I am the Sr. Director of Data at Strava. As an analytics professional and a former software engineer, I've been involved in shaping great products for companies big and small for the last 14 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 (Komodo, Fitbit etc). 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.
A few talks where I share my thoughts and learnings:
- Preventing, diagnosing & curing bad data (Dec'20)
- Tech Trek podcast - Analytics discussion (Oct'20)
- How would Sherlock Holmes fix bad data? (June'20)
- Building Great Products with Effective Analytics (Sept'19)
- Thoughtful Analytics to Drive Product Success (Nov'18)
- Driving Product Adoption with Einstein at Salesforce (Sept'18)
A few articles where I share my thoughts and learnings:
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.
- 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.
- 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
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
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.