Skip to main content

Do you know about GDPR and are you ready?

[PLACEHOLDER]
Image


GDPR is the EU General Data Protection Regulation approved by the EU parliament on April 2016 with the enforcement date of 25 May 2018, replacing the existing Data Protection Directive. 

But why should you care? And why should every country including those outside the EU care? 
This regulation is being put in place to protect EU citizens, which means that all companies or organizations holding or managing data from EU citizens have to be compliant with this regulation. 

The regulation touches a group of strategies and tactics used by everyone in the digital space, guaranteeing that end users are aware of how their data is being used and making sure explicit consent is provided. One of many key items is also the "right-to-be-forgotten". Here are some of the tactics that are under the microscope by the GDPR regulation:
  • Analytics
  • profiling
  • marketing communications (e.g. emails)
  • privacy, terms & conditions statements
  • data retention policies
  • even tactics like cookies and pixel tracking initiatives needs to be reviewed 
The fine for companies that are not compliant are up to 2% of the worldwide annual revenue of the prior financial year.

If you want to know more about it then we recommend going to:


Trending posts

AI architecture and patterns - part I

AI systems can be complex. Architecture patterns provide reusable blueprints to design them effectively, ensuring your AI solution is scalable, modular, and efficient. Here’s a breakdown of the most common AI architecture patterns.   Photo by Jan van der Wolf via Pexels Core AI system patterns. Pipeline pattern. This is great when you need clarity, control, and determinism in your AI system. It breaks a complex workflow into a clean sequence of stages: data ingestion → preprocessing → model training → inference Each step has a single, well‑defined responsibility. This structure makes debugging easier, improves replicability, and allows teams to optimise or swap out individual components without disrupting the entire system. In practice, it’s the backbone of many production ML and LLM workflows where consistency and traceability matter just as much as model performance.    Microservices pattern. Microservices takes AI architecture and breaks it into small, autonomous serv...
Read more

Rethinking Canadian Economic Sovereignty Amid Foreign Acquisitions

About a year ago, I attended the Elevate Festival in Toronto, which I recommend if you haven't had the chance to experience it. The event was very inspiring because of its focus on business, technology, and entrepreneurship. It was interesting to see people at various stages of their careers; some executives, others developing their startups, a few in between, and some simply there to gain insights and knowledge. There was a unique atmosphere, influenced by the current political situation between Canada and the US. Many discussions centred around data sovereignty, cloud infrastructure independence, and ensuring that Canadians' data remained safe and secure within the country's borders or trusted allies. Building trust requires considerable effort, yet it can be shattered very quickly… and once broken, repairing it becomes extremely difficult, if not impossible. Considering the current geopolitical landscape, it is unclear where we go from here... but it seems the rules hav...
Read more

Reimagining Digital Experience Management: How Agentic AI is Transforming Adobe Experience Manager

 Adobe Experience Manager (AEM) has introduced powerful new Agentic AI capabilities designed to continuously improve and adapt digital experiences at the speed of AI. By integrating advanced AI orchestrators through Agent-to-Agent (A2A) and Model Control Protocol (MCP) tools, AEM enables brands to automate complex workflows and enforce compliance seamlessly across enterprise ecosystems. Through a suite of specialized agents, teams can transition from manual, weeks-long processes into fast, AI-assisted workflows powered by simple natural language prompts. Photo by Tunahan KALAYCI via Pexels   Here is a breakdown of the key agents driving AEM’s new Agentic capabilities, their value propositions, their guardrails, and their current availability status. 1. Brand Experience Agent. Overview. The Brand Experience Agent accelerates digital modernization through specialized sub-agents—the Experience Modernization Agent, Experience Production Agent, and Experience Development Agent. Tog...
Read more

AI architecture and patterns - part II

In this article, we continue from Part 1, where we began presenting a range of AI architecture patterns that function as reusable blueprints for effectively designing AI solutions. This can support you on your journey in identifying the appropriate one (or ones) for the problem you are trying to solve. Photo by Jan van der Wolf from Pexels   Data centric patterns. Feature store pattern. This one has become a foundational element of mature ML platforms because it centralises the entire feature engineering lifecycle, ensuring that models train and serve on consistent, high‑quality data. Instead of letting teams repeatedly rebuild the same user metrics, behavioural aggregates, or time slot signals, a feature store provides a single source of truth where these features are computed once, documented, versioned, and reused across many models. This shared infrastructure: Eliminates training‑serving skew, which is one of the most common causes of silent model degradation. Enables organisat...
Read more

This blog uses cookies to improve your browsing experience. Simple analytics might be in place for pageviews purposes. They are harmless and never personally identify you.

Agreed