Most governance programs produce policies and committees. Data Semantics puts governance into the platform itself: named owners, quality rules that run on every load, one trusted record per customer and supplier, and access controls AI agents respect.
Your data today
Duplicate customersUnknown ownersUntagged personal dataQuality checked by handAccess by habitAI does the checking
Owners make every decision
Governed in
Microsoft PurviewDatabricks Unity CatalogSnowflake HorizonData Semantics sets up data governance and data quality inside the platform you already run, whether Microsoft Purview, Databricks Unity Catalog or Snowflake Horizon. AI does the profiling, classification, matching and monitoring, and your owners make the decisions.
When people read a report, they notice when a number looks wrong. An AI agent does not; it acts. Governance that lives in policy documents cannot stop that. Governance that runs in the platform can.
Each one runs in your platform and is owned by a named person.
Rules on the data that matters most, checked continuously and fixed at the source.
One trusted record for each customer, supplier, product or account across systems.
People can find data, understand it and see who owns it.
Sensitive data found, labelled and protected according to your policies and local rules.
See where every number comes from, and what breaks if a source changes.
Clear rules for which data AI agents may read and act on, and how.
AI takes on the slow, manual parts of governance, so owners spend minutes deciding, not weeks investigating. Every rule, label and merge is approved by a named owner.
AI scans key tables for gaps, duplicates, outliers and invalid values and scores quality by domain.
You get: quality scores by domain
Checked by: data stewards
AI finds personal and sensitive data and proposes labels.
You get: proposed sensitivity labels
Checked by: owners confirm every label
AI proposes quality rules from the data and existing reports.
You get: a draft rule set
Checked by: owners approve each rule
AI finds duplicate customers, suppliers and products and proposes golden records.
You get: merge candidates
Checked by: owners approve every merge
AI maps how data flows from source to report and flags the impact of changes.
You get: traceable numbers
Checked by: our governance team
Each issue goes to the right owner with the evidence attached, and is chased until resolved.
You get: issues actually closed
Checked by: owners and stewards
Tell us which domain worries you most. We’ll show you how we would measure it and what we would fix first.
We set governance up natively in the platform you run, and connect them where your estate spans more than one.
Catalog, glossary, lineage, sensitivity labels and access policies across Fabric, Azure and Microsoft 365.
See what we doCentral catalog, fine-grained access, tags, lineage and audit for every table, model and file in the lakehouse.
See what we doObject tagging, classification, masking and row-access policies, lineage and access history inside Snowflake.
See what we doA short assessment shows where you stand and what to fix first.
We profile and classify your key domains, and our consultants turn the findings into a plan.
We put governance live domain by domain and keep it running with your owners.
Owners and rules only work when everyone agrees what the data is. Our governance is anchored in your ontology: each business entity has a definition, an owner, quality rules and access policies, mapped to every system and table where it lives.
Duplicate customers and vendors across two organizations matched into golden records, with merge rules approved by finance and every decision on record.
Units, leases, tenants and rent roll defined once across Yardi and ERP data, so leasing, finance and leadership report the same numbers.
No separate governance silo. Rules, labels and lineage live where the data lives.
Common governance tooling.
Microsoft Solutions Partner for Data & AI and Digital & App Innovation. Beyond Microsoft, Data Semantics delivers on Databricks, Snowflake, AWS and Fivetran, and recommends what fits your estate rather than one vendor.
About governance and quality
Governance sets the ownership, definitions, rules and access. Data quality management measures and fixes the data against those rules, continuously. You need both.
AI agents act on data, so they need data that is accurate, clearly owned and approved for their use. We define which data each agent may use, apply those rules in its context and monitor it.
Governance decides who owns the data, how good it must be and who may use it. A semantic layer and ontology define what the data means and how it connects. AI agents need both: trusted, permitted data and a clear understanding of it. Data Semantics delivers them together or one at a time.
What you get
A golden record is the single trusted version of a customer, supplier, product or account, built by matching duplicates across systems and choosing the best value for each field. It is fed back to the systems that use it.
Quality rules, such as completeness, validity, uniqueness and agreed business checks, run automatically on the data as it loads. Scores are published to owners, breaches raise alerts, and AI suggests the likely cause, so issues are fixed before they reach a report or an AI agent.
AI scans data sets and classifies personal, financial and other sensitive fields. Data Semantics then applies labels, masking and access policies in Purview, Unity Catalog or Horizon, and keeps the evidence for audits.
Yes. Data Semantics find and label personal and sensitive data, apply access and residency controls, and produce evidence for audits, working with your legal and compliance teams on the rules that apply to you.
Tools
Usually not. Data Semantics implements governance in the platform you already run: Microsoft Purview for Fabric and Azure estates, Databricks Unity Catalog for Databricks, and Snowflake Horizon for Snowflake. Catalog, lineage, classification, tags, masking and access policies are set up natively in each, and connected where estates span more than one platform, so there is no extra tool to license or keep in sync. Where a separate tool is already in place, we connect to it.
Time and ownership
An AI & Data Readiness Assessment takes a few weeks. The first domain, with owners, rules and golden records live, usually follows within a few months.
Your named owners and stewards, supported by AI-assisted stewardship and, if you choose, our managed service.
Our AI & Data Readiness Assessment scores your key domains for quality, ownership, sensitivity and AI readiness, and shows what to fix first.
