Data Platform: Your Data Foundation for AI

Transforming operations with AI begins with the most critical asset: your data. But in most organizations, data is fragmented across dozens of systems, making it nearly impossible to establish a trusted, unified view. The Arkham Data Platform is engineered to solve this foundational challenge. It is one of the core pillars of our platform, designed to unify your disparate data sources into a single source of truth, ready for advanced analytics and AI.

Instead of wrestling with a complex web of commodity cloud services, Arkham's architecture provides builders with a fully-managed, UI-driven environment to move from raw data to production-ready assets with unparalleled speed. The integrated toolchain—Connectors, Pipeline Builder, Data Catalog, Playground, and our AI copilot TARS—empowers your teams to focus on creating value, not managing infrastructure.

A Framework for Integrated Data Workflows

Our Data Platform is built on three foundational pillars that work in concert to deliver reliable, AI-ready data.

• Data Connectivity: We provide a comprehensive suite of managed Connectors to reliably and automatically ingest data from any source system. This eliminates the need for brittle, custom ingestion scripts and accelerates the first mile of any data project.
• Data Transformation: The Pipeline Builder offers a transparent, visual environment for transforming raw data into clean, production-grade assets. By representing logic as a graph, we make data lineage explicit and data quality easier to manage.
• Data Management: At the core of the platform is the Data Catalog, which provides a governed, three-tiered registry for all data assets. Powered by our Lakehouse architecture, this ensures every dataset is versioned, auditable, and secure.

Core Components

Our Data Platform is comprised of several integrated services that work together to deliver on the promise of a unified data foundation.

• Connectors: Automate data ingestion from any source system with a library of pre-built, production-grade integrations.
• Pipeline Builder: A visual, canvas-based environment for orchestrating complex data transformation pipelines.
• Data Catalog: The centralized registry for discovering, understanding, and governing all data assets in your organization.
• Playground: An interactive SQL editor for exploring and validating trusted, production-ready datasets.
• Lakehouse: The underlying storage and compute architecture that guarantees data quality, reliability, and performance across the platform.

Core Concepts

The Builder's Workflow: From Ingestion to Insight

Our architecture enables security, reliability and operational excellence in data workflows by design. The following diagram illustrates this prescriptive path, from initial data connection to final consumption, bringing all the core components together in a unified workflow.

• Automated Ingestion: Your journey begins in Connectors, where you configure connections to your source systems through a simple UI. Arkham handles the managed ingestion, reliably landing your raw data into a Staging dataset in the Data Catalog. This gives you an immediate, queryable snapshot of your source data without any manual scripting.
• Visual Transformation: With your data in the Staging Tier, you use the Pipeline Builder to clean, join, and aggregate it. This canvas-based tool lets you visually construct complex transformations. As you build, each transformation can be previewed, validated, and saved. The final output is published as a clean, reliable Production dataset, again, automatically registered in the Data Catalog.
• Instant Discovery and Exploration: The Data Catalog acts as your central registry, automatically indexing both your Staging and Production datasets. From the catalog, you can see dataset schemas, track lineage, and manage access. For immediate validation or ad-hoc analysis, you can jump directly into the Playground, an integrated SQL environment, to query any dataset.
• Consumption & Enrichment: Your high-quality Production datasets are now the trusted foundation for all downstream applications. They are consumed by the integrated AI Platform to train models and by business intelligence tools for analytics. In turn, the AI Platform produces new, valuable ML Model Datasets (e.g., predictions, performance metrics) that are registered back into the Data Catalog, creating a virtuous cycle of data enrichment.

This prescriptive workflow ensures that your data is always governed, your pipelines are robust, and your development cycles are short, enabling you to build and iterate faster.

Related Capabilities

The Data Platform serves as the foundation for several other key capabilities in the Arkham ecosystem.

• AI Platform: Consumes production-grade datasets from the Data Platform to train models and generate insights.
• Ontology: Maps objects and metrics to the trusted datasets curated by the Data Platform.
• Governance: Provides the framework for securing and auditing all assets created and managed within the Data Platform.
• TARS: Our AI Co-pilot assists in every component of the Data Platform, from generating SQL to explaining pipeline logic.