K2View Launches Real-Time Data Product Platform Available Now with a 30-Day Free Trial

Deployable as data mesh, data fabric, or data hub – in the cloud, on premises, or across hybrid environments

K2View, a global leader in operational data management, announced the market’s first Data Product Platform, designed to create, deliver, and manage data products, at massive scale, and in real time. The platform, now available for a 30-day free trial, democratizes operational data access across the enterprise, resulting in increased IT and business agility, and data-driven innovation.

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Real-time data products deliver a trusted view of any business entity, such as a customer, order, supplier, or device. Every data product integrates a specific entity’s data from all relevant source systems, into its own, secure, high-performance Micro-Databaseâ„¢. It also ensures that the Micro-Database is always current with fresh data, and instantly accessible to authorized data consumers across the enterprise.

The K2View platform is unique in its versatility to be deployed as a data fabric, data mesh, or data hub. Moreover, customers can deploy the platform as a centralized data fabric or data hub, and gradually phase into a federated data mesh architecture, at a pace that matches their business needs and the level of their data management maturity.

The platform fuels key operational workloads, including customer 360, data pipelining, data tokenization, legacy application modernization, test data management, and more.

K2View Data Product Platform can be implemented in a matter of weeks, scales linearly, and adapts to change on the fly. It can be deployed in the cloud (as an integration Platform as a Service – “iPaaS”), on premises, or across hybrid environments.

“Thanks to the K2View platform, we’re now able to access the data that was previously trapped in our legacy systems, and leverage it for operational decision-making in real time,” explained Victor Malka, VP and CIO at Cellcom. “The platform supports key operational and analytical workloads, such as our customer service CRM, mobile workforce management app, self-service customer portals, and more. In the end, we benefit from increased agility and faster time to market.”

“Our vision is to become the data platform of choice for real-time operational workloads, in the same way that Snowflake and Google BigQuery have become the enterprise datastores for analytical workloads,” stated Achi Rotem, CEO of K2View. “K2View Data Product Platform is the only platform that makes trusted, operational data instantly accessible to any data consumer in the enterprise.”

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The K2View Data Product Platform manages the entire lifecycle of a data product in short, iterative delivery cycles, from design and engineering, through testing and deployment, to monitoring, maintaining and retiring data products.

Core modules of the platform include:

  • Data Product Studio, a web-based, low-code/no-code integrated development environment (IDE) for building, testing, deploying, and adapting data products. The studio enables data product schema creation, data movement orchestration, data transformation logic, data integration and delivery configuration, access controls, and more.
  • Micro-Database Management, responsible for creating, compressing, securing and synchronizing micro-databases on the fly, and making them instantly accessible via data products, on demand. Billions of mDBs can be managed in a single deployment, on commodity hardware.
  • Data product monitoring, providing visibility into data product performance and usage, and the ability to pause, kill, trace and restart data flows on demand.
  • Data product cataloging, for visualizing the relationships between data products, their sources, and data consumers, in a knowledge graph. The catalog allows users to quickly discover and consume available data products.
  • Embedded BI, enabling the creation of reports and dashboards to visualize and analyze data products.
  • Flexible architecture and operating model, supporting centralized, federated or hybrid architectures: data fabric, data mesh, and data hub.
  • Public cloud deployment (iPaaS), with multi-tenancy support, SSO (Single Sign On) authentication, and identity provider integration.

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