Data Knowledge

Tools to guide you in your data science journey

I am the former Head of Data & Analytics from Strava and Komodo Health. I am also an Angel Investor in data companies. As a data professional and a former software engineer, I've been involved in shaping great products for companies big and small for the last 16 years. I've worked on analyses across various business functions including product, operations, sales, marketing and customer support in Fortune 500 (Salesforce) companies and small start-ups (Fitbit). All the products I've worked on had more 40M+ users, which trained me on the nuances of dealing with data at scale.

My job is to use data to tell effective stories that inspire action and spur tangible business growth. Over the years I've consolidated my learnings into reusable frameworks, that can be applied to extract meaningful insights for various products and services.

I am currently offering multiple data courses:

A few talks where I share my thoughts and learnings:

A few articles where I share my thoughts and learnings:

Preventing, diagnosing & curing bad data - Keynote

Women in Data Science Miami Conference in Apr'21

Bad data has the capacity to ruin your business, and can have dire consequences for your users. Inaccuracies and biases in your data can result in costly outcomes. In this talk, I highlight the typical lifecycle of data, and the phases where bad data gets introduced. I also cover ways to fix issues.

This talk was the Keynote at the WiDS Miami 2021 conference.

A Window into the Future of Fitness Tech

General Assembly Panel in Mar'21

Panel discussion with fitness industry veterans on the future of fitness tech.

  • What is the role of data for fitness enthusiasts?
  • How are fitness and health relevant to the discussions around racial justice?
  • How do data biases show up in fitness products, and how can that be addressed?

Preventing, diagnosing & curing bad data

Online event by Crunch Conference in Dec'20

This talk covers the lifecycle of bad data, and how issues can be introduced during the different phases. I also touch on the biases caused by bad data. The talk covers some common ways to diagnose and cure bad data quality issues.

All of the examples are anchored to the healthcare use cases, which was the focus of this virtual event.

Tech Trek podcast - Analytics discussion

Discussion with Arash Bromand in Oct'20

Discussing the following topics:

  • Where is the analytics space headed? What are the best skills for analysts to learn?
  • How do you align business needs with individual growth goals?
  • How can an analyst stand out in interviews?
  • Advice for Women in Tech to succeed at work

How would Sherlock Holmes fix bad data?

Webinar for Data Umbrella in June'20

Exploring the following topics :

  • What is bad data? What is it not? How does it manifest? What are the common phases that create bad data?
  • Why should organizations care? How does it affect Data Scientist morale?
  • How do we solve bad data by thinking like Sherlock Holmes?
  • Example problem with framework and coding snippets (SQL)

Building Great Products with Effective Analytics

Talk at TechDay LA in Sept'19

How do companies build great products using data? This talk walks through the framework for driving product success through analytics. A quick SaaS case study is included as well.

Three Takeaways:

  • How to be an impactful analyst
  • How to create a framework to use to build great products
  • How to use the framework by seeing it applied in real-world situations

Thoughtful Analytics to Drive Product Success

Presentation at Level Analytics in Nov'18

This talk shares the powerful "Thoughtful Analyst Framework" (designed by me) that can be used by analysts to generate the maximum value.

Key Takeaways:

  • Background on how the frameword was created
  • Guiding principles
  • Steps in the framework
  • Measuring success

Driving Product Adoption with Einstein at Salesforce

Presentation at Dreamforce in Sept'18

My team and I spoke about our internal project at Dreamforce'18.

How did Salesforce use Einstein to rapidly build an application that helps salesforce provide an optimal product experience to their customers and maximize adoption? The Data Intelligence (Di) team within Salesforce seamlessly merged Einstein technology and design thinking to build an application driven by a Net Adoption Score, used to inform and guide product adoption.

Thoughtful Analytics: An introduction to the framework

Thoughtful Analytics: An introduction to the framework

Data is the fuel needed to build successful products. Thoughtful analysts transform that fuel into energy by using a strong foundation of values, and mindful actions that result in effective outcomes.

This framework provides some structure for analysts looking to generate maximum value through their work.

Thoughtful Analytics: Know the Product

Thoughtful Analytics: Know the Product

The Thoughtful Analytics framework has 4 pillars. The first pillar is to Know the Product.

To analyze something effectively, you need to first understand it.

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