What is the Snowflake AI Data Cloud?

The Snowflake AI Data Cloud is a fully managed, cloud-native platform that unifies analytics, data engineering, AI, and applications on one foundation. It separates compute from storage, runs on AWS, Azure, and Google Cloud, and includes built-in governance (Horizon), AI (Cortex), and secure data sharing (Snowgrid).

How does Snowflake differ from Databricks?

Both are leading data and AI platforms with strong overlap. The cloud-based data platform is fully managed, SQL-first, and optimized for analytics, governance, and ease of operations. Databricks builds on Spark and is often chosen for code-heavy data engineering and ML workloads. Many enterprises run both – valantic helps you decide based on your use cases, team skills, and existing ecosystem.

What does a Snowflake implementation cost?

The cloud-based data platform follows a consumption-based pricing model: you pay for compute (per second) and storage separately. Implementation cost depends on scope – typical valantic engagements range from focused 6 to 8-week PoCs to enterprise-wide migrations spanning several months. We always start with a fixed-price assessment to give you a transparent TCO model.

How long does a migration from SAP BW or Teradata to Snowflake take?

Mid-sized SAP BW migrations typically run 4 to 9 months, depending on data volume, number of objects, and the degree of model rebuild. valantic uses accelerator-based approaches (model conversion, automated testing, dual-run validation) to reduce risk and shorten timelines significantly.

Is Snowflake GDPR-compliant and available in EU regions?

Yes. Snowflake is available in multiple EU regions across AWS, Azure, and Google Cloud (Frankfurt, Amsterdam, Dublin, and others). It supports GDPR-aligned controls including data classification, masking, row-level security, and audit trails – managed centrally through Horizon.

What is Snowflake Cortex AI and what can I build with it?

Cortex AI is Snowflake’s fully managed AI layer with industry-leading LLMs, vector search, fine-tuning, and pre-built ML functions. You can build RAG applications over enterprise documents, natural-language analytics agents (Cortex Analyst), forecasting and classification models, and Streamlit-based UIs – all without moving data outside the platform.

Activate your data

Build your unified Data & AI Platform with the Snowflake AI Data Cloud

Fragmented data and rising cloud costs slow down AI initiatives. valantic helps you build a unified, fully managed data and AI platform on the Snowflake AI Data Cloud – from data strategy and migration to a scalable foundation for analytics, AI, and apps.

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Build Your Unified Data & AI Platform with the Snowflake AI Data Cloud

When data silos slow innovation

The challenge

Companies across industries struggle to consolidate growing data volumes from operational systems, SaaS tools, and external sources into a foundation that is ready for AI. In reality, data landscapes remain fragmented: separate data warehouses, data lakes, and ML environments coexist – driving up cost and slowing time-to-insight.

At the same time, the pressure to move AI initiatives into production is rising. Many organizations face inconsistent data, weak governance, and the lack of a single, fully managed platform for analytics, AI, and data sharing.

Media disruptions are particularly common in mature system landscapes: operational data is isolated from analytics layers, while reporting and AI applications need to access complex, disparate data models.

Without a scalable, cloud-native data foundation, the potential of data and AI remains untapped – and a key competitive advantage stays out of reach.

Not sure which architecture is right for you?

Discover our Data AI Platform Starter Package: We offer you an exclusive Vendor Selection Workshop that helps you identify, compare, and select the technology that fits your business best.

Discover the Starter Package here!

Event Recap: EPM & Data Technology Forum June 2026

Our entertaining EPM breakfast session gave our participants a clear, neutral guidance on how to build a Snowflake-based data backbone or explore concrete AI in Planning use cases.

Discover the event highlights now!

Customer benefits

Faster time-to-insight on a single, fully managed AI Data Cloud: from data ingestion to AI agents in one governed environment.

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Cost reduction & predictable consumption

Multiple data tools that do not work together drive up cost and complexity. The Snowflake AI Data Cloud consolidates warehousing, data lakes, AI, and apps onto one fully managed platform. With a consumption-based pricing model and separate scaling of compute and storage, you only pay for what you actually use – with per-second billing. Forrester’s Total Economic Impact study (October 2024) quantifies the savings vs. legacy architectures.

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Near-infinite scalability - without infrastructure management

Snowflake provides near-unlimited, auto-scaling compute and storage for the most demanding workloads. Whether you are dealing with terabytes or petabytes, resources scale automatically – without manual cluster management or pre-provisioned capacity. Your teams focus on insights, not infrastructure.

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Enterprise-grade governance with Snowflake Horizon

In many organizations, it is unclear who can see which data, who has accessed it, and whether compliance requirements are met. Snowflake Horizon – the built-in, unified set of compliance, security, privacy, interoperability, and access capabilities – solves exactly this problem: role-based access control, full data lineage, and audit-ready reports across all workloads, regions, and clouds in real time.

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Native AI & GenAI with Snowflake Cortex

Snowflake Cortex AI provides fully managed, industry-leading AI models, LLMs, and vector search to analyze text data and build AI applications – without moving data outside your governed environment. From RAG architectures over enterprise documents to AI agents grounded in your operational data: design, evaluate, and deploy on one platform with consistent security and observability.

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Secure Data Sharing & Snowflake Marketplace

Snowgrid – Snowflake’s cross-cloud technology layer – connects business ecosystems across regions and clouds. It enables secure zero-copy data sharing, replication for business continuity, and a unified, cloud-agnostic experience. Partners and subsidiaries get instant access to live data – without ETL, without duplicates, with full governance preserved end-to-end.

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Build a productive data & AI platform with Snowflake and valantic

The solution

valantic accompanies companies from data strategy to productive operations on the Snowflake AI Data Cloud. Together, we define a target architecture and build a unified platform for analytics, AI, data engineering, and data sharing.

The cloud-based data platform unifies SQL analytics, Python and Snowpark workloads, generative AI with Cortex, and native applications in one fully managed service – providing the foundation for scalable, AI-ready data products.

Our implementations follow proven design principles: a layered data architecture (Raw, Staging, Curated, Consumption), role-based governance with Snowflake Horizon, automated pipelines with Snowpipe and Dynamic Tables, and end-to-end AI workflows with Cortex AI.

Deployment runs across all three hyperscalers – AWS, Microsoft Azure, and Google Cloud – and integrates seamlessly with existing landscapes such as SAP, Power BI, and Tableau for an end-to-end data foundation.
Through training and coaching, valantic enables your internal teams to develop, operate, and scale the platform independently.

Insights into the platform