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Case Studies

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Transforming PLM workflows to enable business agility

Transforming PLM workflows to enable business agility

Transforming PLM workflows to enable business agility

How a large manufacturer automated data transformation and access control through medallion architecture

How a large manufacturer automated data transformation and access control through medallion architecture

The challenge

Manual efforts and evolving schema with outpaced legacy systems

Legacy data systems struggled to handle growing data volumes, evolving schemas, frequent updates, and complex access requirements. Their limited scalability and unreliable refresh capabilities led to stale, inconsistent data. As a result, many businesses resorted to manual processing, causing delays and fragmented insights, ultimately hindering timely decision-making, secure collaboration, and agility across the product lifecycle.



Key challenges

  • Delayed insights from non-scalable data architecture

  • High manual overhead in transformation processes

  • Limited secure access for diverse business units

  • No clear lineage or governance across data layers

  • Schema evolution in critical datasets

The solution

Medallion architecture for evolving schema and RLS to govern at scale

Dynamic data modeling

Metadata-driven schema generation

4-hour schema refreshes

Parallel refresh pipelines

Safe transformation

Access and governance

Maintaining mappings for various business and AAD groups for RLS

Audit-ready admin/user group separation

Role-based access and filtering

Implementation approach

1

Robust data architecture for scalable, secure analytic

  • 4-hour refresh

  • Validated tables

  • Schema handled

2

Validation process

  • Pre-check schema changes, datatype changes

  • 1-hour gap with respect to 4-hour refresh

  • Secure access

3

Security model

  • AAD mapping

  • Role filters

  • Admin/user split

The impact

Automating complexity, streamlining data migration, and accelerating outcomes

Operational agility

  • Timely insights replace lagging reports

  • Fast iteration on product decisions

  • Better coordination across production teams

  • Defined development lifecycle through metadata driven datasets

Data governance

  • Secure, role-specific access at scale

  • No manual filtering, system enforced

  • Auditable mapping via AAD and context keys

System performance

  • Minimized manual errors and rework

  • High-volume parallel pipeline execution

  • Better modelled data to create a presentation layer

Looking ahead

Qlik sense integration

  • Using presentation layer for business reporting with RLS

New changes onboarding

  • Easy to update any datasets which have schema changes

All rights reserved © 2025 Fractal Analytics Inc.

Registered Office:

Level 7, Commerz II, International Business Park, Oberoi Garden City,Off. W. E.Highway, Goregaon (E), Mumbai City, Mumbai, Maharashtra, India, 400063

CIN : U72400MH2000PLC125369

GST Number (Maharashtra) : 27AAACF4502D1Z8

All rights reserved © 2025 Fractal Analytics Inc.

Registered Office:

Level 7, Commerz II, International Business Park, Oberoi Garden City,Off. W. E.Highway, Goregaon (E), Mumbai City, Mumbai, Maharashtra, India, 400063

CIN : U72400MH2000PLC125369

GST Number (Maharashtra) : 27AAACF4502D1Z8

All rights reserved © 2025 Fractal Analytics Inc.

Registered Office:

Level 7, Commerz II, International Business Park, Oberoi Garden City,Off. W. E.Highway, Goregaon (E), Mumbai City, Mumbai, Maharashtra, India, 400063

CIN : U72400MH2000PLC125369

GST Number (Maharashtra) : 27AAACF4502D1Z8