Databricks delivers enhanced data analytics and intelligence for the energy sector – SiliconANGLE

Big-data company Databricks Inc. today announced the immediate availability of a dedicated data intelligence platform for the energy industry, designed to enable customers in the energy sector to harness enormous streams of data and use them for business insights and to feed generative artificial intelligence workloads.

The Databricks Data Intelligence Platform for Energy, as it’s officially known, is also geared toward confidentiality, enabling energy suppliers to use their most sensitive information without any risks around privacy, the company said.

The main idea is that the offering will give energy company leaders a more holistic, real-time view of their operations, helping them tackle the most critical challenges for the energy industry, such as real-time asset performance, management and maintenance. For instance, energy providers can more effectively gather, analyze and visualize the sensor-based data from physical assets such as grids, wind turbines, pipelines and machines, and use this information to monitor their performance in real time.

It will also support enhanced energy forecasting, the company said, minimizing uncertainty. It helps to tame the wildly unpredictable nature of wind, solar and hydropower sources, combining sophisticated machine learning algorithms with weather forecasts, performance data, pricing trends and demand projections. This will help energy providers more accurately predict and manage demand and thus enhance their resource allocation to maximize profitability.

Customers will also be able to use the platform to adopt a more proactive and predictive approach to grid optimization. By deploying Advanced Metering Infrastructure, utilities providers will be able to take advantage of advanced analytics and predictive modeling that delivers real-time visibility into the state of their grid operations. In turn, that means better load forecasting, the ability to predict outages more accurately and therefore balance supply and demand, improving the overall stability of their grids.

Databricks said its platform will become an essential tool for energy providers which are shifting towards smarter, cleaner and more reliable sources of energy. According to the company, renewable energy sources now account for almost 30% of the world’s power. But the unpredictable nature of these sources means energy providers need better intelligence to manage them efficiently.

Shiv Trisal, Databricks’ global industry leader for energy and manufacturing, said the most successful energy suppliers in future will be those that leverage data, analytics and AI to minimize risk and tap into new opportunities created by the transition to more renewable energy. “This requires a different approach towards data intelligence that puts the power of AI in the hands of every user regardless of technical ability, allowing them to unlock unique insights from the company’s full knowledge base and data to power new innovations and shape a smarter, reliable and sustainable energy system for all,” he said.

Global energy suppliers such as the Australian Energy Market Operator, Chevron Phillips Chemical Co. LLC., Cosmo Energy Group Holdings Ltd., Octopus Energy Group Ltd., Shell International B.V., TotalEnergies SE and Wood Mackenzie Ltd. are among the early adopters. The general reception has been positive, with Dan Jeavons, vice president of digital innovation at Shell, hailing the platform’s “transformative” power. “With Databricks, we’ve accelerated our data analytics and AI capabilities, helping to unlock real-time insights that drive strategic decisions and create process improvements, cost reductions and production increases,” he said.

Databricks Data Intelligence for Energy is built atop the company’s Data Lakehouse architecture platform and has been enhanced with generative AI capabilities, Trisal explained in a blog post. Generative AI enables a number of packaged use case accelerators that can help companies jumpstart their analytics operations.

For example, there’s an LLMs for Knowledge Base Q&A Agents accelerator that can help energy firms to quickly build large language models to power chatbots trained on industry context, to act as a kind of personalized assistant for energy sector workers. The IoT Predictive Maintenance accelerator will help energy suppliers get started in ingesting real-time sensor data from field devices, so as to maximize uptime and minimize the costs of maintenance.

Other use case accelerators include digital twins of physical assets such as wind turbines to enhance predictive modeling, and grid-edge analytics for the optimization of energy grid performance.

Octopus Energy Head of Data David Sykes said Databricks has played a key role in transforming its energy systems by processing the massive amounts of data created by its smart-meter installations across homes in the U.K. “By gaining deeper insights into customer behavior and energy consumption, we can continue to create innovations and services our customers love so much, and ultimately drive the green energy revolution globally,” he said.

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