Konekti provides a platform for building and managing process data models that integrates with existing data warehouses and process mining tools, enabling rapid data preparation and validation. This technology reduces the time and effort required to generate actionable insights, allowing teams to focus on high-value tasks while minimizing IT costs through reusable data models.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations often struggle to efficiently transform raw data into actionable insights for process mining due to the complexities of data modeling, code generation, and data validation. This results in wasted time and resources, increased IT costs, and delayed process improvements.
Solution
Konekti provides a platform for building and managing process data models that integrates with existing data warehouses and process mining tools, streamlining data preparation and validation. The platform simplifies data modeling, automates code generation, and streamlines data validation, resulting in faster data model creation. By enabling the reuse of established data models, Konekti reduces the need to start from scratch, accelerating data delivery and promoting standardization. The platform empowers teams to focus on high-value tasks by reducing the effort required to turn data into insights, while also minimizing IT costs through reusable data models and auto-optimized scripts.
Target Audience
Konekti is designed for process mining teams, business analysts, and IT professionals who need to efficiently build, manage, and validate process data models for process improvement initiatives.
Features
- Seamless integration with leading data warehouses and process mining platforms, including Power BI and Qlik Sense
- Automated code generation for ready-to-run scripts in any environment
- Reusable data models to scale data delivery and reduce development time
- Simplified data modeling with automated code generation and streamlined validation
- Centralized control over data model usage to boost stability, cut maintenance, and optimize storage