The startup offers a data management platform that integrates traditional and semantic data management through a metadata management toolkit and data verification tools. This platform standardizes metadata, enhances data discovery, and improves data quality, enabling organizations to efficiently organize, clean, and visualize their data.
Funding
$620K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Organizations struggle to efficiently discover, access, and understand their data due to disparate systems, inconsistent metadata, and a lack of standardized processes. Data scientists often spend excessive time searching for relevant data, hindering their ability to generate valuable insights and optimize data-driven decision-making. This complexity is amplified in larger, distributed organizations, leading to inefficiencies and underutilization of data assets.
Solution
MetadataWorks provides a unified metadata catalog solution that enables organizations to standardize, govern, and derive value from their data assets. The platform offers a customer-centric search engine for data, facilitating simple, secure, and speedy data access. It includes configurable metadata importers, standardized templates, and workflows to streamline data classification and standardization. By improving data discovery, access, and understanding, MetadataWorks empowers data teams to accelerate onboarding, align with standards, and federate with others, ultimately making data FAIR (Findable, Accessible, Interoperable, and Reusable).
Target Audience
The primary target audience includes data scientists, data engineers, data architects, and other data professionals within government, healthcare, and other large organizations who need to improve data discoverability, accessibility, and reusability.
Features
- Intuitive user experience for data discovery and search
- Configurable metadata importers for various data sources
- Standardized templates and workflows for metadata creation and management
- Role-based access control for secure data access and governance
- Centralized directory for code-sets, models, vocabularies, and reference data
- Open APIs for integration with existing data infrastructure
- Configurable dashboards and scorecards for monitoring data quality and usage
- Support for generating artifacts such as MS and JSON schemas