Find Every Dataset Faster with Data Catalog Services
The Hidden Cost of Untagged, Undocumented Data
Your Team Cannot Find the Data They Need
- Analysts ping six people just to confirm a single column’s meaning
- Critical datasets sit unused because nobody knows they exist
- New hires take months to map your warehouse on their own
- Reports use outdated tables because the right ones stay hidden
- Data teams answer the same “where is X” question every week
Metadata Lives in People’s Heads, Not Your Systems
- No one documents column logic, owners, or refresh schedules
- Tribal knowledge controls who can access which dataset
- Data lineage exists only in scattered Confluence pages
- Audit trails break the moment a senior engineer resigns
- Compliance teams cannot prove what data flows where
You Pay for Data Tools You Cannot Govern
- Snowflake and Databricks costs grow every quarter without controls
- Duplicate tables waste storage and confuse downstream reports
- Sensitive PII sits in tables nobody flagged as restricted
- Data quality issues spread because lineage stays invisible
- Leaders cannot trust dashboards built on untracked sources
Data Catalog Services Built for Discovery and Trust
We connect, tag, and document every data asset so your team finds what they need in seconds.
Most catalog projects fail because they treat metadata as a side task. We start with your highest-value datasets first and document them with business context, owners, and lineage your team can use.
We integrate the catalog directly into your existing stack. Slack lookups, Power BI metadata, and Snowflake permissions all flow through one searchable layer your team adopts on day one.
Strengthen Your Data Foundation
Explore Data Pilot services that complete your data discovery and governance ecosystem.
Data Strategy
Build the roadmap that connects your catalog to real business outcomes.
Data Governance
Enforce policies, access rules, and compliance across every data asset.
Data Quality
Keep every cataloged dataset accurate, fresh, and ready for production use.
Master Data Management
Build one trusted version of customers, products, and core records.
Data Integration
Connect every source so your catalog reflects your full data landscape.
Analytics Engineering
Turn cataloged data into clean models your business teams can trust.
Data Strategy
Build the roadmap that connects your catalog to real business outcomes.
Data Governance
Enforce policies, access rules, and compliance across every data asset.
Data Quality
Keep every cataloged dataset accurate, fresh, and ready for production use.
Master Data Management
Build one trusted version of customers, products, and core records.
Data Integration
Connect every source so your catalog reflects your full data landscape.
Analytics Engineering
Turn cataloged data into clean models your business teams can trust.
The Tools We Use to Build Your Data Catalog
Production-grade platforms that scale with your data and integrate with your existing stack.
Discovery & Lineage
The search layer
DataHub
Open-source catalog with strong lineage, search, and team collaboration features.
Open Metadata
All-in-one platform that unifies discovery, quality, and governance in one tool.
Enterprise Governance
The control layer
Unity Catalog
Native Databricks layer that governs tables, models, and files across workspaces.
Master Data Management
The trust layer
Semarchy
Enterprise hub for managing complex, multi-domain reference and master data.
Structured Path from Data Chaos to Trusted Discovery
Our 4-step delivery process makes every dataset documented, governed, and easy to find.
Diagnose
(Week 1)
Design
(Week 2)
Build
(Week 3-5)
Validate
(Week 6)
Comparison: The Better Way to Run Your Data Catalog
The Data Pilot Way
Frequently Asked Questions
Answers to your top questions about Data Catalog Services.
What is a data catalog and why do we need one?
A data catalog is a searchable inventory of every dataset, dashboard, and pipeline in your stack. It saves your team hours each week and prevents duplicate work.
Which catalog tool is right for our company?
We pick the right tool based on your stack. Databricks teams get Unity Catalog. Open-source preference goes to DataHub or Open Metadata. Enterprise master data needs Semarchy.
How long does a data catalog implementation take?
Most projects ship in six weeks. We start with your highest-value datasets first so your team sees value within the first sprint.
Will the catalog disrupt our existing pipelines?
No. We deploy the catalog as a metadata layer on top of your warehouse. No code changes, no pipeline rewrites, no downtime.
Who owns the catalog after launch?
You do. Full configuration, documentation, and code transfer to your team on handover. No vendor lock-in.
How does the catalog handle sensitive data?
We tag PII and restricted data during the build phase. Role-based access rules then enforce who can see what at the catalog layer.
Find Every Dataset in Seconds, Not Days
Ready to see exactly which datasets your team can document and govern first?
- Identify the three datasets that will deliver the fastest discovery wins
- Review a metadata blueprint matched to your warehouse and BI tools
- Confirm which catalog platform fits your stack, team, and budget
- Walk away with a phased rollout plan your team can launch in weeks
- Understand the exact ROI before committing to a full catalog build