
SCIKIQ is a trailblazing no-code data platform that helps organizations integrate, curate, govern, and activate enterprise data across cloud, multi-cloud, hybrid, and on-premises environments. SCIKIQ works with the technology you already run, SAP, Oracle, Salesforce, databases, data lakes, warehouses, SaaS applications, AWS, Azure, and GCP, without forcing a rip-and-replace.
At its heart is Contextual Intelligence. SCIKIQ understands the unique semantics of enterprise data, connecting technical metadata with business definitions, relationships, rules, quality, lineage, and governance. The result is trusted, contextualized data that people, analytics, applications, and AI can understand and use.
SCIKIQ unifies the data lifecycle in one no-code platform:
• Integrate — Connect structured and unstructured data across applications, databases, files, APIs, SAP, and real-time sources using 200+ connectors and no-code pipelines.
• Curate — Profile, clean, transform, standardize, enrich, model, and contextualize data through automated data preparation.
• Govern — Manage metadata, catalog, data quality, lineage, privacy, policies, access, and stewardship across the enterprise.
• Activate — Deliver trusted data to BI, analytics, enterprise applications, data products, machine learning, AI copilots, and intelligent agents.
Instead of stitching together disconnected tools, SCIKIQ brings data integration, ETL, transformation, data quality, governance, catalog, lineage, semantic models, knowledge graphs, data products, and intelligence together on one unified platform. SCIKIQ works on top of your existing data architecture, reducing engineering complexity, bridging skill gaps, and accelerating time to value.
Recognized by Forrester, NASSCOM, YourStory, Inc42, and DataIQ for innovation in enterprise data and intelligence.
SCIKIQ is The No-Code Data Platform That Works for Your Business.
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Validio
See how your data assets are used: popularity, utilization, and schema coverage. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Find and filter the data you need based on metadata tags and descriptions. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Drive data governance and ownership across your organization. Stream-lake-warehouse lineage to facilitate data ownership and collaboration. Automatically generated field-level lineage map to understand the entire data ecosystem. Anomaly detection learns from your data and seasonality patterns, with automatic backfill from historical data. Machine learning-based thresholds are trained per data segment, trained on actual data instead of metadata only.
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