Kamal will share his experiences in entering new competitive markets & global best practices.

Fireside Simolation is a safe space for all participants to have a friendly discussion about all the things that bother, inspire, or preoccupy you in the digital analytics space.

Even though the resources are always limited it might be tempting to focus on collecting data the right way instead of collecting the right data.

This session will cover a modern data stack approach that drives analytics, feature engineering, and dashboards across the enterprise. It will showcase real time streaming capabilities, data lakes, decentralized vs. centralized warehousing, and feature store architecture. The solution provides sub second latency to data and scales to billions of transactions a day.

As a digital analyst the core of our job is to translate what the data is saying about the business so we can use that knowledge to improve it. Pretty simple, awesomely valuable and radically focused on facts.

So you've got analytics working but you need to grow your data collection to other websites, other markets, other apps? In this presentation, Julien and the Media.Monks data team share best practices and solutions that were used (and often custom built!) to achieve at-scale deployment of data collection across thousands of websites and apps.

After a decade of digital marketing, I've decided to transition into digital analytics in 2022 because I wanted to work even more with data to solve complex problems.

In this talk, we will delve into the features and capabilities of Google Analytics 4's measurement protocol. We will discuss its strengths and limitations, and explore how the client-side protocol can be used to bypass some of these limitations. Finally, we will present a real-world use case for the client-side protocol and demonstrate its potential benefits.

Web bots have been around for decades, but the volume of bot traffic has increased massively. So has the complexity of bot filtering. While the bots have become way better, bot filtering solutions haven’t – especially in common analytics tools. Even IT security teams are usually not handling the problem properly.

I'll discuss why, and how data makes me tick. I've been doing work with data for decades but it's more exciting now than ever. Why do I get nerdy excitement from data? Because of my personal data, because data fuels change, because data is used for good. I'm immersed in data that has purpose on a daily basis.

Over the past 2 decades, Jim has watched the industry take on many different forms, maturing from the lawless wild west of the digital industry to an increasingly-regulated establishment. This departure from the lawless world of analytics has left some of us looking for new, exciting frontiers. Jim will share his perspective on where we might find it.

A delightful way to gather and continue socializing: competitive team challenges and prizes that will give you a short break from analytical topics.

Demonstrate any Digital Analytics solutions or method of your own that is way beyond the defaults. Who decides who's gonna win? The audience. Send your nomination to [email protected]!

Shifts in technology and the rise of privacy laws are reshaping the industry, bringing the uncertainty to analytics professionals' work. And the most significant changes are still ahead of us.

Kris Ewald will give you an overview of Innovations in Data Science you should be aware of. If data driven insights are key to competitiveness, you need to keep innovating on how you Collect, Manage and Challenge data. With plenty of other talks about very specific tools and data analytics frameworks, this talk will instead aim to inspire you to apply new approaches to your data science - it'll give you a list of topics you should care about and pay attention to. Expect to hear about Zero-knowledge proofs, Homomorphic encryption, DAGs, and Blockchain and data as value objects.

Every team wants to improve, optimize, reach goals, to grow. Every team also has a massive pile of ideas on what to work on next. Prioritization is the key to success, ensuring they work on stuff with a high chance of making an impact. As an analyst, you should deliver the insights that feed the prioritization. Did you know that analytics is just a tiny part of those insights? In this talk, I'll show you the best sources to analyze to develop insights that optimize your prioritization.

Marketing teams need analytics. Product teams need analytics. There are marketing analytics vendors like Google Analytics and Adobe Analytics. There are product analytics vendors like Amplitude and Mixpanel. But what are the real differences between marketing and product analytics? Do organizations need different teams for each? Should organizations use both types of tools? Will one replace the other or will these disciplines converge?

With the current economic challenges, layoffs and budget cuts proofing the value of analytics and making the case of how it could be used to bring value to organizations is of an increasing importance. In this talk Ibrahim will cover this topic and will suggest a framework and ways of working to proof and communicate that value.

Join us for a deep dive into the analytics and marketing tech stack of the future! Drawing inspiration from the lovable robot Johnny 5 in the classic film Short Circuit, we'll explore the critical role that data (aka input) plays in driving marketing and analytics success. Discover how innovative tools like customer data platforms and reverse ETL platforms are revolutionizing the way we build and improve our analytics infrastructure and tech stacks. Learn how to stay ahead of the curve in a much more data-driven world and discover how to make use of the power of more input for your own organization!

In the age of GDPR, CCPA, and HIPAA along with the widespread proliferation of ad blockers and Apple’s ITP, it’s never been harder to measure the effectiveness of your digital marketing efforts while protecting your customers' data.

In August 2020 Matteo and Roberto met for the first time a fascinating creature with a cumbersome name: App + Web. It was not love at first sight. After all, they were already engaged in a longtime romance with Universal Analytics.

When most Marketers think of Analytics, they think of clickstream data… the clicks, visits, views and hopefully the conversions. But Analytics is so much more than that. Analytics is applying your brain for discovery, interpretation, and communication of meaningful patterns in data.

In the past, digital analytics experienced a boom with the emergence of tag management systems. These tools allowed marketers to quickly and easily implement tracking and marketing tags without relying on web developers, improving speed and agility for those eager to take advantage of new opportunities. And we all know how eager marketers are.

As analysts we are well aware of the legal and moral boundaries that come with handling delicate data. But imagine for a moment that behind a desk at your competitor's office was an analyst unbothered by those boundaries. His only goal is to get a competitive advantage by exploiting the weak points in your analytics pipeline. He wants you to waste as much time, money and credibility while you deal with polluted source data, spam, data breaches and legal DDoS attacks.

Digital analytics data is almost exclusively data that exists over time. That is such an obvious fact that it's easy to blow right past some important considerations and techniques that are unique or (or, at least, present in) time-series data. Stationarity (and, often, the lack thereof) and seasonality (annual...and intra-week!) alone are important and intriguing considerations when it comes to time-series data. In this session, Tim will do a high-level review of some key concepts and some of his favorite techniques for responsibly working with time-series data.