Category: notes-from-industry
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Forget About Cloud Computing. On-Premises Is All the Rage Again
Forget About Cloud Computing. On-Premises Is All the Rage Again Ten years ago, everybody was fascinated by the cloud. It was the new thing, and companies that adopted it rapidly saw tremendous growth. Salesforce, for example, positioned itself as a pioneer of this technology and saw great wins. The tides are turning though. As much…
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Experiments Illustrated: Can $1 Change Behavior More Than $100?
Experiments Illustrated: Can $1 Change Behavior More Than $100? I currently lead a small data team at a small tech company. With everything small, we have a lot of autonomy over what, when, and how we run experiments. In this series, I’m opening the vault from our years of experimenting, each story highlighting a key…
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Platform-Mesh, Hub and Spoke, and Centralised | 3 Types of data team
Platform-Mesh, Hub and Spoke, and Centralised | 3 Types of data team Introduction In the “ever rapidly changing landscape of Data and AI” (!), understanding data and AI architecture has never been more critical. However something many leaders overlook is the importance of data team structure. While many of you reading this probably identify as the data…
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Data vs. Business Strategy
Data vs. Business Strategy There seems to be a consensus that leveraging data, analytics, and AI to create a data-driven organization requires a clear strategic approach. However, there is less clarity and agreement on exactly what this strategic approach should look like in practice. This article provides a short overview of what strategy work I…
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DeepSeek V3: A New Contender in AI-Powered Data Science
DeepSeek V3: A New Contender in AI-Powered Data Science How DeepSeek’s budget-friendly AI model stacks up against ChatGPT, Claude, and Gemini in SQL, EDA, and machine learning Continue reading on Towards Data Science » Yu Dong Go to original source
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Modern Data And Application Engineering Breaks the Loss of Business Context
Modern Data And Application Engineering Breaks the Loss of Business Context Here’s how your data retains its business relevance as it travels through your enterprise Continue reading on Towards Data Science » Bernd Wessely Go to original source
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My Experience Switching From Power BI to Looker (as a Senior Data Analyst)
My Experience Switching From Power BI to Looker (as a Senior Data Analyst) What you need to know before you switch from Power BI to Looker. Continue reading on Towards Data Science » Tomas Jancovic (It’s AI Thomas) Go to original source
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2024 in Review: What I Got Right, Where I Was Wrong, and Bolder Predictions for 2025
2024 in Review: What I Got Right, Where I Was Wrong, and Bolder Predictions for 2025 What I got right (and wrong) about trends in 2024 and daring to make bolder predictions for the year ahead AI Buzzword and Trend Bingo (Image by the author) In 2023, building AI-powered applications felt full of promise, but the challenges…
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The Case Against Centralized Medallion Architecture
The Case Against Centralized Medallion Architecture Why tailored, decentralized data quality trumps the medallion architecture Continue reading on Towards Data Science » Bernd Wessely Go to original source
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How to Integrate AI and Data Science into Your Business Strategy
How to Integrate AI and Data Science into Your Business Strategy DATA SCIENCE CONSULTING Insider consulting guide to conducting a successful 2-day executive workshop Image by author using Canva “Our industry does not respect tradition — it only respects innovation.” — Satya Nadella, CEO Microsoft, Letter to employees in 2014 While not all industries are as competitive and cutthroat as the…
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What Teaching AI Taught me About Data Skills & People
What Teaching AI Taught me About Data Skills & People Three key lessons from my journey as a corporate AI educator Photo by Mikhail Nilov. As an AI Educator, my job was to equip corporate teams with the data & AI skills they needed to thrive. But looking back, I realized that I learned far more from…
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The Lead, Shadow, and Sparring Roles in New Data Settings
The Lead, Shadow, and Sparring Roles in New Data Settings From data engineer to domain expert—what it takes to build a new data platform Continue reading on Towards Data Science » Marina Tosic Go to original source
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Why Internal Company Chatbots Fail and How to Use Generative AI in Enterprise with Impact
Why Internal Company Chatbots Fail and How to Use Generative AI in Enterprise with Impact Start with the problem and not with the solution Background licensed from elements.envato.com, edit by Marcel Müller 2024 The most common disillusion that many organizations have is the following: They get excited about generative AI with ChatGPT or Microsoft Co-Pilot, read some…