What is a modern data stack?
Well, depends on whom you’re asking.
Ask a Head of Data or any data practitioner like an analyst, engineer, or scientist and they are likely to swear by Fivetran or Stitch for ingestion, Snowflake or BigQuery for warehousing, dbt for transformation, and Looker or Mode for BI. Essentially, the focus here is on analytics and therefore it is fair to refer to this as the modern data stack for analytics.
But if you ask a Head of Growth or any growth/marketing professional what their data stack looks like, you are likely to hear a different combination every time. This is because, unlike what is happening in data communities, there is very little discussion in growth communities around the modern data stack for growth.
So what exactly is it?
An extension of the modern data stack for analytics, a modern data stack of growth includes the tools that enable teams to analyze user behaviour to drive insights into the user journey and activate the data based on those insights to build personalized customer experiences across every touchpoint.
In this episode of The Data-led Professional podcast, hosts Claudiu and Arpit answer questions like:
- What are the different layers and tools of the modern data stack for growth?
- What is the role of Reverse ETL in this stack?
- What is event-based engagement?
You may read select excerpts from the episode here.