Zaloni

Zaloni - Integrated Self-Service Data Platform for Cloud and Hybrid Environments


Enable the data lake for management that scales

IT and engineering teams can build and manage the data lake to scale for right-time insights across the enterprise:

  • Ingest data, from any source, with ease
  • Simplify and accelerate ingestion processes through self-service ingestion wizard
  • Automatically capture operational, technical and business metadata to organize your data lake
  • Orchestrate and automate data preparation
  • Significantly reduce time spent on coding via the drag-and-drop interface
  • Maintain a clean data catalog for self-service data discovery and preparation

Govern the lake for data quality and trust

Data stewards and compliance teams have access to manage processes and access to data for right-sized governance and quality:

  • Leverage metadata management for governance
  • Track data lineage throughout the data lifecycle
  • Implement agile data mastering
  • Automate workflows to ensure data quality and integrity
  • Enforce data privacy and role-based security
  • Manage the comprehensive data lifecycle from interception to retirement

Engage with analytics-ready data

Analysts and data scientists can discover data sets, interact with them and uncover the insights that drive your business:

  • Explore and curate data from an enterprise-wide data catalog
  • Expand search globally across zones, projects, workflows, data quality rules and transformations
  • Reduce time to analytics with self-service data preparation
  • Enable collaboration in workspaces for improved productivity
  • Increase efficiency through automated workflows

Zaloni Data Platform [VIDEO Demo]

Customize to Fit Your Business Needs

Data Master Extension (DME)

Build golden records using a spark-based machine learning engine for matching and linking records.

Catalog Plus

Bridge the gap between business & IT. Turn the promise of governed self-service data into reality.

About the Architecture

Minimize the pain of modernizing your data architecture with no need to rip and replace.

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