Use Case Intelligence RSS Search use cases Search
Snowflake Software / SaaS San Francisco, CA

Autodesk

Data Lake / Data Warehouse Modernization

replace a costly, maintenance-heavy Spark and Athena ecosystem so customer 360 analytics, BI, and data science users could get reliable self-service insight.

Read the original story Explore all use cases
10x faster data ingestion and transformation
3x fewer staff needed to support data lake
ETL processes now run in minutes, not hours

Reported impact

Business outcome

Autodesk cut staffing needs for the data lake by 3x, accelerated ingestion and transformation 10x, and gave more teams a reliable foundation for customer 360, BI, and analytics use cases.

  • Cost Reduction
  • Productivity Improvement
  • Scalability

Solution

Autodesk uses Snowflake and Snowflake Marketplace as the core of its Customer 360 Analytics Data Platform, replacing a brittle Spark and Athena ecosystem with a more scalable BI and data science foundation. Ingestion and transformation workloads now run natively in Snowflake with standard SQL, connectors, drivers, and bidirectional sync to Autodesk’s cloud object storage, which simplifies pipeline development and reduces homegrown code. Snowflake Marketplace adds ready-to-query datasets for behavior analysis without heavy ETL, while the platform’s multi-cluster architecture gives product teams and business users reliable performance for dashboards, customer experience analysis, churn prediction, and opportunity discovery. The rearchitected platform reduced maintenance work, improved governance, and expanded self-service analytics without the performance and trust problems that had pushed teams toward shadow environments.

Data flow

Customer and operational data syncs between Autodesk’s cloud object storage and Snowflake, where ingestion and transformation run in a single platform. Ready-to-query external datasets from Snowflake Marketplace enrich the environment, and curated datasets are consumed by BI, CX, and analyst teams for self-service insight.

Solution architecture

2 components · 2 layers
  1. Ingest
    • Snowflake Marketplace Supplies ready-to-query external datasets that accelerate customer and behavior analysis without new ETL work.
  2. Storage
    • Snowflake Provides the multi-cluster data platform for ingestion, transformation, BI, and data science workloads.

Architecture clues

  • A bidirectional sync to cloud object storage accelerated adoption of the new architecture.
  • Snowflake’s multi-cluster shared data architecture resolved dashboard performance issues.
  • The team enabled an end-to-end pipeline entirely in Snowflake with native SQL and broad connectivity.

Evidence from the source

10x faster data ingestion and transformation
3x fewer staff needed to support data lake
Our goal was to enable that end-to-end pipeline entirely in Snowflake
Snowflake Marketplace offered a convenient way to access ready-to-query data sets
Transparency Evidence & methodology 100/100 reference value · 79% 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 value100/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    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 confidence79%
  • 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
    4 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • 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. Snowflake

    Autodesk customer story

    First-party
    https://www.snowflake.com/en/customers/all-customers/case-study/autodesk/
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • First archived Oct 3, 2024 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
  • Sitemap last modified Jul 11, 2026 · Snowflake · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

Related

Similar use cases

See all like this
Snowflake Modified · Sep 11, 2026 Order.co Software / SaaS New York, NY, USA replace a warehouse where development workloads, production pipelines, ad hoc analytics, and real-time traffic competed for the same resources, creating operational risk and scaling complexity. 2 - 7x Faster analytics queries Data Lake / Data Warehouse Modernization Snowflake · dbt Google Cloud Archived · Sep 9, 2026 Etsy Software / SaaS Global To serve its massive community, Etsy relies on multiple compute engines to process vast amounts of structured and unstructured items and search data. Previously, users read and wrote to Google Cloud Storage using Apache… Accelerated data joining by up to 60% Data Lake / Data Warehouse ModernizationIT Operations Automation BigQuery · Cloud Storage · Managed Spark Databricks Jul 28, 2026 OpenAI Software / SaaS United States OpenAI’s data platform powers one of the fastest-scaling products in tech history. ChatGPT, the OpenAI API, and the internal tools used by thousands of OpenAI employees require a foundation that can withstand sudden… $400K/month Storage costs eliminated by marketing team Data Lake / Data Warehouse ModernizationReal-time Analytics Databricks Data Warehouses · Databricks Jobs · Databricks SQL