Data Integration Tools

AI automation and active metadata

AI automation copilot

Auto-discover and model your data products.
Auto-classify, generate, and document your data pipelines.

Pipeline auto-recovery

Automatically recover your data pipelines after failures without data loss, for seamless data ingestion and integration.

Schema drift prevention

Auto-detect changes, perform impact analysis, and provide recommendations and actions for continuous integration.

Self-optimization

Analyze metadata to continuously improve resilience, optimize data integration performance, and control costs.

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 M icro-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.

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.

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.

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.

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

Any data architecture

Deploy in a data mesh architecture, data fabric architecture, or data hub

Data quality

Inflight data quality is enforced by customizable business rules

Deploy anywhere

Support for cloud, hybrid, or on-prem data integration

Overview

Capabilities

Architecture

Data Privacy and Compliance

Data for Generative AI