available data, increased computational power through cloud computing and a hike in statistical power through the integration of offerings such as the open-source language R. The next stage in the race to gain a competitive advantage will involve applying machine learning to data, says Aiman El‑Ramly, chief operations officer at Zema PowerGroup – a data software and consulting firm that specialises in energy and commodities. The firm, which launched its Zema data integration and analytics platform 20 years ago, provides across-the-board commodities data and helps firms achieve their analytics goals.

While machine learning offers huge potential for analytics development, it is fraught with challenges at this stage, says El‑Ramly.

Read more about The advance of analytics.

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