Intelligent Lakehouse Framework
Portable by Design – Unified Analytics Anywhere
What is a Lakehouse?
A Lakehouse combines the strengths of Data Lakes and Data Warehouses into a single platform.
It bridges the gap between two key user communities:
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Data Analysts & BI Users who rely on SQL-based tools for reporting and dashboarding.
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Data Scientists & Engineers who need flexible, scalable platforms like Apache Spark for machine learning, real-time processing, and advanced analytics.
A Lakehouse delivers structured and unstructured data in one unified platform, enabling AI-powered, real-time, and business-ready insights.
Why Choose the EnablerMinds Portable Lakehouse Framework?
Our framework is designed from the ground up for flexibility, reusability, and speed – no matter your technology stack.
Production Grade simply works at scale with high cost efficiency
Methodology and deployed technologies for the framework follow industry standards for optimal and cost-efficient usage allowing room for ample growth.
Lower entry barrier to integrate new sources data
Out of the box connectors for most common data sources used in organizations and config driven with generic reusable pipeline templates approach allows for faster onboarding of new sources as well as new objects from both existing or new sources by just registering the configs and triggering the pipelines.
Faster Time to Market
With out-of-the-box framework modules covering the entire data lifecycle—from ingestion to delivery—the solution enables faster provisioning of data and use cases. This makes data readily available for diverse consumption needs and significantly reduces time to market for business analytics.
Business friendly data access powered by AI based Natural Language Interface and SQL tools
Empowers business users with desired tools they need for easier data access without having to learn the technologies underneath to allow them to focus on generating business value rather on technical exploration.
DevOps Enabled
All framework components—including code, configurations, and metadata—are fully version-controlled and adhere to software development best practices. This includes unit testing, CI/CD pipelines for automated build, test, and deployment processes, and structured release management with traceable promotion across environments.
✅ Portable by Design. Runs seamlessly on:
Modular and platform-agnostic by architecture – bring your own cloud,
we bring the framework.
Core Capabilities
🔹 Metadata-Driven Architecture
Quickly onboard new data sources just by updating configurations – not code.
🔹 Out-of-the-Box Connectors
Instant integration with SFTP, APIs, Salesforce, Oracle, Teradata, and more.
🔹 Reusable Data Pipeline Templates
Pre-built ingestion and transformation templates save development time and reduce errors.
🔹 Prebuilt Commonly used Functionalities
Prebuilt modules for generic json flattening, data format conversion (csv to delta lake), data consolidations (merges of increments), anonymization, data quality checks, schema validation, schema evolution, etc.
🔹 DevOps-Baked-In
Version control, CI/CD, infrastructure-as-code, and automated deployments for agile delivery.
🔹 Enterprise-Grade Security
Data masking, encryption, role-based access, and integration with your platform’s security layer.
🔹 Governance & Observability
Automated lineage, data quality checks, and pipeline monitoring dashboards built in.
Business Benefits
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Rapid Development
Minimal coding effort using predefined metadata and templates.
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Cloud & Platform Agnostic
Set up on your own preferred cloud or on-prem Kubernetes environment.
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Cost-Efficiency
Choose the most cost-effective engine (e.g. Spark vs SQL) for each workload.
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Secure & Compliant
End-to-end encryption, masking, and governance.
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Business-Ready
From raw data to consumable products through a layered architecture for all analytics use cases.
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AI-Ready
Designed to facilitate advanced analytics use cases including Machine Learning and AI use cases.