Your Single 
Source of Truth for Marketing Analytics

NinjaCat Data Cloud is a marketing‑specific data platform that ingests, stores, transforms, and ships your analytics data at scale. It centralizes paid media, social, web, CRM, and offline data, normalizes it, and makes it BI‑ and AI‑ready for activation in Reporting, Dashboards, and AI Agents.

Most ETL tools are general‑purpose. Data Cloud is built for marketing with native/smart connectors, no‑code + chat‑driven transforms, campaign taxonomy handling, and live delivery to BI tools and downstream apps. Unlike a CDP focused on profiles/audiences, Data Cloud focuses on analytics tables (spend, clicks, impressions, conversions, revenue, etc.) with auditability and governance for analysis and decisioning.

Over 100 native connectors cover the most common marketing platforms (Google Ads, GA4, Meta, LinkedIn, Microsoft Advertising, CallRail, Sheets, etc.). For anything unique, use AI Connectors, MCP Servers, or Custom Connectors to bring in additional sources. Browse Integrations.

Data Cloud supports daily syncs and up to 2 years of historical backfill (where supported by the source) so your agents, dashboards, and analyses start with deep context from day one.

Yes. Use a visual editor and plain‑English prompts (SQL optional) to join, map, rename, and calculate fields. Automatic normalization brings order to multi‑account, multi‑network campaign data.

You get your own Snowflake environment managed by NinjaCat, or you can push governed data to external warehouses you already use (e.g., BigQuery, Databricks, Redshift) and data lakes like Amazon S3. There’s no vendor lock‑in.

Yes. Use Live BI Delivery to send visualization‑ready tables to Tableau, Looker Studio, Sisense, NinjaCat Reporting, and other destinations. Data Cloud also supports API and code‑free replication for operational use cases.

Data Cloud is the trusted foundation for NinjaCat AI Agents. Agents read governed, standardized datasets from Data Cloud to monitor performance, explain anomalies, and draft recommended actions (briefs, CSVs, alerts) with human‑in‑the‑loop controls.

No. Customer data (including prompts and outputs) is not used to train foundation models. Data is processed to operate the product, improve reliability, and meet security and compliance obligations.

NinjaCat employs encryption in transit and at rest, RBAC permissions, MFA, logging, and hardened cloud infrastructure. You choose what sources are connected and which datasets are in scope. See Security & Privacy.

Data Cloud offers flat‑rate pricing with no metered usage or surprise compute/tokens. Pricing reflects data volumes, destinations, and users. Request a demo for a tailored plan or pilot.

Most teams begin delivering governed, BI‑ready tables shortly after connecting sources. Pre‑built transforms, templates, and backfill accelerate time‑to‑insight; scale across portfolios with repeatable onboarding. Many teams see their first live agents operating within a week and full reporting automation within 30 days.

It depends. Many customers keep their current warehouse/BI and use Data Cloud as the marketing pipeline + model layer, pushing governed tables downstream. Others run primarily in the NinjaCat‑managed Snowflake and deliver to BI tools directly.

Yes. Use role‑based access, approvals, and change logs to control who can connect sources, edit models, or ship data.

Yes. Data Cloud normalizes multi‑account, multi‑platform structures, supports labeling and templated transforms, and can roll up KPIs across portfolios while preserving account‑level drill‑downs.

1) Identify priority sources and KPIs.
2) Connect accounts and run historical backfill.
3) Configure normalization & calculations (no‑code/chat).
4) Validate tables and naming. 5) Turn on BI delivery and (optionally) enable AI Agents.
6) Expand to more sources/brands.