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Welcome to our in-depth tutorial on Microsoft Fabric, the all-encompassing SaaS platform designed to revolutionize your data management and analytics experience. In this video, we will walk you through the essentials of Microsoft Fabric, showcasing its integration with Power BI and how it enhances your data engineering, analysis, and science capabilities.
What is Microsoft Fabric? Microsoft Fabric is a cutting-edge SaaS platform that combines various Microsoft technologies to offer a unified solution for data engineering, analysis, and science. It seamlessly integrates Azure Data Engineering, Microsoft Machine Learning Studio, and Power BI to provide a holistic approach to handling and interpreting business data.
Key Learning Objectives:
Data Engineering: Learn how to extract, transform, and load business data efficiently. Understand the processes of data collection, cleaning, and transformation, and how to load data into a Data Warehouse (DWH).
Data Analysis: Discover how to analyze business data, design impactful reports and dashboards, and visualize key insights to drive informed decision-making.
Data Science: Explore the fundamentals of machine learning models, including how to prepare and use them for making accurate predictions, such as forecasting sales amounts for the upcoming months.
What You Will Learn Inside Microsoft Fabric:
Azure Data Engineering: Dive into the tools and technologies that support data engineering, including Data Lake, Synapse Data Warehouse, Data Factory, Databricks, and live streaming analytics.
Data Analysis with Power BI: Master the art of data visualization using Power BI, ensuring you can turn complex datasets into actionable insights.
Data Science with Microsoft Machine Learning Studio: Gain hands-on experience with machine learning models, from preparation to execution.
Job Opportunities: Microsoft Fabric opens up various career paths, including roles such as:
Data Engineer
Data Analyst
Data Scientist
Business Intelligence (BI) Developer
Technical Skills Covered:
DP-600: Storage solutions such as Lake House, Data Warehouse, and KQL Database.
Data Ingestion: Master tools like Data Factory, Data Flows, and data engineering using Spark Notebooks (SQL or Python).
Semantic Modeling: Utilize semantic modeling techniques to enhance data understanding and reporting.
Whether you're looking to dive into data engineering, enhance your data analysis skills with Power BI, or explore the world of data science, this video will provide you with a comprehensive understanding of Microsoft Fabric and its capabilities.
Join us to unlock the full potential of Microsoft Fabric and elevate your data expertise to new heights!
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18 сен 2024
