Oracle Energy North America

Liberty Energy

IT Operations Automation · Real-time Analytics · Supply Chain Optimization

Liberty Energy needed to connect siloed finance, workforce, supply chain, and field-equipment data so it could optimize trucking and rail logistics, analyze profitability in real time, and keep operating control while scaling a high-growth energy services business that processes about 1 GB of equipment data per hour.

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Analytics that previously took days are now available in seconds

Company scaled beyond 700% growth

Lakehouse scaled to over 50 TB of data

Manual reporting and reconciliation effort reduced by 30%

Reported impact

Business outcome

Liberty Energy cut manual reporting and reconciliation work by 30%, reduced analytics latency from days to seconds, scaled its lakehouse beyond 50 TB while supporting more than 700% growth, and improved hiring and operational decision-making on one multicloud AI and analytics foundation.

Solution

Liberty Energy standardized core business processes on Oracle Fusion Cloud ERP, EPM, SCM, and HCM, then extended that foundation with Oracle Fusion Agentic Applications and an Oracle Autonomous AI Lakehouse on OCI. The lakehouse centralizes finance, operations, supply chain, and workforce data alongside petabyte-scale field information using OCI Object Storage, Oracle AI Data Catalog, and open Apache Iceberg tables that ingest data from AWS, Azure, MongoDB, Postgres, and Amazon databases. OCI GoldenGate and Oracle Data Integrator replicate data in near real time, while Oracle Analytics Cloud and Oracle Essbase expose field revenue, inventory, cost, and profitability metrics to decision-makers. Oracle APEX and Oracle Autonomous AI Database support low-code extensions, and Primavera tools add project planning and maintenance management. Together, the platform turns multicloud operational data into analytics and agentic automation across business functions.

Data flow

Finance, supply chain, workforce, and field-equipment data from Fusion applications plus AWS, Azure, MongoDB, Postgres, and Amazon data stores are ingested through OCI GoldenGate and Oracle Data Integrator into Oracle Autonomous AI Lakehouse and OCI Object Storage; Oracle Analytics Cloud and Essbase expose profitability and operations views, while APEX and agentic apps automate downstream business workflows.

Solution architecture

12 components · 3 layers

Ingest
- OCI GoldenGate Replicates source data into the lakehouse in near real time as new operational data arrives.
- Oracle Data Integrator Brings additional enterprise data sources into the platform and helps incorporate new metrics at scale.
Storage
- Oracle Autonomous AI Lakehouse Centralizes finance, operations, supply chain, and workforce data into a scalable analytics and AI platform.
- OCI Object Storage Stores large-scale lakehouse data used in Liberty's AI and analytics environment.
- Oracle Autonomous AI Database Backs APEX and PaaS extensions with autonomous database services inside Liberty's multicloud AI platform.
Serving
- Oracle Fusion Cloud Enterprise Resource Planning (ERP) Runs core finance and cost-management processes that feed Liberty's profitability and operational analytics.
- Oracle Fusion Cloud Enterprise Performance Management Supports planning and predictive profitability analysis across the energy services business.
- Oracle Fusion Cloud Supply Chain and Manufacturing (SCM) Standardizes supply chain and inventory processes that are analyzed against field activity and logistics costs.
- Oracle Fusion Cloud Human Capital Management (HCM) Captures workforce data used for recruiting, onboarding, and peak-labor planning.
- Oracle Fusion Agentic Applications Adds AI-driven automation and decision support across enterprise workflows tied to the Fusion data foundation.
- Oracle Analytics Cloud Delivers real-time revenue, inventory, cost, and profitability dashboards to business leaders.
- Oracle APEX Supports low-code extensions that automate recruiting, onboarding, and operational workflows.

Architecture clues

Low-code APEX apps and PaaS extensions automate recruiting, onboarding, and operational workflows
Near-real-time replication is handled with OCI GoldenGate and Oracle Data Integrator
Open Apache Iceberg tables are used for multicloud ingestion

Evidence from the source

Liberty Energy’s lakehouse platform with Oracle AI Data Catalog and OCI Object Storage has scaled to over 50 TB of data.

Standardizing on the Oracle solution reduced manual reporting and reconciliation effort by 30% and helped Liberty Energy scale beyond 700% growth.

The company stores many petabytes of data and collects and processes roughly 1 GB of data per hour from critical field equipment around the world.

Transparency Evidence & methodology 100/100 reference value · 74% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value100/100

Problem clarity20/20
Measures whether the customer's operational problem is specific enough to compare.
Implementation depth25/25
Rewards named components, data flow, integrations, and architecture detail.
Outcome specificity20/20
Measures whether the reported benefit is concrete rather than a generic claim.
Quantified impact25/25
3 metrics describe measurable impact.
Deployment scale10/10
Rewards evidence of a live or scaled deployment and meaningful integration scope.

Evidence confidence74%

Source authority20/25
The main evidence is an official vendor-published customer story.
Claim traceability21/25
10 of 12 key fields link to a named source.
Direct evidence15/20
3 direct source quotes retained.
Date provenance0/10
The publication date has no documented provenance.
Source transparency8/10
1 source reference document publisher, URL, authority, retrieval, and supported fields.
Implementation specificity10/10
Rewards source-backed components, data flow, quantified impact, and a specific outcome.

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

Oracle
Liberty Energy customer story

First-party
https://www.oracle.com/customers/liberty-energy/

Source type
Vendor-published customer story
Supports
- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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