Skip to main content

Value Creation Within the Modern Data Stack

Yali joins the show to explore what the modern data stack really means, and the right way businesses should approach data.

Dec 2022

Photo of Yali Sassoon
Guest
Yali Sassoon

Yali Sassoon is the Co-Founder and Chief Strategy Officer at Snowplow Analytics, a behavioral data platform that empowers data teams to solve complex data challenges. At Snowplow, Yali gets to combine his love of building things with his fascination of the ways in which people use data to reason.


Photo of Adel Nehme
Host
Adel Nehme

Adel is a Data Science educator, speaker, and Evangelist at DataCamp where he has released various courses and live training on data analysis, machine learning, and data engineering. He is passionate about spreading data skills and data literacy throughout organizations and the intersection of technology and society. He has an MSc in Data Science and Business Analytics. In his free time, you can find him hanging out with his cat Louis.

Key Quotes

The key to success is to have a value-driven approach. Start by identifying the different ways data can be used to to drive value in your business, then you work backward to identify what data is needed and how you can use it to drive that value. Keep your focus narrowly on that until you've delivered that value to that end user, to that line of business, but don’t stop there. Go the extra mile and make sure that the line of business understand the value and your business clearly understands the value.

The warehouse is where the data lives, so it performs a storage function, but it's also where all the computation happens. These technologies provide organizations with the ability to store and compute on data at unprecedented scale in ways that are much more economical than ever before. If you vizualize the modern data stack as a diagram from left to right, on the left you have the data and specialized ingestion tools that bring the data to the warehouse in the middle. Then within the data warehouse, the you are provided this computation so your team can transform the data that comes in into different derived data sets that can be used by different teams. 

Then on the right you've got your different BI tools for visualizing and consuming that data push it back into your different SaaS applications or different production systems. Those are, on a broad level, the core different components of the modern data stack. What we've seen over the last few years is more and more vendors and more and more boxes appear is as this kind of ecosystem has exploded around the cloud data warehouse to help organizations execute more and more use cases on that architecture.

Key Takeaways

1

Data teams need to stay focused on ensuring they are creating clear, measurable value for the business through how they implement the modern data stack.

2

A value-driven approach to the modern data stack starts with identifying the ways data can be used to drive value and working your way backward to identify what data is needed and how to use it to drive that value.

3

Organizations should always be open to optimizing the technology for the use case rather than forcing the use case to fit the technologies and the architecture that they want to adopt.

Related

How to Become a Data Scientist in 8 Steps

Find out everything you need to know about becoming a data scientist, and find out whether it’s the right career for you!

Jose Jorge Rodriguez Salgado

12 min

Top 2022 Resources to Sharpen your Data Skills

Get access to our top-performing resources from 2022, including webinars, blog posts, white papers, cheat sheets, tutorials, and articles, all designed to help you sharpen your data skills and scale your organization's data culture. Start learning and growing your data expertise today!
Adel Nehme's photo

Adel Nehme

14 min

21 Top Data Scientist Interview Questions

Explore the top data science interview questions with answers for final-year students and professionals looking for jobs.
Abid Ali Awan's photo

Abid Ali Awan

21 min

[Infographic] Data Science Learning Checklist

Use this handy checklist to guide your data science learning journey.
DataCamp Team's photo

DataCamp Team

4 min

Successful Data & Analytics in the Insurance Industry

Rob joins us to share In-depth knowledge of how insurance companies utilize data, the top skills to get data jobs in insurance and much more.

Richie Cotton's photo

Richie Cotton

47 min

Data Trends & Predictions for 2023

DataCamp Co-founders, Jonathan Cornelissen, and Martijn Theuwissen break down the top data trends they are seeing in the data space today, as well as their predictions for the future of the data industry.

Richie Cotton's photo

Richie Cotton

39 min

See MoreSee More