Energy, the driver of the global economy, is undergoing one of the largest secular shifts of our time, propelled by hundreds of trillions of dollars in global investment in the next 25 years. This shift creates a tremendous opportunity for energy companies. And, at the heart of successfully navigating this change sit data and AI.
As energy companies strive to thrive in this new landscape, they face several critical challenges:
Digitizing aging infrastructure: Grids and oil wells that were built decades ago need to be upgraded and digitized. On top of this, with the deployment of millions of wind turbines, solar panels and electric vehicles, energy companies must integrate operational technology (OT) with information technology (IT) data. The result is an influx of zettabytes of data, requiring efficient ingestion, cleaning and analytics to optimize operations.
Managing market volatility and financial exposure: Extreme weather, geopolitical instability and more variable renewables are contributing to increased volatility in commodity markets, including power, gas and oil. This unpredictability necessitates sophisticated data analytics to mitigate risks and stabilize financial performance.
Adapting to changing customer demands: The energy transition brings with it evolving customer expectations. Corporations seek quantitative data for environmental, social and governance (ESG) reporting, while end consumers demand intuitive, user-friendly home energy systems that are as easy to use as their smartphones.
With Snowflake’s AI Data Cloud for Energy, energy companies can digitize physical infrastructure, thrive in volatile market conditions and deliver new and improved customer experiences. With the AI Data Cloud for Energy, including Snowflake and partner-delivered solutions as well as industry-specific data sets, energy companies can drive significant improvements in agility, collaboration and visibility across their entire value chain.
Key features of Snowflake’s AI Data Cloud for Energy:
Data unification and collaboration: Facilitate secure and scalable collaboration with partners, suppliers, data providers and customers
Advanced analytics and AI: Utilize sophisticated AI and analytics tools to optimize operations and decision-making
Industry-specific solutions: Access tailored solutions and data sets designed to address the unique challenges of the energy sector
With the AI Data Cloud for Energy, companies in the Oil & Gas and Power & Utilities industries can leverage data analytics in three strategic areas:
Assets and Operations: By integrating OT and IT data, energy companies can utilize solutions to ingest Internet of Things (IoT) data, identify anomalies, schedule predictive maintenance and optimize work schedules. Snowflake Cortex, in conjunction with connectors from various industrial software partners, facilitates comprehensive analytics across the enterprise. As an example, this solution shows how to provide field crews with repair suggestions, based on equipment manuals and historical error resolution logs.
Markets and Finance: Snowflake Marketplace provides a platform to unify market data across multiple commodities. With Snowflake’s MLOps, companies can develop precise forecasts to inform trading and portfolio management decisions. They can also leverage Snowflake’s single integrated platform for a single source of truth for financial reporting and enhancing energy trading and risk management. As an example, this solution shows how to forecast electricity prices in Texas, using data from Snowflake Marketplace and Snowflake’s AI/ML capabilities.
Customer 360: Combining their customer data from various platforms, energy companies can harness generative AI to create personalized “next best actions” (NBA). Snowflake’s Cortex Copilot and Analyst streamline staff operations by summarizing key insights, while Streamlit in Snowflake enables rapid development and deployment of new offerings. As an example, this solution shows how to use Snowflake’s Cortex LLM functions to predict customer sentiment based on product reviews.
Several leading energy companies are leveraging Snowflake’s AI Data Cloud to achieve transformative business outcomes:
EDF: One of the UK’s largest energy suppliers for homes and businesses used Snowflake and its Snowpark Python development framework to build a complete machine learning operation platform in a few months, delivering data products that lead to higher customer satisfaction and retention.
ExxonMobil: The global energy supermajor uses Snowflake as its enterprise data platform, streamlining supply chain operations and driving strategic insights in its sustainability efforts.
IGS Energy: The retail energy provider of electricity and gas in the Midwest U.S. leverages Snowflake to identify underperforming rooftop solar PV installations and to forecast electricity consumption across 1 million homes.
Snowflake Marketplace extends the value of the AI Data Cloud by offering a variety of data and data applications. Key data providers include S&P Global Commodities, Yes Energy, Grid Status, Amperon, Arcadia, AccuWeather, Vaisala and Weathersource. Applications, like Maxa’s application to integrate data from multiple ERPs and Bidgely’s electricity demand disaggregation, run natively within Snowflake, providing tailored solutions for energy companies.
Snowflake’s AI Data Cloud for Energy not only unlocks the potential of data, it’s a strategic enabler that positions energy companies at the forefront of the energy transition, ready to capitalize on new opportunities and drive sustainable growth.
To learn more about how Snowflake can help your company navigate the energy transition, visit Snowflake for Energy.
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