Privacy-Law Aware ML Data Preparation

The new PDP (Personal Data Protection) Law, which is similar to GDPR
and CCPA, is being implemented in India. All enterprise data services
including analytics and data science within the scope of the law are
required to comply with the same. Almost all major geographies have now
passed similar laws. The expectation of responsible data handling from
organizations is also increasing.

Enrich, our product, is a high-trust data preparation platform for
enterprises that provides data input to analysts and models at scale
everyday. Such data preparation services are on organizations’
compliance and privacy-activity critical path because of their
‘fan-out’ nature. They provide a convenient location to enforce policy
and safety mechanisms.

In this talk we discuss some of the mechanisms that we are building
for clients in our data preparation platform, Enrich. They include
opensource compliance checklist to help with the process, ‘right to
forget’ service using anonymized lookup key service, and metadata
service to enable tracking of the datasets. The focus will be on the
generic capabilities, and not on Scribble or our product.

Note: Will update this over the next few days and weeks


Outline/Structure of the Talk

  • 1. PDP and Impact (4 mins)
    • Provisions with Architectural Significance
  • 2. Scribble as Data Processor (2 mins)
  • 3. PDP Awareness (10 mins)
    • Opensource Compliance checklist
    • Data Inventory & Classification
    • Data Quality Monitoring
    • Consent manager & Data sanitization
  • 4. Open Challenges (1-2 mins)
    • Extending to enterprise beyond ML data prep

Learning Outcome

Audience will learn:

1. What it will take to support PDP Law

2. Machine-readable compliance checklist

3. Example implementation from Scribble

Target Audience

Data Scientists, Data product Managers, ML Engineers

Prerequisites for Attendees

1. Familiarity with production data science and feature engineering



schedule Submitted 1 year ago

Public Feedback