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What You'll Learn
Enterprise Resource Planning (ERP) systems lie at the heart of modern business operations, integrating finance, supply chain, HR, sales, manufacturing, and customer service into a unified platform. Traditionally, ERP data is stored and processed within monolithic systems such as SAP, Oracle, Microsoft Dynamics, or Infor. While these systems manage transactions effectively, they have historically fallen short in delivering real-time analytics, advanced AI capabilities, and cross-platform data interoperability.
Databricks, built on a Lakehouse architecture, introduces a new paradigm: merging data engineering, data warehousing, and machine learning into a single, governed platform. When used alongside ERP systems, Databricks transforms ERP data into a strategic asset, enabling predictive analytics, process optimization, and real-time operational intelligence at scale.
Why Do Enterprise Resource Planning Systems Need a Lakehouse?
Enterprise Resource Planning systems produce high-value operational data, but several challenges limit its strategic potential:
1. Data Silos and Fragmentation
Organizations commonly operate multiple ERP modules or even multiple ERP platforms across regions and business units. Integrating these datasets is often costly and complex.
2. Limited Analytical and AI Capabilities
ERP databases are optimized for transactions (OLTP), not analytics (OLAP) or machine learning workloads. Advanced forecasting or optimization is typically offloaded to separate tools, creating latency and governance issues.
3. High Cost and Rigidity of Traditional Warehouses
Legacy enterprise data warehouses are expensive to scale and inflexible when ingesting new ERP data types such as unstructured logs, IoT signals, or external market data.
Also watch our webinar on: From Legacy to SaaS: Your MDM Modernization Journey Explained
4. Real-Time Needs Exceed Traditional Architecture
Modern enterprises require real-time inventory visibility, dynamic pricing, predictive maintenance, and anomaly detection, capabilities that conventional ERP analytics cannot support natively.
Databricks Lakehouse: A Unified Platform for Enterprise Resource Planning Modernization
Databricks addresses ERP challenges through a single platform that combines:
- Data ingestion & ETL (batch + streaming)
- Governed data storage via Delta Lake
- Data warehousing with Databricks SQL
- Machine learning & GenAI with Foundation Models
- BI and real-time dashboards
- Open data sharing with Unity Catalog
This enables organizations to create an open, scalable, and AI-ready digital core surrounding their ERP system.
Integrating Enterprise Resource Planning Systems with Databricks
Databricks integrates with major ERP systems in multiple ways:
SAP
- SAP ODP, SAP SLT, and SAP CDC connectors
- Partner tools (Qlik, Fivetran, Informatica)
- Direct extraction from SAP BW, ECC, and S/4HANA
Oracle ERP Cloud
- REST and SOAP APIs
- Oracle Fusion connectors via partner ETL
- JDBC-based extraction from on-premises Oracle EBS
Microsoft Dynamics 365
- Dataverse connectors
- Event-driven ingestion via Azure Event Hub
Databricks then stores this ERP data in Delta Lake for downstream analytics, ML, and BI.
Key Use Cases: Enterprise Resource Planning + Databricks
Financial Analytics & Forecasting
- Cash flow forecasting using ML
- Automated variance analysis
- Real-time profitability dashboards
- Faster month-end close via reconciled, unified data
Supply Chain Visibility
- Demand forecasting using MLFlow models
- Inventory optimization via real-time signals
- Supplier risk scoring using NLP and external data
- Conveyor, fleet, and IoT integrations without schema limitations
Manufacturing Intelligence
- Real-time quality monitoring
- Preventive and predictive maintenance
- Yield and throughput optimization
- Root cause analysis using unified plant + ERP data
Also watch our quick demo on: AI Agents in Databricks
Sales & Customer Experience
- Unified customer 360 across ERP, CRM, e-commerce
- Predictive revenue forecasting
- Price optimization and discount recommendations
- Order fulfillment optimization
Human Capital Analytics - HCM
- Attrition risk modeling
- Workforce planning
- Skills inference using LLMs
- Payroll and labor cost forecasting
AI & GenAI for Enterprise Resource Planning Data
With Databricks’ Mosaic AI and the lakehouse, enterprises can apply advanced AI to ERP data:
Intelligent Automation
- Automated invoice classification
- AI-assisted procurement workflows
- Chatbots that query ERP data using natural language
AI-Powered Forecasting
- More accurate demand and supply forecasting
- Production scheduling recommendations
- Automated anomaly and fraud detection
Natural-Language Insights
- CFO and COO copilots powered by LLMs
- Automated reporting from ERP transactions
- Interactive, conversational analytics
Also read about: Best Steps for Hadoop to Databricks Migration
Governance & Security with Unity Catalog
Given the sensitivity of ERP data, governance is critical. Unity Catalog provides:
- Centralized identity and access management
- Fine-grained column- and row-level security
- Data lineage across ingestion to AI models
- Audit logs and compliance-ready controls
This ensures ERP data remains controlled, traceable, and fully compliant with enterprise policies.
Also read about: What Is Dynamic View Access Control in Databricks?
Architectural Blueprint: Enterprise Resource Planning + Databricks
- Ingestion Layer: Streaming and batch ingestion from ERP APIs, CDC, and ETL tools.
- Bronze Layer (Raw Data): ERP tables and logs landed in Delta Lake.
- Silver Layer (Cleaned + Conformed): Harmonized master data: products, customers, vendors, ledgers, BOMs, etc.
- Gold Layer (Business Models): Finance, supply chain, and sales data models optimized for BI and AI.
- AI/ML Layer: MLFlow-tracked models for forecasting, optimization, and NLP.
- Consumption Layer: Databricks SQL, Power BI, Tableau, Looker, custom apps, or API endpoints.
Business Outcomes
Organizations that combine ERP with Databricks typically achieve:
- 40–70% faster reporting cycles
- 20–50% improvement in forecast accuracy
- 5–15% reduction in supply chain costs
- Reduced ERP workload and storage costs
- Accelerated digital transformation and AI-readiness
Conclusion
Enterprise Resource Planning systems remain essential for transactions and core business processes, but the future of enterprise operations requires real-time intelligence, predictive analytics, and flexible data architecture.
By integrating ERP platforms with the Databricks Lakehouse, organizations unlock:
- A unified, trusted source of truth
- Scalable analytics and AI at low cost
- More agile and data-driven business decisions
- The foundation for an intelligent, autonomous enterprise
Also read about: Databricks Data Intelligence Platform
About LumenData
LumenData is a leading provider of Enterprise Data Management, Cloud and Analytics solutions and helps businesses handle data silos, discover their potential, and prepare for end-to-end digital transformation. Founded in 2008, the company is headquartered in Santa Clara, California, with locations in India.
With 150+ Technical and Functional Consultants, LumenData forms strong client partnerships to drive high-quality outcomes. Their work across multiple industries and with prestigious clients like Versant Health, Boston Consulting Group, FDA, Department of Labor, Kroger, Nissan, Autodesk, Bayer, Bausch & Lomb, Citibank, Credit Suisse, Cummins, Gilead, HP, Nintendo, PC Connection, Starbucks, University of Colorado, Weight Watchers, KAO, HealthEdge, Amylyx, Brinks, Clara Analytics, and Royal Caribbean Group, speaks to their capabilities.
For media inquiries, please contact: marketing@lumendata.com.
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