Integrate any source to any target,
in any method, at any frequency.
Deliver trusted data to data consumers in milliseconds.
Access clean, complete, and consistent data, by data product.
Integrate and deliver data from any data source – on premises or in the cloud – to any data consumer, using any data delivery method: bulk ETL, data streaming, data virtualization, log-based data changes (CDC), message-based data integration, Reverse ETL, and APIs.
A data product approach to data integration integrates, processes, and deliveris data by business entities. Data integration tools enable data engineers to create and manage reusable data pipelines, for both operational and analytical workloads.
Enterprise data integration tools include auto-discovery and modeling of the data product schema, which defines all the tables and fields for a specific business entity (e.g., customer, location, device, etc.), from all your existing systems – regardless of the underlying technologies or formats.
A data product ingests the data for each instance of a business entity into its own high-performance, patented Micro-Database™.
It then applies data masking tools, transformation, enrichment, and data orchestration tools – in flight – to make the individual entity's data available to any authorized data consumer, in any delivery style, while complying with data privacy and security regulations.
As part of Data Product Platform, we provide a no-code data transformation tool for defining, testing, and debugging data transformations – logic and flows – to address simple and complex needs, with ease:
Basic data transformations
Data type conversions, string manipulations, and numerical calculations.
Intermediate data transformations
Lookup/replace using reference files, aggregations, summarizations, and matching.
Advanced data transformations
Complex parsing, unstructured data processing, combining data and content sources, text mining, correlations, custom enrichment functions, data validation, and cleansing
Unlike traditional ETL vs ELT approaches, enterprise data integration tools use an in-memory database to perform data transformation at high speed. Data transformation is applied at the individual business entity level, making performance lightning fast, in support of high-scale data preparation and delivery.
Data engineers, enterprise architects, and data integration developers
use our data integration tools for a wide variety of use cases, such as:
Migrate and modernize data and analytics workloads to the cloud, reliably and securely, with a data product architecture that spans multiple on-premise and cloud environments.
Provide real-time access to trusted data, across a broad range of landscapes, by leveraging active metadata through patented Micro-Database technology.
Create, manage, and operationalize data pipelines to support analytics demands (e.g., logical data warehouse, data science) by adhering to predefined architectural methodologies, patterns, and tools.
Support operational use cases – like customer data hub, and multi-domain MDM – by consolidating, integrating, and synchronizing data related to data governance, and key business processes.
Data Product Platform scales linearly to manage hundreds of concurrent pipelines, and billions of Micro-Databases, in support for high-scale operational and analytical data integration workloads.
It can be deployed, on premises or in the cloud, in a data mesh architecture, data fabric architecture, or data hub architecture.
Enterprise data integration was designed with digital business in mind, where every millisecond counts. In-memory computing, combined with patented Micro-Database technology, and distributed architecture, deliver unmatched source-to-target performance.
The K2view platform can be deployed as an iPaaS, in a public cloud architecture, to deliver the following benefits:
Application and data integration is seamless, without any delays.
Integrations are available quickly, to speed your digital transformation initiatives.
Built-in connectors, and no-code data orchestration tools, integrate with all your apps and data sources.
Integration flows can be used by both business and data teams, so you can expand the scope of your integrations.
Integration flows are quickly adapted to match your business requirements and digital transformation efforts.
The platform supports data mesh, data fabric, and data hub architectures.
Connectors to hundreds of SQL and NoSQL data sources
Dedupe/mask/encrypt functionality for privacy and security
Data virtualization, as an easy-to-access logical abstraction layer
Multiple data delivery styles, including CDC, ETL and message-based data movement
High-speed exposure and orchestration of data services
Data transformation of unprecedented sophistication
Support for cloud data integration
Metadata and data modeling support
Design and development tools
Data governance support
Deployment environment flexibility
Operations and admin capabilities
Support for multiple architectures and integration
Simple usability, due to no-code studios and dashboards
Get a live demo of the K2View platform to assess its fit for your use cases.
Experience the power and flexibility of the K2View platform with a 30-day trial.
Experience the power and flexibility of the K2View platform with a 30-day trial.
