What can K do for you?
K is a Data Knowledge platform built around three core disciplines: data discovery, knowledge management, and data governance. The sections below map each key outcome K delivers — as seen on kada.ai — to the specific features that power it.
Whether you're a data user trying to find trusted data, a governance manager trying to maintain control, or a data owner managing your assets, this page shows you which features to reach for and why they work together.
Data Discovery — Find and trust data quickly
The outcome: Data consumers can find the right data asset, understand it in context, and know whether to trust it — without needing to chase down a data owner.
How K delivers this:
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Feature |
Role in this outcome |
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The central source of knowledge for any data asset — combining automated metadata with manually curated context so users understand how, where and when to use it |
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K's unique algorithm surfaces a trust signal for every asset, guiding users toward reliable data and helping managers spot what needs attention |
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My Ecosystem gives each user a personalised view of the assets they own, use, follow and manage — making it easy to return to the right data fast |
Who this is for: All users — especially data consumers and analysts onboarding to new data products.
Teams using K report up to 75% decrease in data discovery efforts.
Collections — Categorise and organise your data ecosystem
The outcome: Data assets are grouped, categorise, and governed using a consistent framework — from domain structure to PII detection to business glossaries — so that users can find, trust, and understand data at scale. Collections underpin discovery, governance, and knowledge management across the platform.
How K delivers this:
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Feature |
Role in this outcome |
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K's built-in platform collections (Zone, Usage, PII) provide out-of-the-box classification maintained automatically — no manual effort required |
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Align data assets to business domains and sub-domains — giving governance managers a structured, accountable way to organise ownership across the estate |
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K's automated scanner detects and flags personally identifiable information — linking affected assets to dedicated PII collections for targeted governance action |
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Link business vocabulary to technical assets — enabling business users to navigate and understand data using familiar language |
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Visualise what's linked to a collection, identify coverage gaps using lineage, and link missing items directly from the map |
Who this is for: Data Governance Managers, Data Managers, business analysts, and K Administrators.
Usage & Insights — Understand how data is being used
The outcome: Data owners, governance managers and admins get visibility into which assets are actively used, by whom, and how — so they can focus their efforts where it matters most.
How K delivers this:
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Feature |
Role in this outcome |
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A powerful multi-tab dashboard surfacing usage, connectivity, governance gaps, quality issues, and performance metrics across the data estate |
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A dedicated view for data owners and stewards to review governance, quality and usage metrics for the assets they are responsible for |
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Per-asset usage signals — who is using a data item, how frequently, and where it sits in its lifecycle |
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Self-service Q&A and scheduled exports for data managers and admins to interrogate the data ecosystem without writing queries |
Who this is for: Administrators, data owners, data stewards, and governance managers.
Intelligent Lineage & Change Mgement — Trace data end-to-end, and act when things change
The outcome: Anyone can follow a data asset upstream to its sources and downstream to its consumers — and when something changes, the right people are notified automatically so impact is scoped quickly and resolution time is minimised.
How K delivers this:
Understand your data flows
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Feature |
Role in this outcome |
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Visualise field-level lineage including calculations and logic. Maps automatically update as data flows change |
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Layers usage data on top of lineage — showing which flows are actively used, by which teams, and for what purpose |
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Uses lineage to scope the blast radius of a change before it happens — or to trace root cause when something breaks |
Respond when data changes
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Feature |
Role in this outcome |
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K catalogs and manages changes to data items, maintaining a chronological history of what changed and when |
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Turns change events into personalised notifications for the people directly downstream — fast-tracking incident investigation and root cause analysis |
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Complete tasks in bulk to speed up implementation of changes across affected assets |
Who this is for: All users for viewing lineage; data owners, governance managers, and data project teams for change management.
📉 Teams report up to 72% decrease in data migration change management efforts and a 65% increase in efficiency managing data incidents using K's lineage, impact assessment, and automated notifications together.
Data Governance — Govern data at scale
The outcome: Governance isn't a separate workstream — it's embedded into how people interact with data every day. Policies are applied at the point of use, not bolted on afterwards.
How K delivers this:
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Feature |
Role in this outcome |
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The profile is where governance context lives — ownership, classification, policies, and quality context in one place |
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Makes governance visible and actionable for every user — not just admins |
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Gives data owners and stewards a focused view of their governance responsibilities and the health of their assets |
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Automatically identifies and classifies personally identifiable information across the data estate |
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Applies governance tags at scale using automation rules — reducing manual classification effort |
Who this is for: Administrators, data governance managers, and data owners.
K Applications — Purpose-built tools for high-value workflows
The outcome: Data teams have task-focused applications for the most demanding workflows — scoping a migration, auditing embedded code logic, or applying bulk metadata updates at scale. Unlike core platform features, K Applications are optimised for specific jobs.
How K delivers this:
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Application |
Role in this outcome |
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Run upstream or downstream impact assessments at table, column, user, or collection level — returning a visual map and exportable list of all affected assets and users |
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Visualise how data flows end-to-end across sources, transformations, and outputs — with field-level detail, automatic and manually-added links, and advanced filtering |
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Search across all source object code in K to find specific logic, variables, or filter conditions embedded across measures, procedures, and other code objects |
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Apply large-scale metadata updates using a structured Excel import — updating properties, collection linkages, and governance attributes across many assets at once |
Who this is for: Data engineers, data managers, governance teams, and K Administrators tackling complex, high-impact tasks.
KADA Data Quality (KDQ) — Manage data quality checks
KDQ is KADA's data quality module — enabling you to define, run, and monitor data quality checks across your data estate, with results surfaced directly in K.
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Description |
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Connect KDQ to your data sources |
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Set up and manage KDQ workspaces |
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Push KDQ results into the KADA platform |
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Manage user access to KDQ workspaces |