Paxata Self Service Data Preparation (SaaS)
Paxata Self-Service Data Preparation (SaaS)
Paxata Self-Service Data Preparation is a solution for business analysts and data professionals to discover, ingest, explore, transform, and export data, creating clean and contextual information from raw data.
Up to 80% of the effort in analytics exercises is spent on data preparation – gathering, exploring, cleaning, combining, shaping, and enriching data to make it usable and reliable. Paxata transforms analytics by removing the critical bottleneck of turning raw data into trustworthy information with an enterprise-grade, self-service data preparation application and machine learning platform.
Paxata is a visually-dynamic, intuitive solution that enables business analysts to rapidly ingest, profile, and curate multiple raw datasets into consumable information in a self-service manner, greatly accelerating development of actionable business insights. In addition to empowering business analysts and SMEs, Paxata also provides a rich set of workload automation and embeddable data preparation capabilities to operationalize and deliver data preparation as a service within other applications. The Paxata Adaptive Information Platform (AIP) unifies data integration, data quality, semantic enrichment, re-use & collaboration, and also provides comprehensive data governance and audit capabilities with self-documenting data lineage. The Paxata AIP utilizes a native multi-tenant elastic cloud architecture and is the only modern information platform that is currently deployed as a multi-cloud hybrid information fabric.
Leading global enterprises across all industries, including financial services, retail, pharmaceutical, healthcare, technology, as well as the public sector, leverage Paxata to increase analytics speed, quality and volume. With Paxata, business consumers use clicks, not code, to drive insights and unlock business value in minutes, not months. Paxata customers complete analytics and data migration projects 75% – 95% faster with dramatically improved accuracy at a fraction of the cost of traditional data preparation methods.