Data & Analytics Marketplace

01 / Overview

A marketplace for data, built like a product catalog.

This case study outlines the development and implementation of the Data & Analytics Marketplace — a centralized platform designed to streamline how employees discover, govern, and utilize data assets within the organization.

The product brings consumers, data owners, and governance into one experience: people can find data products, templates, and proven use cases, understand whether they can trust them, and acquire them through a governed, self-service flow — without the duplicated effort and blind access requests that defined the old way of working.

02 / Problem

The Discovery Gap.

Before the marketplace, data was an asset the organization owned but couldn't easily put to work. Three pain points compounded each other:

Pain 01

Discovery

The primary pain point. Employees were often unaware of what data products existed at all, or of how to find the ones they needed.

Pain 02

Inefficiency & duplication

Teams repeatedly rebuilt work because they had no visibility into existing solutions or the use cases other departments had already developed.

Pain 03

Opaque governance

With no transparency into data quality, schema, or lineage, users had to request access blindly — never knowing if the data was fit for their purpose.

03 / Users & roles

Three roles, three distinct experiences.

Role-based access control shaped the product from the ground up: each role gets its own UI and capabilities, so the same platform serves the person consuming data, the person accountable for it, and the person administering the whole ecosystem.

Consumer

Data Consumer

Browses the catalog to find data products, templates, and use cases
Bundles what they need into a single request
Provides justification and a target analytics platform

Producer

Data Owner

Publishes data products and monitors their health via DQ metrics
Reviews and manages access through a dedicated approvals page
Grows the pool of trustworthy, available data

Governance

Marketplace Admin

Administers the catalog, categories, roles, and platform config
Oversees standardization and audit across the enterprise
Maintains the governed structure the marketplace runs on

04 / Requirements

Building a governed ecosystem.

Five core requirements anchored the work — each one targeting a specific gap from the problem above.

REQ 1

Unified discovery

A Discovery Catalog using product cards and tiles, with AI-powered search to browse active data products.

REQ 2

Transparent metadata

Detailed overview pages with business descriptions, Data Quality (DQ) scores, schema visibility — including PII and Confidential classification — and data lineage.

REQ 3

Streamlined access

A shopping-cart experience that lets users bundle multiple products and templates into a single request.

REQ 4

Governed approval workflows

A mandatory approval chain — the Reporting (1-Up) Manager, followed by the Data Product Owner.

REQ 5

Role-based access control

Distinct UIs and capabilities for Data Consumers, Data Owners, and Marketplace Admins.

05 / Solution

The Data & Analytics Marketplace.

The platform answers each pain point with a dedicated capability, organized into three pillars: discovery and context, governed acquisition, and value-add services. The screens below are from the shipped product.

A Discovery & context

Find data — and the proven ways to use it.

Users explore a hierarchical catalog of Data Products, Templates, and Use Cases. Use cases are the differentiator: by surfacing approaches other teams have already built, they let people reuse instead of rebuild — directly cutting duplication. Personalization and transparent metadata make discovery fast and trustworthy.

Consumer · HomeA home page that already knows what's relevant
Featured data products lead with their quality score, and templates surface by the user's stated interests — so discovery opens with trusted, relevant options instead of a blank search box. Add to Cart and Request Access sit right on each card.

Onboarding · PersonalizePersonalization captured at onboarding
A short setup records role, analytics skill level, and topics of interest — the signals that power the home page's recommendations, faster discovery, and a tailored learning path.

Data Product · MetricsThe trust dossier
Before requesting anything, users see DQ scores, per-table quality, data volume and trend, with tabs for schema, lineage, and use cases — turning “is this fit for purpose?” into a visible answer.

B Acquisition & governance

A standardized checkout for data access.

Acquiring data works like a governed checkout: users bundle products and templates into a cart, give a business justification, and pick a target analytics platform such as Databricks or Power BI. Workday / O365 integration routes the request to the right manager, and it moves through a clear two-step approval chain — Reporting (1-Up) Manager, then Data Product Owner.

