
This chapter is about Data used in today's world
This chapter is on Tools and Services
This chapter is about Microsoft Power BI
This chapter goes deep into a Lab on installing Power BI Desktop
This chapter gives a tour of Power BI Desktop
This chapter is about our Data Sets
This chapter is about setting up an Azure Free tier account
This chapter is on creating the Azure free account
This chapter gives an introduction onto the Azure SQL database service
This chapter shows how to create an Azure SQL database server
This chapter shows how to setup the Azure SQL Database
This chapter shows how to get data in Power BI Desktop.
This chapter shows how to remove columns in Power BI Desktop.
This chapter shows how to handle missing values in Power BI Desktop.
This chapter shows how to add new columns in Power BI Desktop.
This chapter is about Online Analytical Processing Systems
This chapter is about what goes into building a data warehouse
This chapter is about Power BI Desktop-Merge queries
This chapter shows how to build the Dimension Product table in Power BI Desktop.
This chapter shows how to build the Dimension Customer table in Power BI Desktop.
This chapter shows how to build the Fact Sales table in Power BI Desktop.
This chapter is about different views in Power BI desktop
This chapter is about what are we going to do next
This chapter shows how to build simple visualizations in Power BI Desktop.
This chapter is about hierarchies in Power BI Desktop.
This chapter shows how to perform a quick drill down in Power BI Desktop.
This chapter is about overview on DAX
This chapter shows how to create a measure using DAX expressions.
This chapter shows how to use aggregate functions using DAX expressions.
This chapter shows how to use filter functions using DAX expressions.
This chapter shows how to use information functions using DAX expressions.
This chapter shows how to use quick measures.
This chapter shows how to build a date dimension table in Power BI Desktop.
This chapter shows how to use calculation groups in Power BI Desktop.
This chapter shows how to use field parameters in Power BI Desktop.
This chapter is about Semantic Model-Storage design
This chapter shows how to use the direct query mode
This chapter is about Power BI Desktop-Column Profiling tools
This chapter talks about other performance considerations in Power BI Desktop.
This chapter shows how to use the Performance Analyzer in Power BI Desktop.
This chapter gives an introduction onto Microsoft Fabric.
This chapter is about Microsoft Fabric terms
This chapter provides the note on Microsoft fabric licensing
This chapter is all about On-boarding ourselves onto Microsoft Fabric
This chapter is about getting Microsoft Fabric trial capacity
This chapter shows how to publish a report onto Power BI.
This chapter gives a review on data warehousing fundamentals.
This chapter shows how to create a simple data warehouse in Microsoft Fabric.
This chapter talks about ingesting data in Microsoft Fabric.
This chapter shows how to create an Azure Storage account.
This chapter shows how to ingest data using the COPY command.
This chapter shows how to ingest data using the COPY command using a Shared Access Signature.
This chapter shows how to build a visual query in Microsoft Fabric.
This chapter shows how to clone tables in Microsoft Fabric.
This chapter shows to create tables using the CTAS command.
This chapter shows how to ingest data using the data pipeline.
This chapter shows how to ingest data using Data Flow Gen2.
This chapters how to build the Fact Sales table in Microsoft Fabric.
This chapters shows how to build the Dimension tables in Microsoft Fabric.
This chapters is about how to build the Dimension Date table in Microsoft Fabric.
This chapter shows the default semantic model in Microsoft Fabric.
This chapter shows column profiling in the data warehouse.
This chapter is about slowly changing dimensions in data warehouse
This chapter is about query folding in Power Query.
This chapter shows the basic SQL commands for a data warehouse.
This chapter shows the Group By SQL commands for a data warehouse.
This chapter shows how to find duplicate values.
This chapter shows the JOIN SQL commands for a data warehouse.
This chapter shows how to define a user-defined SQL function for a data warehouse.
This chapter tells us about Lakehouse
This chapter shows how to create a lakehouse in Microsoft Fabric.
This chapter shows how to Ingest data via files in Microsoft Fabric Lakehouse.
This chapter shows how to Ingest data via parquet files in Microsoft Fabric Lakehouse.
This chapter is about Microsoft Fabric Lakehouse - Delta Lake
This chapter shows how to Ingest data via the data pipeline in Microsoft Fabric Lakehouse.
This chapter shows how to Ingest data via the data flow gen2 in Microsoft Fabric Lakehouse.
This chapter shows how to use shortcuts to Azure Data Lake.
This chapter shows how to use shortcuts to AWS S3.
This description is About using Apache Spark on Microsoft Fabric
This chapter shows how to create a notebook in Microsoft Fabric Apache Spark.
This chapter shows how to load data into a data frame into Microsoft Fabric Apache Spark.
