DataOS® - Complete Data Management - World's First Data Operating System
by The Modern Data Company
A complete data management platform that removes complexity & future-proofs data ecosystems.
DataOS The Modern Data Operating System
DataOS is the world’s first fully integrated data operating system that delivers a data infrastructure that rapidly moves you from data to trusted decisions in weeks instead of years.
The DataOS Difference:
Modern Layer over Legacy Systems
DataOS allows organizations to instantly use their legacy systems in modern ways. With DataOS, you can apply modern governance and activation to legacy systems without the need to modernize them.
Outcome-Based Data Engineering
Business users define the outcome they need. DataOS automatically gets the required data without the need to write pipelines.
Data Analysis without Data Movement
Perform most data analysis with data in place. Move only the data that needs to be operationalized. Less risk, cost, and significantly more value.
Modern Composable Architecture
Composable architecture allows you to realize Data Fabric, Data Mesh, Lakehouse, CDP and similar architectures in weeks vs years.
The World’s First Data Operating System
Connect to Any Data Type
Our Data Depot construct allows you to connect to any type of source or sync system. It abstracts the underlying technology and credentials needed to connect to these systems so that you can model against that data and then operationalize it.
Automatically Catalog Your Current Data Infrastructure
DataOS automatically scans your current data infrastructure(hybrid, on-prem or any cloud) and catalogs all data elements across your enterprise. This enables a Google-like semantic search across all things data (metadata, queries, jobs, dashboards etc. ).
Understand the Relationships Between all of Your Data Elements
DataOS provides real-time context of your data. All the relationships between data sets, queries, jobs, dashboards, metrics, tags etc. are created using our knowledge graph.
Access Any Type of Data Using a Common SQL Interface
DataOS normalizes access to any type of data across your enterprise. You can now use standard SQL to access data within CSV files, Kafka topics, databases, data lakes and any other data system. This enables organizations to apply modern governance to legacy systems. DataOS is the only product that promises to free your data while making the data more secure than before.
Data as a Product
DataOS converts database tables, blob files, CSV files, unstructured data etc. into data products. It automatically creates the data dictionary and manages schema evolution. Additionally, DataOS automatically profiles the data, runs quality checks, creates lineage and impact analysis, versions your data and converts disparate data elements into a standardized tabular structure.
Data as Software
Declarative primitives • In-place automation • Flexible APIs
Allow you to easily discover, understand and transform data as you need, to operationalize or observe.
Outcome Based Data Engineering
DataOS has a patented right to left data engineering capability that allows business users to define what data they need to drive business outcomes. DataOS automates the data pipeline to deliver data to the business user. This eliminates the need to high skill resources to support business teams and makes them self-sufficient to access the data they need.
DataOS delivers one of the most advanced governance capabilities in the world. Our Attribute based access control enables enterprises to govern data centrally in a proactive manner.
DataOS creates a business ontology of your data which allows business users to view data through a business lens without the need to understand the systems, technologies and formats in which data is stored across the enterprises. Business users don’t need to worry about how the data needs to be joined together.
DataOS enables organizations to share just the metadata instead of transferring data for data sharing purposes. We enable data movement only to operationalize data. This eliminates the need to make data copies to share data.