databeats Arpit Choudhury

In this episode, our host Arpit Choudhury talks with Boris Jabes, CEO of Census, about how you can transform your data warehouse into your growth engine.
While many of us say that using the existing data in your warehouse is the best way forward, the real question is, how do we ensure that the growth team can effectively leverage the data that is already in the warehouse?
If you're looking for insights into making your data warehouse a powerhouse for growth, this episode is a must-watch. In just under 15 minutes, you'll receive answers to the following questions:
 • What does it take for a growth team to effectively leverage the data that's already in your warehouse? • What role does the data team play in empowering the growth team to utilize the available data? • How can data analysts and engineers engage in more impactful work and understand how their efforts drive business outcomes?
Happy watching! 🥁
You can learn more about Census here: https://www.getcensus.com/
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Reverse ETL has been gaining traction over the last few years. In this episode, our host Arpit Choudhury talks to Boris Jabes, CEO at Census about Reverse ETL and how it can improve customer experiences, especially given the increasingly complex user journeys spanning multiple touchpoints across various channels.

With data permeating every aspect of businesses, the conversation moves to how people in GTM (go-to-market) roles can leverage available customer data to improve campaigns via privacy-friendly personalization, and how modern tooling is enabling GTM folks to move even faster. 

Arpit also shares his take on the term "non-technical" and Boris describes the factors leading to the rapid adoption of Reverse ETL as well as the pros and cons of centralizing all the data in the warehouse.

Happy listening! 

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Come say hi 👋  on our socials! 

🧳LinkedIn: https://www.linkedin.com/company/data-beats/
📱Instagram: https://www.instagram.com/datafreakinbeats/
🐦Twitter: https://twitter.com/databeatsnow

What is data minimization? 

As per the GDPR, data minimization implies that “data controllers should collect only the personal data they really need, and should keep it only for as long as they need it” 

Organizations that collect data about their users and customers are essentially data controllers. Organizations control the data they collect and store and are responsible for the consequences of that data being misused. 

But that’s not all. 

To stay compliant with privacy regulations such as the GDPR, organizations need to ensure the following: 
They only collect and store customer data that they have received consent forThey do not continue storing any data that they’re supposed to delete from all they systems
The practice of Data Minimization ensures that organizations only collect and store data that they have an identified need for – they know why they’re collecting the data and how they’re going to use that data to improve the customer experience. Knowing the purpose of the collected data enables organizations to easily keep customers and regulators informed about what data is being collected, how it’s being collected, and where it is being used. 

It also makes it easy for customers to opt out from certain data collection practices because they know exactly what they will be losing out on – they need not continue sharing data in fear of losing access to a service or being subject to a degraded customer experience. 

It’s becoming the norm for organizations to collect ALL the data from ALL the sources and dump it ALL in the data warehouse. And this practice of collecting and dumping all the data is fueling the rise of “data swamps”. 

There’s a massive disconnect between data teams that implement data collection initiatives and non-data teams that need the data in the tools they use every day. And that is the biggest cause for a data swamp – too much raw, unusable data that not only increases storage cost but also increases the risk potential for the organization.

Therefore, organizations that are serious about adopting privacy-friendly personalization practices must embrace the practice of Data Minimization — sooner rather than later.

Welcome to Round 2 of the CDP Rapid Fire!
In this round, our host, Glenn Vanderlinden asked the guests follow-up questions based on their responses to the statements from round 1.
This one is packed with too much good advice and too many laughs, leaving no reason to miss it.
In fact, there was so much goodness in this episode that I had to cut it short. In the coming weeks, we’ll release the rest as short snippets so stay tuned (and subscribe if you haven’t already). 
P.S. If you’re a recent subscriber and are wondering what’s with CDPs being all the rage, please have a quick look at our campaign, Let's End The CDP Battle: https://databeats.community/p/lets-end-the-cdp-battle-a-campaign
If you prefer to read, here you go.

It’s been 10 years since the term “Customer Data Platform” was coined by David Raab, Founder of the CDP Institute. Needless to say, the definition of a CDP has evolved a lot, and slowly but surely, the beast that is the CDP has grown new heads – or components – each of which serves a specific purpose.   

Part of the confusion regarding what a CDP even means stems from the fact that companies that recognized the opportunity early have been pushing the CDP envelope by building or buying complementary solutions, while others are selling CDP components but calling themselves a CDP nonetheless. 

Segment, which was acquired by Twilio in late 2020, has been around since the early days. And so has their VP of Product, Kevin Niparko who’s been with Segment since 2015 and has had a front-row seat to how the CDP space has evolved over the last 8 years. 

In this episode, our host, Arpit Choudhury, and our guest, Kevin Niparko rapidly discussed his early days as a growth analyst at Segment followed by the key innovations that put Segment on the map. We concluded the episode by discussing the two underrated but extremely important components of the CDP – data quality and privacy.

I learned a lot while researching for this episode and my key takeaway was that the industry needs to focus less on what’s new and flashy and take a moment to acknowledge the innovations that enable most of what’s new and flashy. 

Fun fact: In late 2015, Segment launched its Warehouses product that let customers sync data to their own Redshift or Postgres database – long before the rise of the cloud data warehouse. 

P.S. A conversation about CDPs in 2023 is incomplete without shedding some light on the Composable vs Packaged CDP debate. 
If you prefer to read, here you go: https://databeats.community/p/the-evolution-of-the-cdp

We recently managed to bring together some leading minds in the CDP arena — not to fight or argue, but to find some common ground and put an end to the debate-turned-battle between the Composable and the Packaged CDP camps. 
Here’s the guest list:
Boris Jabes from Census represents the Composable CDP campMichael Katz from mParticle represents the Packaged CDP campDavid Raab from the CDP Institute represents the neutral party that cares deeply about the category (he coined the term, Customer Data Platform, after all)Jacques Corby-Tuech, a RevOps practitioner, represents the end user or the beneficiary of a CDPMatthew Niederberger, a CDP consultant, represents folks who implement CDPs of all typesAnd some context on how we landed here:
At Human37, Glenn implements CDPs of all types for companies in Europe. And in my quest to grow this community (thank you for being a part), I talk to a lot of people — all types of stakeholders essentially.
And Glenn and I found one thing in common:
Everybody in the CDP space was confused. People building CDPs, people selling CDPs, people buying CDPs. Even people using CDPs and those implementing CDPs — everyone was confused and many were frustrated.And we just wanted to change that.
We also think that this battle between Composable and Packaged CDPs is fruitless — it’s not helping anybody or adding much value. And we wanted to get people together who want to discuss more pressing problems in the data space.
Needless to say, we’re far from achieving that goal but this is a good start and we’re optimistic.
So, without further ado, welcome to Round 1 of the CDP Rapid Fire! 🥁🥁
In this round, I’ll deliver one statement at a time and each guest will respond with “I agree” or “I disagree”, along with some quick thoughts to support their stance. 
What’s really valuable here is that together, these five individuals represent all the stakeholders involved in buying, deploying, and deriving value from a CDP. 
Let’s get into it.