Delve into the intriguing intersection of technology and hip-hop with our latest blog, where we dissect the high-profile rivalry between Kendrick Lamar and Drake to demonstrate GraphRAG's potential offer insights that go beyond the music industry.
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Data Science & Data Engineering blogs
Thanks for reading. Here you will find a huge range of information in text, audio and video on topics such as Data Science, Data Engineering, Machine Learning Engineering, DataOps and much more. The show notes for “Data Science in Production” are also collated here.
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The International Day Against Homophobia, Biphobia, and Transphobia (IDAHOBIT) is observed annually on 17th May. This year the theme is ‘Unity’ - read more about its history and why the day is important.
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With a world wide industry market cap of $7.1 trillion and substantial investments totalling $22.3 billion, let’s delve into the basics around GraphQL and why you should be including it in your infrastructure.
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We are thrilled to announce that we have partnered with dbt Labs, the company behind the premier analytics engineering product: dbt, which is fast becoming the new standard for data transformation workflows, that power and populate our curated layers.
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Unlock the future of AI with PromptFlow in Azure Machine Learning & AI studio. From automation with GitHub Actions to scalability with Azure API Management, learn how PromptFlow is changing the game for LLMOps.
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Navigating the rapidly evolving AI development landscape poses a distinct challenge, especially when choosing the appropriate tools for developing Large Language Model (LLM) applications. This blog explores Prompt Flow, Semantic Kernel, and LangChain, leading technologies each offering unique features to enhance AI-driven applications.
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Discover why your business needs to focus on fine-tuning datasets now. With AI technology evolving, having the right data can set you apart.
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Data Products are all the rage, but are they really a good idea? This blog explores further…
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Data and AI Maturity is a journey that every organisation is on, whether they are aware or not. This blog looks at what the Data and AI Maturity curve is, how to know where you are, and how to improve.
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As a round-up for February from the DIBs team, we bid farewell to the Year of the Tiger, and welcome the promising Year of the Dragon! Here are 5 things we can learn from going into the Chinese culture and the Year of the Dragon.
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Databricks Unity Catalog (UC) has gained significant attention lately, with Databricks making huge investments and shifting to make it the default choice for all new Databricks accounts. But what does that mean and how will it affect you?
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Data Governance – you have heard the term a million times and not once has it driven excitement in to your heart. I’d like to spend the next few minutes changing that.
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At Advancing Analytics, we have a question we like to ask new hires: Are you a plate or a bowl? In a chat with colleagues someone made an offhand comment about Morpheus from the Matrix offering a plate or bowl instead of the red or blue pill from the movie. This comment made me want to try and generate this image using AI and was also an interesting example of prompt refinement.
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Generative AI is accelerating a global workforce disruption, the likes of which we have not seen since the Industrial Revolution. But where do you start? How do you ensure you are using AI in legal, responsible, ethical ways? How do you decide you are ready to start employing Generative AI?
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If you keep up with the latest developments in the data space, you will probably know that Microsoft Fabric has now reached general availability. One of the trickiest things we’ve had to come to terms with is how concurrency works and how to run multiple notebooks at once without errors.
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When it comes to selecting data curation options in Fabric there are an entire haberdashery of options. Let’s explore some of those options, looking at which path might best suit which types of Analytics Engineering personas.
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