Guide to Data Science in Microsoft Fabric
Microsoft Fabric
Oct 15, 2023 4:33 AM

Guide to Data Science in Microsoft Fabric

by HubSite 365 about Reza Rad (RADACAD) [MVP]

Founder | CEO @ RADACAD | Coach | Power BI Consultant | Author | Speaker | Regional Director | MVP

Data AnalyticsMicrosoft FabricLearning Selection

Explore the intricacies of Data Science workloads in Microsoft Fabric with our comprehensive guide on its usage and functionality.

In an informative content piece by "Reza Rad (RADACAD) [MVP]", he explores the subject of Data Science in Microsoft Fabric. The SaaS platform offers a multitude of workloads, comprising the Data Science. Rad elucidates the Data Science workload, its constituents, and its interoperability with other workloads within SaaS.

Microsoft's platform for analytics, Microsoft Fabric, includes several products and services which, combined, present an easy-to-use platform for data analytics. The main components, or workloads, are explained in detail by Rad.

Rad takes us through how Data Science works. Beginning with the definition of Data Science as a process which uncovers knowledge and patterns using different methods and algorithms, he introduces us to the steps involved in this process. These include the problem definition, data discovery and exploration, modelling and experimenting, operationalizing, and insight.

Microsoft Fabric's Role in Data Science

An integral part of Microsoft Fabric's functionality is its Data Science capabilities. This involves a suite of tools, libraries, and features that facilitate Data Science. Notably, the platform features various tools for data scientists to use such as Notebook, Data Wrangler, Power BI, and Visual Studio Code.

The Fabric includes multiple languages like PySpark, Scala, SparkR, and Spark SQL for data scientists to write code to enable the data science process. Further, several objects within Fabric are explicitly designed for data scientists to work with, including Lakehouse, Model, Experiment, and a Semantic Link.

Noting that the Data Science process is cyclical, Rad explains that insights derived from the process can lead to new questions and challenges which trigger the process anew. This iterative process holds true irrespective of the technology involved – any application or service that claims to facilitate Data Science should provide the tools, services, and means to accomplish the process above.

Trainer, Consultant, Mentor

Lastly, Rad provides a summary of how Data Science operates within the Microsoft Fabric framework. He emphasizes the importance of objects, services, tools, and languages in performing diverse tasks such as data discovery, exploration, modelling, training, testing models, operationalizing them, and ultimately, gaining valuable insights.

Reza Rad is a seasoned professional in the field of data analysis with extensive expertise in diverse Microsoft technologies. He has earned a reputation as an author, trainer, consultant, and mentor. Rad is very active in sharing his knowledge and insights, contributing to blogs, co-organizing summits, and providing mentorship for data enthusiasts.

In conclusion, the YouTube video and article explain the relevance and operation of Data Science within Microsoft's SaaS platform, Microsoft Fabric. The elucidation of the process and its associated steps provides a comprehensive understanding of Data Science and its integral role in data analytics.


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Microsoft Fabric - Comprehensive Guide to Data Science in Microsoft Fabric

Learn about Data Science in Microsoft Fabric


The field of Data Science plays an integral part in Microsoft's Fabric. This SaaS platform provides versatility in its workloads, and its clustered system allows it to function efficiently with other tasks. Ideal for data analytics, Fabric has assimilated a selection of products and services to provide an end-to-end, user-friendly platform.

Data Science: An Overview

Encompassing a broad spectrum of capabilities, Data Science involves using scientific computing and algorithms to extract pertinent knowledge and patterns from data. Behind the process is the Data Scientist, whose role is pivotal in utilizing quandaries and discoveries to generate solutions. This multi-tiered approach comprises various stages, from problem definition, data discovery, and exploration to experimenting and modelling, operationalization, and insights

Microsoft's SaaS Platform

Dedicated to providing a comprehensive analytics service, Fabric offers various tools, objects, and libraries. Created for data scientists, these resources aid in tasks like data exploration and discovery, building models, and operationalizing with Python libraries. Notable among these resources are Notebooks, primarily used for data science tasks in the Fabric environment.

Additional tools include Data Wrangler, a GUI editor for data preparation and exploration that can be launched from a Notebook, Power BI, which allows data scientists to connect to the data output they generate, and Visual Studio Code, a tool for developers to use Python codes during the data science process.

Fabric Objects

Fabric features numerous objects that data scientists regularly interact with, such as Lakehouse, Model, Experiment, and Semantic Link. Lakehouse is a structured and non-structured data storage area accessible using Notebook, while Model is an object trained to recognize patterns in the data. The Experiment is the environment encompassing the model, while the Semantic Link connects two crucial items, streamlining the data science process.


This SaaS platform offers an extensive array of services, tools, languages, and libraries, catering to data discovery, exploration, modeling, and training. These various components allow data scientists to execute their data science process as part of the larger data analytics project in the SaaS platform.

About the Author

Reza Rad, a Microsoft Regional Director, Author, Trainer, Speaker, and Consultant, has dedicated over two decades to data analysis, BI, databases, programming, and development on Microsoft technologies. He is a Microsoft Data Platform MVP for his commitment to Microsoft BI and has co-authored 14 books on Microsoft Business Intelligence.


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Data science in Microsoft Fabric
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Data Science, Microsoft Fabric, Data Analytics, Microsoft Data Science, Big Data, Azure Fabric, Machine Learning, Data Science Tools, AI in Microsoft, Cloud Computing Data Science.