Panagiotis Tzamtzis - Digital analytics consultant & Web developer

Airbyte serverless to load data to your warehouse in 10 lines of Python source code

AirbyteServerless is a straightforward tool designed to manage Airbyte connectors. It offers the flexibility to run these connectors either locally or in serverless mode. If you’re dealing with data pipelines, ETL, data warehousing, or data engineering, AirbyteServerless is a must-have in your tech stack. It simplifies the process of moving data from various sources to your data warehouse. The repository is available on GitHub here. You can use it to load data to your datawarehouse from almost any data source out there. And you don’t need a DB, a UI or an Airbyte server. Plus, serverless compute deployment is supported meaning it can work on Github...

Tokenization by Andrej Karpathy

In a recent YouTube tutorial, Andrej Karpathy—the wizard behind Tesla’s Autopilot and OpenAI’s GPT—unveiled the secrets of tokenization. Buckle up, tech-savvy professionals, because this isn’t your run-of-the-mill theoretical lecture. It’s a hands-on journey into the heart of language models. So, what’s the deal with tokenization? Imagine it as the backstage choreographer for Large Language Models (LLMs). It translates between human-readable strings and the cryptic tokens that LLMs munch on. In this tutorial, we’re not just peeking behind the curtain; we’re building our own tokenizer from scratch. Here’s the lowdown: So grab your code editor, channel your inner Karpathy, and let’s build...

GA4 and ChatGPT tricks for power users

GA4 and ChatGPT tricks for power users

Are you tired of sifting through mountains of data, drowning in analytics, and feeling like you’re always one step behind your digital marketing goals? Welcome to the era of GA4 Mastery, where the power of Google Analytics 4 (GA4) meets the limitless potential of ChatGPT. In this blog, we’re about to unlock the secrets that will forever change how you navigate the complex world of web analytics. Whether you’re a seasoned data wizard or just dipping your toes into the data-driven universe, these top five tips are your golden ticket to turbocharging your workflow, driving better insights, and achieving digital...

150x Faster Pandas using NVidia

Believe it or not NVIDIA is making Pandas 150x faster without source code changes. What you need to do? Their RAPIDS library will automatically know if you’re running on GPU or CPU and speed up your processing. You can try it here: https://colab.research.google.com/drive/12tCzP94zFG2BRduACucn5Q_OcX1TUKY3 Github Repo (7K stars): https://github.com/rapidsai/cudf Sign up to receive updates about new posts!

Intro to Large Language Models from Andrej Karpathy

Andrew Karpathy (Former Sr Director of AI @Tesla & Research scientist @ OpenAI) recorded a great 1 hour introduction to the mechanics of Large Language Models. I really liked the easy-to-understand examples that even non-experienced listeners can relate to, the awesome summarization of the most important events/breakthroughs that lead the field to where we are today and the LLM OS analogy. Sign up to receive updates about new posts!

Act Fast: Revolutionizing Data-Driven Decisions

Act Fast: Revolutionizing Data-Driven Decisions

In the rapidly evolving business landscape, agility and responsiveness are key. This article delves into the importance of harnessing and acting on the vast data available to businesses. It highlights the need for companies to become proactive 'thermostats' rather than reactive 'thermometers' in their environment, emphasizing the role of strategic automation in achieving this goal. The article explores five critical barriers to data-driven maturity: scalability, efficiency, consistency, accuracy, and the tech stack. Each section provides insights into overcoming these challenges through smart automation and data handling strategies. For example, it discusses how scalability can be achieved by automating data processing, and how efficiency in data analysis leads to more strategic and creative business practices. The article also touches upon the future of business and technology, predicting that 90% of data will become actionable in real-time through machine learning, and AI will play a significant role in transitioning to a 4-day work week. This shift promises greater efficiency and a better balance between professional and personal lives. Finally, it introduces Baresquare as a comprehensive solution to these challenges. As an enterprise-level SaaS product, Baresquare streamlines data handling and decision-making processes, offering real-time actionable insights through its AI-powered analytics platform. It positions itself as a tool that not only meets current business needs but also paves the way to a smarter, AI-driven future in business operations.