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What is K2View?

K2View is committed to empowering enterprises to fully utilize their data for enhanced agility and innovation. Our Data Product Platform facilitates this by generating and overseeing a reliable dataset for each business entity as needed and in real-time. This dataset remains continuously aligned with its original sources, adjusts seamlessly to changes, and is readily available to all authorized users. We support a variety of operational applications, such as customer 360, data masking, test data management, data migration, and the modernization of legacy applications, enabling businesses to achieve their goals in half the time and at a fraction of the cost compared to other solutions. Additionally, our approach ensures that organizations can swiftly adapt to evolving market demands while maintaining data integrity and security.

What is Informatica Data Engineering?

Efficiently ingesting, preparing, and managing data pipelines at scale is critical for cloud-based AI and analytics. Informatica's extensive data engineering suite provides users with a comprehensive array of tools essential for executing large-scale data engineering tasks that facilitate AI and analytical insights, incorporating features like advanced data integration, quality assurance, streaming capabilities, data masking, and preparation functionalities. Through CLAIRE®-driven automation, users can rapidly create intelligent data pipelines that incorporate automatic change data capture (CDC), enabling the ingestion of numerous databases and millions of files along with streaming events. This methodology significantly accelerates the return on investment by facilitating self-service access to trustworthy, high-quality data. Users can gain authentic perspectives on Informatica's data engineering solutions from reliable industry peers. Moreover, reference architectures tailored for sustainable data engineering practices can be explored to enhance efficiency. By adopting AI-driven data engineering in the cloud, organizations can guarantee that their analysts and data scientists have the reliable, high-quality data necessary for effectively transforming their business operations. This comprehensive strategy not only simplifies data management but also empowers teams to confidently make data-driven decisions, ultimately paving the way for innovative business solutions. In conclusion, leveraging such advanced tools and practices positions organizations to thrive in an increasingly data-centric landscape.

Media

Media

Integrations Supported

Azure Marketplace
Model Context Protocol (MCP)
Salesforce

Integrations Supported

FairCom DB
FairCom EDGE

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

K2View

Date Founded

2009

Company Location

United States

Company Website

k2view.com

Company Facts

Organization Name

Informatica

Date Founded

1993

Company Location

United States

Company Website

www.informatica.com/products/big-data.html

Categories and Features

Cloud Migration

Not specified

Data Catalog

Not specified

Data Engineering

Not specified

Data Fabric

Data Lineage Tools
Data Networking / Connecting
Metadata Functionality

Data Governance

Not specified

Data Integration

Not specified

Data Management

Data Integration
Data Migration
Master Data Management

Data Masking

Not specified

Data Pipeline

Not specified

Data Preparation

Not specified

Data Virtualization

Not specified

DataOps

Not specified

GDPR Compliance

Not specified

Integration

ETL - Extract / Transform / Load

iPaaS

Not specified

Metadata Management

Not specified

Test Data Management

Not specified

Categories and Features

Big Data

Not specified

Data Engineering

Not specified

Data Pipeline

Not specified

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