Feature Store Master Class for 2021. MLOps Coffee Sessions #26 with Vishnu Rachakonda of Tesseract Health, Daniel Galinkin of iFood, Matias Dominguez of Rappi & Simarpal Khaira of Intuit, all talking about the various stages they are in right now of building and buying feature stores for their machine learning infrastructure.

//Bio
Vishnu Rachakonda
Machine Learning Engineer at Tesseract Health. Coffee sessions co-host.

Daniel Galinkin
One of the co-founders of Hekima, one of the first companies in Brazil to work with big data and data science, with over 10 years of experience in the field. At Hekima, Daniel was amongst the people responsible for dealing with infrastructure and scalability challenges. After iFood acquired Hekima, he became the ML Platform Tech Lead for iFood.

Matias Dominguez
A 29-year-old living in Buenos Aires, past 4.5 years working on fraud prevention. Previously at MercadoLibre and other random smaller consulting shops.

Simarpal Khaira
Simarpal is the product manager driving product strategy for Feature Management and Machine Learning tools at Intuit. Prior to Intuit, he was at Ayasdi, a machine learning startup, leading product efforts for machine learning solutions in the financial services space. Before that, he worked at Adobe as a product manager for Audience Manager, a data management platform for digital marketing.

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Connect with Demetrios on LinkedIn:   / dpbrinkm  
Connect with David on LinkedIn:   / aponteanalytics  
Connect with Vishnu on LinkedIn:   / vrachakonda  
Connect with Daniel on LinkedIn:   / danielgalinkin  
Connect with Matias on LinkedIn:   / mndominguez  
Connect with Simarpal on LinkedIn:   / simarpal-khaira-6318959  

Timestamps:
[00:00] Introduction to guest speakers.
[00:33] Vishnu Rachakonda Background
[01:00] Matias Dominguez Background
[01:42] Simarpal Khaira Background
[02:13] Daniel Galinkin Background
[03:13] Are Feature Stores for everyone?
[04:02] Matias' Feature Store background
[10:25] Simar's Feature Store background
[13:07] Daniel's Feature Store background
[17:09] Customizing Feature Store
[17:34] Simarpal's process for Feature Store
[21:41] Matias' process for Feature Store
[25:39] Daniel's Modularity process for Feature Store
[31:14] Solution
[31:17] Simar's solution to build
[36:42] Consistency in transformation logic and processing generating features
[37:31] Matias' consistency solution
"One of the challenges that we have is to evangelize everyone into the importance of checking the data they're producing. That's one of the key things that can't be solved by libraries, frameworks, or any source of the system. It's a people and awareness problem." - Matias
[40:37] Daniel's consistency solution
[43:06] "How increasingly as organizations become more and more data-driven. We need access to the data to know how teams are doing, know what they need, and take deeper responsibility for that. They're making it harder for the company to really empower them...They may not know that totally because they were not confronted with that problem on a day to day basis." - Vishnu
[43:39] In terms of versioning that transformation logic and knowledge that goes into creating Feature Stores and allowing them to be reusable and consistent, how are you going to grapple with that?
[43:58] Simar's technical solutions to Feature Store
[46:03] "Any data scientist wants to know what is in the background. What's the transformation logic for the feature to be able to make that connection. It brings back the trust again." Simar
[48:06] How do you bake in best practices into the services that you offer?
[48:12] Daniel's best practices into the services they offer
[49:34] "It's too possible for you to do something wrong. You have to specify that wrong thing. That makes it harder to do that wrong thing." Daniel
[51:03] Simar's best practices into the services they offer
[51:54] "It starts with changing the mindset. Making people get the habit of what is the value here. Then you are producing features for consumers because tomorrow you could become a consumer. Write it in a way as you want to consume somebody's feature." Simar
[54:40] Matia's best practices into the services they offer
[56:51] "As part of that process, it should come with everyone's best practices to actually improve all features" Matias
[57:33] Can we try to rally around an idea of getting gamification involved in this feature store you can see different badges of are creating the most expensive features, creating most features, etc