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Data analytics in Energy and Natural Resources

Unlock Enormous Value From Your Energy and Natural Resources Industry Data

OmniSci enables you to interpret your largest energy and natural resources datasets visually with advanced energy data visualization.  
Instantly interact with time-series data in a geospatial context to determine productivity drivers, assess suitable land, and understand benchmark performance.

Learn how interactive spatiotemporal data analytics in energy can transform your organization today. 

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Energy Data Analytics Software That Industry Experts Trust

USE CASE IN OIL AND GAS

Take Action on Upstream Production Data

OmniSci and IHS Markit help industry professionals understand why wells are over or underperforming their estimated potential, compare daily drill and well performance, and evaluate production trends across basins.

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Big Data Energy Analytics Demo

Interactively explore a US oil and gas industry dataset from MineralAnswers covering 300 million well production records from 1.3 million wells, spanning 20 years. Using OmniSci's advanced energy data analytics software you can analyze production decline, performance, correlations, rate of change, and compile formation-based type curves in seconds.

USE CASE IN RENEWABLE ENERGY

Evaluate Optimal Renewable Resource Sites Upstream

Big data analytics in renewable energy: An industry leader uses OmniSci to interactively assess the profitability of land using massive multi-sourced datasets representing location, time, landscape, and weather to determine where their customers should make wind, solar, biomass, hydroelectric, or geothermal energy investments.

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USE CASE IN OIL AND GAS

Broker Energy Acquisitions Downstream

Oil and gas data analytics: OmniSci has partnered with an industry expert to accelerate the brokerage of diversified energy acquisitions by allowing professionals to connect energy buyers and sellers quickly and interactively pinpoint market opportunities buried in vast, disparate data sources.

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Use case

Optimizing 5G Network Architecture

Modern 5G network development requires efficient, cost-effective placement of cellular equipment to maximize network performance and return value on significant capital investments. With OmniSci, telecommunication network operators, engineers, and data scientists can analyze and visualize complex data records at scale. They can layer their existing network data sets with modeling and coverage analysis and rapidly run millions of complex calculations aimed at reducing interference between the innumerable towers of 5G networks.

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Use case

Customer Churn Analysis

Acquiring new customers can cost up to 25 times more than retaining existing ones. Carriers rely on data analytics around demographics, usage, connectivity, network performance and reliability, and more, to reduce their customer churn rates. Yet the scale of this data is too vast for their existing analytics tools, which limits telco customer churn analysis from quickly running ad-hoc queries or visualizing and dashboarding customer data in its entirety. With OmniSci, analysts can rapidly visualize billions of records to spot anomalies and immediately drill down to specific network issues that can cause customer churn.

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Use case

Special Event Performance
& Network Monitoring

Special events, such as concerts and conferences, are bandwidth-heavy as customers upload photos, videos, and even live streams of their experience. This requires real-time network monitoring to adjust resources and spot anomalies before they become outages. Yet the ability to layer these disparate, high volume data sets is beyond the capabilities of traditional analytics platforms. With OmniSci, telecommunication network operators can derive real-time insights from real-time events. This allows them to rapidly understand complex customer experiences and perceptions, fine-tune, and optimize their networks to manage the load.

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Benefits of OmniSci's Energy Analytics Tools

Accelerated Insights

Harness the power of GPU and CPUs for query compilation, query vectorization, and advanced three-tier memory management.

Data Accessibility

Layer multiple data sets for new context, and leverage our data catalog for streamlined access to curated data sets.

Limitless Exploration

Seamlessly switch to python, including JupyterLab, and continue to explore your energy data set with your familiar data science tools.

Location Intelligence

Bring spatiotemporal data to life with native support for interactively querying, filtering and visualizing it in milliseconds.

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