Data cleansing made simple. Deliver consistent, high quality data. Enrich raw data for meaningful and trusted insights.
Accelerate the process of getting data ready. Reduce data preparation resources. Improve data analyst productivity.
Solve your problems with data. Manage highly distributed and massive volumes of diverse data. future-ready architecture.
Access a large quantity of relevant data types, aligned to your business to deepen insights and make better decisions.
“VIMANA built a robust real-time data foundation, collecting data from machines and systems, and making it available to our data lake for downstream analytics. We didn’t need to hire data scientists, and we dramatically reduced the time to prepare the data,”
A Global Tier 1 Automotive Company
VIMANA Data Transformation prepares, normalizes, and contextualizes manufacturing and enterprise data leveraging open standards, a robust rules engine, and machine learning to build a data foundation for consumption by next-generation analytics.
Standards-based data collection from a wide variety of sources and attributes to solve industrial business problems. Integrating with enterprise systems for insight into the complex enterprise ecosystem.
Builds a consistent, holistic view using standardized semantic asset models with a common set of terms, units, and vocabulary. Leverages industrial domain-driven ontologies to model assets, processes, and businesses enabling automated reasoning and analytics.
Filters out unnecessary noise from raw data, and inconsistent and corrupt data, improving the data quality.
Uses the enrich rules engine and applies proprietary domain-driven ML and AI algorithms for multi-dimensional contextualization and aggregation of event streams for an understanding of the true state of industrial assets, people, processes, and products.
Enables analytics-ready data stores with other storage solutions, data lakes for integration with enterprise systems, BI tools, and other downstream analytics.
Enables real-time visualizations, metrics, historical reporting, anomaly detection, alerts, digital twin, machine learning, predictive and prescriptive insights.