MineralAnswers.com Provides the First Nationwide Oil & Gas Data Solution on Snowflake
MineralAnswers.com, a new knowledge platform for energy information, announced its data products are available on Snowflake Data Marketplace, where organizations can find, share and list data to achieve crucial business insights. Snowflake, the Data Cloud, provides the platform where users such as data scientists, business intelligence analysts and analytics professionals, can leverage MineralAnswers.com data within Snowflake Data Marketplace to enrich their own data with MineralAnswers.com public or premium oil and gas insights.
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The datasets now available on Snowflake Data Marketplace include some of MineralAnswers.com most sought-after data products, including:
- Raw Regulatory Oil and Gas Data – The raw datasets for permits, operators and wells across 20 U.S. states.
- Permits (Premium) – Drilling permits for planned well spots in the U.S.
- Advanced Permits (Premium) – Drilling Permits with our drilling propensity insight scores to forecast the likelihood a permit gets drilled.
- Production (Premium) – Monthly production reported on a lease basis with well level allocation.
- U.S. Analytics Ready (Premium) – All producing wells in the U.S., with over 30 analytics variables pre-built in.
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Snowflake users can browse the MineralAnswers.com datasets on Snowflake Data Marketplace and contact MineralAnswers.com if they would like to sample the data. If users decide to purchase data, it is delivered to them via Snowflake’s secure platform for easy integration into their analytics processes.
“MineralAnswers.com has compiled a vast amount of oil and gas, energy and infrastructure intelligence that enable companies to efficiently power their analytics, AI and machine learning capabilities,” said Jeff Chambers, founder and CEO of MineralAnswers.com. “Being able to provide our data through Snowflake Data Marketplace opens tremendous opportunities for other companies to leverage the data cleansing work we’ve done, so they can spend more time on analysis and less on data cleanup and feature engineering.”
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