Move, transform, and trust your enterprise data

ETL stands for extract, transform, and load. It's the process of pulling data from your source systems, cleaning and reshaping it into a consistent format, and delivering it to your warehouse or analytics platform. Enterprises need ETL because data lives everywhere, like CRMs, ERPs, databases, SaaS tools, and data lakes. Without ETL, every downstream report, dashboard, and AI model is built on inconsistent, unreliable data. DataPrep gives your data team a governed, auditable pipeline so the data your business acts on is always clean and trustworthy.

Zia is DataPrep's built-in AI assistant for data preparation. You describe a transformation in plain English (like, "standardize all phone numbers to E.164 format" or "flag any order record where revenue is null but status is completed"), and Zia generates the transformation logic instantly. It also supports transform-by-example: provide a before/after sample, and Zia infers the rule automatically. The chat formula builder lets you construct complex multi-condition expressions conversationally. Smart profiling uses Zia to surface data quality issues like missing values, outliers, and format inconsistencies—before you build the pipeline, not after it breaks in production.

Yes, entirely. DataPrep's cloud-native architecture scales automatically with your workload. That means there's no cluster sizing, no capacity planning, and no infrastructure team required. It's built to process tens of millions of rows per pipeline run. If you want to validate performance against your specific data volumes before committing, our solutions team can run a scoped proof-of-concept with your actual data.

DataPrep validates data before it reaches your destination. Bad rows type mismatches, nulls in required fields, and duplicates are flagged and held back, not silently loaded. If a pipeline stage fails, automated retry logic handles transient issues like timeouts without human intervention. Persistent failures trigger an alert with a detailed error log: which stage failed, which records were affected, and the full retry history. Your destination data stays clean, and your team has everything needed to fix the issue fast.

Both are built into the platform, not added on. For GDPR: data minimization controls, right-to-erasure workflows, data residency settings, and PII masking before data leaves controlled environments with a full audit trail on every access and transformation. For HIPAA: field-level PHI masking, access logging, minimum necessary data controls, end-to-end encryption in transit and at rest, and Business Associate Agreement (BAA) support included with enterprise contracts.

Most enterprise customers have production pipelines live within one to two weeks of signing, with full deployment in four to eight weeks. You get a dedicated onboarding engineer, structured testing, and a 30-day hyper care period post-launch. After go-live: 24/7 phone and chat support with SLA-backed response times, a named Customer Success Manager, quarterly business reviews, and access to a global certified Partner network. Enterprise pricing is based on data volume and pipeline count with all 90+ connectors included, so there's no per-connector charges.