STEP 01

Add to cart

Bundle products & templates into one request

→

STEP 02

Justify & target

Justification + platform (Databricks, Power BI)

→

STEP 03

1-Up Manager

Routing automated via Workday / O365

→

STEP 04

Data Owner

Owner approves and grants access

Acquire

Consumer · Request cartThe cart that makes bundling the default
Data products and templates collect in one Request Cart — each showing sensitivity (Confidential, Highly Confidential, Internal), quality, and consumer count — so a user checks out a whole analytics need in a single governed request instead of chasing access item by item.

Consumer · Request accessA request form that fills itself in
Requester details are auto-fetched from the employee profile (Workday / O365), so the user only states a reason for access. Product tier, score, and SLA sit alongside to keep the decision informed.

Consumer · My RequestsTracking the request after checkout
Bundled “Group” requests carry multiple products and templates as one item — each with its own status, SLA countdown, and PII-removed flag — replacing scattered, untracked tickets.

Govern & approve

Consumer · Approval workflowThe approval chain, made legible
A four-stage stepper — Submitted → Manager → Product Owner → Admin — shows exactly where a request sits, each stage's SLA, and an inline discussion for clarifications. Governance stops being a black box.

Admin · Access requestsA workspace for the people accountable
Stewards work a prioritized queue with one-click approve or reject, full requester context, and a governance rail spanning roles, domain categories, and audit logs — control they operate, not email.

Own & monitor

Data Owner · Active productsOwners watch their products' health
Each published product shows live quality score, subscriber count, status, and SLA expiry — and a clear path to become a publisher grows the pool of available data.

Consumer · DashboardEverything in one personal view
Request volume, engagement, contribution scores, and asset performance give each user a single place to track their activity across the marketplace.

C Value-add services & automation

More than a catalog — a way to move faster.

Beyond discovery and access, the marketplace bundles services that compress time-to-insight: ready-made templates, expert build services, and a path to grow data skills.

Automation

Analytics templates

Pre-built solutions for tools like Alteryx and Power BI automate repetitive tasks and expedite work.

Service

Our Services

Non-technical users can request build services from the EAPE team for specialized analytics projects.

Enablement

Learning Paths

A structured progression of courses helps employees build data skills, rewarding them with badges on completion.

Consumer · Template marketplaceA filterable gallery of ready-to-run templates
Pre-built solutions for Power BI, Databricks, Tableau, Alteryx and more are filterable by tool, category, domain, and complexity — each card showing inputs, build time, and skill level so teams reuse a proven workflow instead of starting cold.

Consumer · Request a serviceNon-technical users brief an expert team
The “Our Services” flow lets business users request a custom build from the EAPE team, with similar past use cases offered to pre-fill the brief and an SLA shown up front. Requester details auto-fetch as before.

Consumer · Learning PathSkills growth, tracked and rewarded
Enrolled courses, average progress, and achievement badges turn capability-building into a visible path — from Data Explorer to Analytics Expert — so the marketplace grows the skills to use the data it offers.

06 / Impact

From a discovery gap to a governed, trusted ecosystem.

The marketplace shifted the organization's relationship with its own data across four dimensions:

Value

Unlocking value

Empowering data owners to publish their assets increased the overall pool of available, usable data.

Trust

Enhancing trust

Static and automated quality scores let consumers trust data before they used it — closing the “is this fit for purpose?” gap.

Efficiency

Improving efficiency

Templates and build services reduced time-to-market for critical analytics projects.

Consistency

Standardization

Automated user-profile syncing and standardized custom filters (SBU, LOB) created a consistent experience across the enterprise.

— / Reflection

What I'd carry forward.

What worked

Designing for three roles from the start kept consumer speed and owner control from undercutting each other.
Surfacing use cases — not just raw data — attacked duplication at its source.
Treating metadata, DQ, and lineage as first-class made governance feel like trust, not a gate.

What's next

Deepen AI-powered search into role- and usage-aware recommendations.
Lower the publishing barrier for data owners to keep the pool growing.
Proactive DQ alerts so freshness and trust degrade visibly, not silently.