KADA
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About
KADA is an intelligent data copilot designed to bridge the gap between business context and technical data assets. It serves as a centralized platform for data observability and governance, helping organizations manage millions of data assets by providing visibility into how data is used, who is using it, and where it comes from. By processing billions of logs, KADA provides a clear picture of the data ecosystem, ensuring that teams can rely on the information they use for decision-making. The platform aims to build data trust by making complex data flows transparent and understandable for everyone from data scientists to business users. The tool integrates seamlessly with popular data stacks such as Snowflake, Oracle, Tableau, and dbt to provide automated, field-level lineage. This lineage is more than a static map; it combines usage data with flow information to show which data products are actually active and critical for the business. KADA leverages AI to identify opportunities for cost reduction and to detect potential PII (Personally Identifiable Information) automatically, which fast-tracks governance activities. It also features a powerful impact assessment tool that transforms potential changes into personalized notifications, helping teams investigate root causes and respond to incidents much faster than manual methods. KADA is built for a diverse range of roles, including data users, governance managers, project teams, and data stewards. Data users benefit from a self-service environment where they can find trusted data, while governance managers can prioritize their tasks based on real-world usage patterns. According to the platform's data, users have seen a 75% decrease in data discovery efforts and a 65% increase in efficiency when managing data incidents. It is particularly well-suited for large-scale organizations in sectors like finance, retail, and education that handle high volumes of data and require strict compliance standards. What makes KADA unique is its focus on the intersection of usage and lineage, making maps actionable by showing how data flows are used by specific teams. It bridges the gap between technical schemas and business terminology by automatically connecting business glossaries to data assets. This allows new employees to self-service information within their specific business context from their first day. Furthermore, with SOC2 compliance and a deployment time of less than one hour, KADA offers an enterprise-grade solution that is remarkably quick to implement compared to traditional data governance frameworks.
Pros & Cons
Reduces data discovery efforts by up to 75% for project and data teams.
Supports field-level lineage with specific logic and calculation details.
SOC2 compliant ensuring enterprise-grade security and data privacy.
Provides rapid deployment, allowing users to see their ecosystem in less than an hour.
Automatically connects business glossaries to technical data assets for better context.
Pricing information is not publicly available and requires contacting sales for a quote.
Primary focus is on enterprise-scale data ecosystems like Snowflake and Oracle.
Requires a demo booking to access the full capabilities of the data copilot.
Use Cases
Data Governance Managers can use automated monitoring to prioritize governance tasks on the most critical and high-usage data assets.
New Data Consumers can use the business glossary connection to find and trust data products from their first day on the job.
Data Stewards can increase efficiency by 65% by using automated notifications to manage data incidents and document assets.
Project Teams can decrease data migration efforts by 72% through automated impact assessments and personalized change alerts.
Platform
Task
Features
• usage analytics
• pii detection
• soc2 compliance
• advanced data monitoring
• business glossary integration
• data ecosystem copilot
• impact assessment notifications
• automated field-level lineage
FAQs
How does KADA help with data discovery?
KADA reduces data discovery efforts by up to 75% by providing an intelligent copilot that helps users find and understand trusted data assets. It connects business concepts directly to data products, allowing users to self-service from their own context.
What integrations does KADA support?
KADA integrates with a wide variety of tools in the data ecosystem, including Snowflake, Oracle, Tableau, dbt, Microsoft, and Teradata. These connections allow KADA to automatically map lineage and monitor usage across different platforms.
Can KADA help with PII and data security?
Yes, KADA uses automatic detection to identify potential PII (Personally Identifiable Information) within your data ecosystem. This feature helps fast-track governance activities and reduces risks associated with sensitive data handling.
How quickly can KADA be deployed?
KADA is designed for rapid implementation and can be deployed in less than an hour. Once connected, it begins processing logs to provide visibility into your data ecosystem almost immediately.
Does KADA provide lineage at the field level?
Yes, KADA offers unprecedented depth by providing field-level lineage that includes details such as calculations and logic. These lineage maps are updated automatically as your data flows change.
Pricing Plans
Enterprise
Unknown Price• Advanced data monitoring
• Automated field-level lineage
• PII detection
• Business glossary integration
• Impact assessment notifications
• Usage analytics
• SOC2 compliance
• Data ecosystem copilot
Job Opportunities
Front End Engineer
Eliminate data silos and build organizational trust using an AI-powered copilot that automates lineage, monitoring, and governance across your data ecosystem.
Benefits:
Profit Share / Equity Packages
Flexible Work Options
Meaningful Work
Company Retreats
Experience Requirements:
2-4 years of experience in a front end, full stack engineering or related technical role
Other Requirements:
Strong proficiency in React, JavaScript/TypeScript and modern ES6+ features
Solid understanding of HTML, CSS, Web components, and responsive design
Familiarity with state management patterns and libraries like zustand and redux
Experience writing unit, integration, and end-to-end tests using vitest or playwright
Good understanding of debugging and troubleshooting using browser dev tools
Responsibilities:
Build scalable web applications
Work across the full front end stack
Implement new features
Write tests and ensure code quality
Collaborate with other team members to review and provide feedback on their code
Show more details
Python Integration Engineer
Eliminate data silos and build organizational trust using an AI-powered copilot that automates lineage, monitoring, and governance across your data ecosystem.
Benefits:
Profit Share / Equity Packages
Flexible Work Options
Meaningful Work
Company Retreats
Experience Requirements:
2-4 years of industry experience as a Software or Data engineer
Other Requirements:
Solid programming skills in Python
Practical experience building or maintaining integrations, APIs, or connectors
Working knowledge of the modern data ecosystem (Snowflake, BigQuery, dbt, etc.)
Knowledge of software testing principles and experience writing unit tests
Strong problem-solving and analytical skills with attention to detail
Responsibilities:
Design, build, and maintain scalable integrations with databases, BI tools, and ETL platforms
Troubleshoot and resolve integration issues reported by customers
Collaborate with product and engineering teams to prioritise integration work
Ensure code meets quality standards by building unit and performance tests
Stay current with changes to third-party APIs and platforms
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Ratings & Reviews
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