Continuous data integration and delivery
From any source to any target
at AI speed and scale
Leverage AI to integrate and deliver data from any data source – on-prem or cloud – to any data consumer, using any data delivery method: bulk or reverse ETL, data streaming, data virtualization, CDC, message-based data integration, and APIs.
AI automation + active metadata
- 01 AI automation copilot
- 02 Pipeline auto-recovery
- 03 Schema drift prevention
- 04 Self-optimization
01AI automation copilot
AI automation copilot
Auto-discover and model your data products.
Auto-classify, generate, and document your data pipelines.
02Pipeline auto-recovery
Pipeline auto-recovery
Automatically recover your data pipelines after failures without data loss, for seamless data ingestion and integration.
03Schema drift prevention
Schema drift prevention
Auto-detect changes, perform impact analysis, and provide recommendations and actions for continuous integration.
04Self-optimization
Self-optimization
Analyze metadata to continuously improve resilience, optimize data integration performance, and control costs.
Robust, reusable data integration
Entity-based data integration
A data product approach
Ingest and deliver data by business entities
K2view takes a data product approach to data integration.
Data engineers create and manage reusable data pipelines that integrate, process, and deliver data by business entities – customers, employees, orders, loans, etc.
- The data for each business entity is ingested and organized into its own high-performance Micro-Database™.
- The schema for a business entity is auto-discovered from the underlying source systems.
- Data masking, transformation, enrichment, and orchestration are applied – in flight – to make entity data accessible to authorized data consumers, while complying with data privacy and security regulations.
Quick and easy
No-code data integration
and transformation
K2view data integration includes no-code tooling for defining, testing, and debugging data transformations to address simple and complex needs, with ease. Data transformation is applied in the context of a business entity, making performance lightning fast, in support of high-scale data preparation and delivery.
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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.
Linear scalability on commodity hardware
Real-time performance
at AI scale
K2view Data Product Platform scales linearly to manage hundreds of concurrent pipelines, and billions of Micro-Databases, in support of enterprise-scale operational and analytical data integration workloads.
- In-memory computing, patented Micro-Database technology, and a distributed architecture are integrated to deliver unmatched source-to-target data performance.
- K2view can be deployed on-prem or in the cloud, in support of a data mesh architecture, data fabric architecture, or data hub architecture.
- Data pipelining monitoring and control is built in, with observability at the business entity level.
Key features and capabilities
Augmented data integration tools for any task
No-code/low-code tooling
Support for every level of data engineering expertise
Connection to any source
Built-in connectors to hundreds of data sources and applications
Any delivery style
Including CDC, ETL, streaming, and messaging
Data virtualization
Data virtualization support, for an easy-to-access logical abstraction layer
Data transformation
Data transformation of unprecedented sophistication
Auto-discovery
Metadata discovery and data classification, for quick implementation
Data quality
Inflight data quality is enforced by customizable business rules
Deploy anywhere
Support for cloud, hybrid, or on-prem data integration