Data Pipeline Tools| K2View

Complete, clean, connected data, every time

Data engineers can now pipeline fresh, trusted data, from all sources, to all targets, at enterprise scale.

K2View Data Pipelining Tool - Complete Set of data

Benefit from a complete set of data pipeline tools

Integrate, transform, cleanse, enrich, mask, and deliver data – however and whenever required.

Ensure data integrity with patented technology

An entity-based approach guarantees that data is always complete, clean, connected, governed, and up-to-date.

K2View Data Pipelining - data flows for data teams

Productize data pipeline tools flows
for data teams

Build, certify, and package automated data orchestration flows, for use by data-consuming apps and teams.

Our unique approach

Data prepared and delivered
as real-time data products

Unlike traditional ETL vs ELT, that rely on complex and compute-heavy transformations to deliver disjointed data, a data pipeline tool moves data via data products, ensuring data integrity, high-speed pipelines, and agility.

A data product corresponds to a particular business entity – such as a customer, product, order, or location. The data for each instance of a business entity (like a single customer) is persisted and managed in a patented Micro-Database™ – one per customer.

Data Product Platform provides you with tools to auto-discover, and quickly modify, data products. Data engineers use our no-code platform to integrate, cleanse, enrich, mask, transform, and deliver data – enabling lightning-fast querying in data lakes, without complex, and compute-intensive joins between tables.

And there's more. Since data is continually collected and processed by Micro-Database, it can also be delivered to your operational systems in real time, to support Customer 360, Data Masking, Test Data Management, Data Migration, Legacy Application Modernization, and more.

Why a data pipeline tool is necessary

Patented approach to ETL/ELT ensures data integrity,
high-performance pipelines, and business agility

Accelerate time to insights with data pipeline automation

Data pipeline flows can be set up, tested, and packaged for reuse, and can automatically be invoked to operationalize data preparation, and accelerate time to insights.

Data scientists can roll back to previous sets of data, and access any historical version of that data, at the click of a button.

Data engineers use data pipeline tools to configure data, and automatically apply data cleansing, transformation, and enrichment – and to employ data masking tools, when needed – within the broader context of data integration tools.

Enterprise Data Pipeline ingests and delivers data via batch, data streaming (Kafka), CDC (Change Data Capture), and messaging.

new-UI-screens-Data-PipeliningData-Pipelining---Dynamic

Keep your data safe
and well-governed

Data pipeline tools dynamically masks sensitive data at the entity level – preserving data integrity, even after masking.

In addition, data is encrypted from the time it is ingested from the source systems, to the moment it is served to data lakes and data warehouses, including data at rest.

Enterprise Data Pipeline is based on Data Product Platform, which supports both operational and analytical workloads, and can be implemented as a data mesh or data fabric – on premises, in the cloud (iPaaS), or across hybrid environments.

It can be deployed in a cluster – close to sources and targets – to reduce bandwidth costs, enhance security, and increase speed.