End-to-end DataOps platform
with a modern data and compute architecture
We help companies to build computing and data infrastructure that enables enterprises to rapidly adopt a modern data strategy and robustly manage unlimited amounts of data. Working with you can bring our IP if that suites you or we work with your technology stack to build full-stack analytics platform, with services for data orchestration, automation and analytics. Such an application accelerates the development of data-driven applications and serves as a coherent analytics ecosystem for your business users that want to architect data intelligence solutions that leverage disparate data sources, live feeds, and event data regardless of the amount, format or structure of the data.
Data-driven enterprises are recognizing that no matter how one defines “big data,” whether along the volume, variety or velocity axes, one simple definition is clear: big data means all data. That is, information may be available to an enterprise as numerical tables, unstructured text articles, images, or sound and video, and they must therefore be ready to operate on massive volumes of diverse, rapidly changing data sets.
Just as enterprises recognize the need for DevOps to ensure coordination between software developers and IT operations, there is now a strong need to support DataOps as coordination between data engineers, data scientists, and IT operations becomes more critical. Large investments are made into developing advanced analytical models, but enterprises only generate their returns on these investments when analytical models are operationalized and executed on in production.
We bring industry’s leading Intelligent DataOps platforms that offers a full portfolio of capabilities for orchestration, automation and analytics, ensuring that analytics can be rapidly deployed into business workflows.
Enterprises must leverage big data with infinite flexibility and at scale, to successfully address the 3 C’s of data management: Collection, Consolidation and Consumption. A modern Composable data architecture provides a framework for synthesizing disparate data sources, with the use of event-driven workflows and built in services for all the data plumbing, integration, processing, mastering and structuring of the data. Business users can now use ad-hoc, self-service analytics for data discovery and analysis, or external applications (CRMs, EPMs, etc.), without the time-consuming data preparation that is typically required.
Key features of a modern, composable data and compute architecture:
- Embrace heterogeneity of diverse data, diverse platforms, and diverse technologies.
- Best of breed technologies supporting business and technical needs.
- Reduced operating costs with minimal infrastructure transformations.
- Accelerated adoption with capabilities for self-service, data discovery and ad-hoc analytics.
- Data, Metadata & Algorithms widely accessible.
- Unanticipated Users and Use Cases fully supported.