Learners will build on existing analytics experience and learn how to use Microsoft Fabric components, including lakehouses, data warehouses, notebooks, dataflows, data pipelines, and semantic models to create and deploy analytics resources.
Data collection is critical to analysis. Microsoft Fabric's Data Factory provides Dataflows (Gen2) to create and visualize multi-level data collection and transformation using Power Query Online.
You will learn how to use Apache Spark and Python for data collection in a Microsoft Fabric Lakehouse. Fabric notebooks offer a scalable and systematic solution.
Microsoft Fabric includes Data Factory capabilities, including the ability to create pipelines that orchestrate data collection and transformation tasks.
Lakehouses combine the flexibility of data lake storage with data warehouse analytics. Microsoft Fabric is a lakehouse solution for comprehensive analyses on a single SaaS platform.
Explore the potential of Medallion architecture design in Microsoft Fabric. Organize and transform your data in the Bronze, Silver and Gold tiers of a Lakehouse to enable optimized analytics.
Apache Spark is a core technology for comprehensive data analysis. Microsoft Fabric supports Spark clusters so that you can analyze and process even large amounts of data in a lakehouse.
The tables in a Microsoft Fabric Lakehouse are based on the Delta Lake storage format, which is commonly used in Apache Spark. You can use the advanced functions of delta tables to create complex analysis solutions.
Data warehouses are analytics stores based on a relational schema to support SQL queries. With Microsoft Fabric, you can create a relational data warehouse in your workspace and easily integrate it with other elements of your end-to-end analytics solution.
The Data Warehouse in Microsoft Fabric is a comprehensive data and analytics platform that provides advanced query processing and full transactional T-SQL capabilities for easy data management and analysis.
The Data Warehouse in Microsoft Fabric is a comprehensive data and analytics platform that provides advanced query processing and full transactional T-SQL capabilities for easy data management and analysis.
A data warehouse is an important component of an enterprise analytics solution. It is important to learn how to monitor a data warehouse so that you can better understand the activity occurring within it.
Scalable data models enable enterprise-wide analytics in Power BI. You will implement best practices for data modeling, use large storage formats for datasets, and practice creating a star schema to design scalable analytics solutions.
Power BI model relationships form the basis of a tabular model. Defining Power BI model relationships, setting up relationships, recognizing DAX relationship functions and describing the relationship evaluation.
Develop, manage and optimize Power BI data models and DAX query performance with tools.
Enforce model security in Power BI using row and object level security.
This course consists of training training and is led by a trainer who supervises the participants live. Theory and practice are taught with live demonstrations and practical exercises. The video conferencing software Zoom is used.
The primary audience for this course is data professionals who have experience with modeling, extracting and analyzing data. This course is designed for professionals who want to use Microsoft Fabric to build and deploy enterprise-scale data analytics solutions.
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