Databricks Commercial and Professional Services Global

EY-Parthenon

Data Lake / Data Warehouse Modernization · Document Processing · Real-time Analytics

They needed a partner — not just a platform — capable of scaling AI-powered workflows, unifying fragmented data sources and embedding intelligence securely and compliantly across global engagements.

30%–50% Efficiency gains, accelerating client decision-making and unlocking new opportunities
This allows teams to analyze complex Excel models (with 50+ tabs and tens of thousands of rows), extract only relevant KPIs and correlate them with broader sector insights — all within a single workflow.

Reported impact

Business outcome

EY-Parthenon achieved measurable business impact on Databricks, including 30%–50% Efficiency gains, accelerating client decision-making and unlocking new opportunities; This allows teams to analyze complex Excel models (with 50+ tabs and tens of thousands of rows), extract only relevant KPIs and correlate them with broader sector insights — all within a single workflow..

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement

Solution

The organization’s transformation hinged on finding a platform that could power their vision end to end, from ingesting massive volumes of unstructured data to enabling nontechnical users to extract insights with speed and confidence. The Databricks Data + AI Platform enabled EY-Parthenon to accelerate development, enforce data governance, embed AI and increase scalability across the DBS initiative. One of the first critical advantages was the inherent medallion architecture core to Databricks, which provided EY-Parthenon with a robust and proven methodology to manage the lifecycle of data, from raw ingestion (Bronze), to cleaned and structured data (Silver), to analytics-ready insights (Gold).

Data flow

Unstructured documents and reference data lands in Databricks and is transformed through managed pipelines stored in Delta Lake under Unity Catalog governance before being served through Databricks SQL

Solution architecture

5 components · 5 layers
  1. Compute
    • Agent Bricks Supports agentic or GenAI applications that EY-Parthenon uses to automate or accelerate work.
  2. Storage
    • Delta Lake Stores EY-Parthenon's curated datasets for analytics, machine learning, and operational use cases.
  3. Serving
    • Databricks SQL Serves dashboards, interactive analysis, and governed SQL workloads for business users at EY-Parthenon.
  4. Orchestration
    • Lakeflow Jobs Orchestrates recurring ingestion and transformation pipelines inside EY-Parthenon's lakehouse.
  5. Governance
    • Unity Catalog Provides access control, governance, and lineage across EY-Parthenon's shared data products and AI workloads.

Architecture clues

  • Cloud: Azure
  • Key product: Agent Bricks
  • Key product: Databricks SQL
  • Key product: Delta Lake
  • Key product: Unity Catalog
  • Medallion architecture

Evidence from the source

30%–50% Efficiency gains, accelerating client decision-making and unlocking new opportunities
At the center of this transformation was the EY-Parthenon Data Bureau Services (DBS) initiative.
EY-Parthenon advises on thousands of high-stakes engagements annually, generating massive volumes of structured and unstructured client data.
EY-Parthenon, a leader in strategy consulting, recognized growing client demand for data-driven insights alongside professional advice.
This allows teams to analyze complex Excel models (with 50+ tabs and tens of thousands of rows), extract only relevant KPIs and correlate them with broader sector insights — all within a single workflow.
Transparency Evidence & methodology 95/100 reference value · 89% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value95/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    2 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Databricks

    EY-Parthenon customer story

    First-party
    https://www.databricks.com/customers/ey-parthenon
    Source type
    Vendor-published customer story
    Published
    Aug 14, 2025
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Aug 14, 2025 · Databricks · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.