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Data person, who dat?

Data person, who dat?
By Arpit Choudhury • Issue #12 • View online
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In the previous issue, I had covered the role of people and processes in building a data stack. 
Today, I want to share my thoughts on something I’ve been thinking a lot about – Data People.
Disclaimer: I am vendor-neutral and I don’t make affiliate revenue or referral fees from data companies I refer to.

Data People
It’s a term that’s thrown around a lot these days and it generally refers to folks working as Data Engineers, Analysts, Scientists, Analytics Engineers, and Heads of Data teams. Let’s refer to these as core data roles
But does it mean that someone who doesn’t carry one of these titles cannot identify as a data person?
Let’s shift gears for a second and talk about the Growth function. I’m sure you have seen “Growth” being used in conjunction with many different titles. I’ve seen Growth (yes, just growth), Growth Manager, Head of Growth, Product Growth, and Growth Marketing to name a few. 
Folks who attach Growth to their titles work across Product, Marketing, Sales, Customer Success, and Operations. And this is perfectly fine. 
I personally believe that everybody in an org contributes to growth – whether that’s growing the brand, the user base, the revenue, the number of paying customers, the number of partners, or even the number of employees.
Similarly, someone who works with data every day to make decisions or to power customer experiences is as much a data person as the one who makes the right data available in the right place.
In fact, if you know a really good Product/Marketing/Growth/Sales (GTM) person, it is likely that they understand the data that is made available to them and make use of that data in their day to day activities – here are some common examples:
  • Product uses data to understand user behavior and build better products
  • Growth uses data to build personalized experiences throughout the user journey 
  • Sales uses data to identify the accounts they should go after 
  • Marketing uses data to measure the relevance of the traffic driven by their efforts
There is a growing number of GTM folks who do a lot of cool things with data, and at the same time, there are folks with data engineering or analytics experience shifting to GTM roles. 
Data Person Skills
For those working outside of data teams, it’s unclear what one needs to know to call oneself a data person. And as the data space continues to explode, the divide between data people and non-data people is only getting bigger.
In fact, this divide was one of my motivations behind starting DLA as I’ve never worked as part of a data team or held a title containing “Data” but having worked with data at scale as a Head of Growth, I do identify as a data person.
Unless one wants to work in one of the core data roles, there isn’t a specific course or learning path to become a data person. Learning specific tools (or types of tools) plays a big part in becoming a data person, but at the same time, the tools one needs to know and the skills one needs differ from role to role.
  • Product and Growth professionals must understand how customer data is collected, stored, analyzed, and acted upon, which means at the very least, they need to be familiar with Product Analytics and Event-based Engagement tools. 
  • Sales professionals need to know their way around complex CRM tools but in the PLG era, they also need to understand product-usage data to identify key accounts and power users using a Data Activation tool. 
  • For Marketers, Google Analytics is not enough – they should be able to use Product Analytics tools to go beyond looking at performance metrics and measure the true impact of their campaigns.  
Additionally, those who want to level up and acquire a versatile skill to work with and analyze different types of data should consider learning SQL – it’s not difficult at all and there are some really great learning resources out there. 
Learning Resources
📘 If you work in Product or Growth and wish to level up your data literacy, check out my free microcourse that covers everything you need to know about Customer Data
📗 If you’re keen to learn SQL, I’ve curated some really good SQL courses here.
📕 If you’d like to dig deeper into analytics and data modeling, this free book is highly recommended
📙 If you’re interested in becoming a data engineer, check out this learning path that offers a bunch of free and paid resources
📘 If you’re a data analyst interested in analytics engineering, you should definitely check out this upcoming cohort-based course
New at Data-led Academy
👉 You can now discover Data Discovery tools like Secoda, Select Star, Castor, and Atlan as well as Data Observability tools like Falkon, Bigeye, and Monte Carlo.
👉 New tools have been added to the Analysis and Activation categories including Deepnote (a data science notebook) and Jitsu (a Segment alternative).
👉 We’re working on a new brand as Data-led Academy doesn’t portray what we’re building for data companies and practitioners. That said, DLA is here to stay and will continue to offer free learning content.
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Arpit Choudhury

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