Categoria: Blog
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Create and Ingest Data with a Microsoft Fabric Lakehouse
Traditionally, large-scale data analytics solutions revolved around data warehouses, where data is stored in relational tables and queried using SQL. The rise of “big data,” characterized by high volumes, variety, and velocity, coupled with affordable storage and cloud-scale computing, gave birth to an alternative: the data lake. Data lakes store data as files without imposing…
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Work with Microsoft Fabric Lakehouses – A Hands-On Guide
Now that you grasp the fundamental capabilities of Microsoft Fabric Lakehouses, let’s delve into the practical aspects of creating, managing, and utilizing them. Create and Explore a Lakehouse You create and configure a new Lakehouse within the Data Engineering workload. Each Lakehouse generates three key components in your Fabric-enabled workspace: You can work with the…
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Lakehouses in Microsoft Fabric – The Foundation of Unified Analytics
Lakehouses merge data lake storage flexibility with data warehouse analytics. Microsoft Fabric offers a lakehouse solution for comprehensive analytics on a single SaaS platform. The core of Microsoft Fabric’s power is the Lakehouse, built upon the scalable OneLake storage layer and leveraging Apache Spark and SQL compute engines for big data processing. A Lakehouse marries…
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Microsoft Fabric – Getting Started
Before you can explore the powerful capabilities of Microsoft Fabric, it must be enabled for your organization. If you’re not an administrator, you might need to coordinate with your IT department to get Fabric up and running. Prerequisites for Enabling Fabric To enable Fabric, you’ll need one of the following admin roles: Fabric can be…
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Microsoft Fabric – Unlocking Collaboration and Productivity
Microsoft Fabric redefines how data teams work together. Its unified management and governance features tear down data silos and streamline access to multiple systems, fostering collaboration and efficiency among data professionals. Bridging the Gap between Data Engineers and Data Analysts In traditional setups, the separation of roles between data engineers and data analysts often created…
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Microsoft Fabric – Simplify Scalable Analytics
Scalable analytics solutions can often become a complex web of fragmented services and escalating costs. Microsoft Fabric introduces a unified approach, allowing you to focus on insights rather than wrestling with disparate vendor tools. Data professionals are increasingly expected to be able to work with data at scale, and to be able to do so…
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Checklist for using AI responsibly
Antes de utilizar a IA, é vital que pense cuidadosamente sobre como o fazer de forma responsável. Isto garante que o utiliza de forma ética, minimizando os riscos e alcançando os melhores resultados. O uso responsável da IA implica ser transparente sobre a sua utilização, avaliar cuidadosamente os seus resultados e considerar o potencial de…
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Bias, drift, and knowledge cutoff
Uma compreensão completa dos conceitos de IA responsável – como o preconceito, o desvio e o corte de conhecimento – pode ajudá-lo a utilizar a IA de forma mais ética e com maior responsabilidade. Nesta leitura, aprenderá a utilizar as ferramentas de IA de forma responsável e a compreender as implicações de resultados injustos ou…
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Práticas recomendadas de Prompt engineering
Os grandes modelos de linguagem (LLMs) reagem ao que lhes pedimos – quanto melhor for a entrada, mais útil será o resultado. Utilize este guia para criar prompts eficazes que ajudem os LLM a ter o melhor desempenho, para que possa obter a resposta mais valiosa. Especifique a tarefaOs LLMs são treinados em grandes quantidades…
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Explore chain-of-thought prompting
Visão geralA solicitação de cadeia de pensamento é uma técnica que envolve a solicitação de um grande modelo de linguagem para explicar os seus processos de raciocínio. A solicitação de cadeia de pensamento é útil para resolver problemas que envolvem raciocínio passo a passo. Esta técnica melhora a qualidade das respostas de um LLM em…