This chapter shows how to perform operations on a data frame in Microsoft Fabric Apache Spark.
This chapter shows how save the data frame in Microsoft Fabric Apache Spark.
This chapter is about further working with data in Microsoft Fabric Apache Spark.
This chapter is about Lab-Microsoft Fabric-Making sure the date is displayed properly
This chapter is on -Microsoft Fabric Lab-Deleting NULL values
This chapter is on Microsoft Fabric Lab-Checking for duplicate rows
This chapter is on Lab-Microsoft Fabric -Building our fact date frame
This chapter is on Lab-Microsoft Fabric-Building our dimension data frame
This chapter shows how you can run SQL commands in a notebook.
This chapter is about Microsoft Fabric -What is an event house
This chapter is on Lab-Microsoft Fabric -Eventhouse -How to create an event house
This chapter is on Lab-Microsoft Fabric -Event house ingest sample data
This chapter is on Lab-Microsoft Fabric -Event house Ingest data from Azure data lake
This chapter is about the Kusto Query language
This chapter is on Lab-working with KQL queries
This chapter is about Microsoft fabric eventstream
This chapter is on Lab-setting up Azure event hubs
This chapter on about Lab-Microsoft Fabric -Eventhouse -Setting up the event stream
This chapter is on Lab-Using Power BI to visualize the data
This chapter is about what we will be covering in this section
This chapter is on Power BI Assets
This chapter is about Power BI Project files
This chapter is on Lab-Microsoft Fabric -Creating a new workspace
This chapter is on Lab Microsoft Fabric -Assigning users to Microsoft Fabric
This chapter is about Lab-Microsoft Fabric-What can be the new user do
This chapter is on Lab-Microsoft Fabric -Data warehouse-Giving access to the SQL endpoint
This chapter is on Lab-Microsoft Fabric -Giving updated permissions to the user
This chapter is on Microsoft Fabric security -Data warehouse-Column level security
This chapter is on Microsoft fabric security -Data warehouse -row level security
This chapter is about Power BI desktop-Manage roles
This chapter is on Microsoft Fabric -Sensitivity Labels
This chapter is about Microsoft Fabric -Endorse items
This chapter is about Medallion Architecture
This chapter is on Microsoft Fabric -Deployment pipelines
This chapter is about Lab-Microsoft Fabric -Deployment pipelines -Workspace and item creation
This chapter is about Lab-Microsoft Fabric-Deployment pipelines-Deployment pipelines
This chapter is about Microsoft Fabric-Deployment pipelines-Additional points
This chapter is about Microsoft Fabric Deployment pipelines -Clean up
This chapter is on note-Microsoft fabric -workspace identity
This chapter is about Microsoft fabric -Version Control
This chapter is on Microsoft Fabric -Example on using version control
This chapter on about Microsoft Fabric-Performing an entire clean up
This chapter on about Project design and requirements
This chapter is on project data
This chapter is on Lab-Building our workspaces and user groups
This chapter is on Lab-lakehouse -Preparing the lakehouse
This chapter is on lab-Lakehouse-Ingesting Activity Log data-Building the pipeline
This chapter is about Lab-Lakehouse-Ingesting ActivityLog data-Scheduling the pipeline
This chapter is about Lab-Lakehouse-Loading data from delta tables
This chapter is about Lab-Lakehouse-Giving access to the scientists
This chapter has a note on Using the Power BI library in notebooks
This chapter is a Note on Lakehouse -Row and column level security
This chapter is a Note on Lakehouse and delta lake optimization
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"This course requires you to download Power BI Desktop on your local machine. If you are a Udemy Business user, please check with your employer before downloading software."
This intensive, comprehensive course is designed to prepare data professionals for the Microsoft DP-600 certification exam, focusing on data warehouse implementation and optimization using Microsoft Fabric. Participants will gain the knowledge and practical skills necessary to design, implement, and manage semantic models, data warehouses , lakehouses that leverage the full power of Microsoft's modern data analytics platform.
This course also contains a full-fledged project which covers the important concepts taught in this course.
The course also contains around 100 questions spread across Practice Tests and Quizzes
What are we going to learn
Basics around data and getting the required tools in place for the course.
Getting and transforming data within Power BI Desktop.
Building various aspects in Power BI Desktop such reports, visualizations, Measures etc.
How to use Power Query in Power BI Desktop to transform data. We will see an example on how build a semantic model around Fact and Dimension tables.
Getting started with Microsoft Fabric. How we get trial capacity to start working with the service.
How we can build data warehouses in Microsoft Fabric.
Using T-SQL, data pipelines and Data Flow Gen2 we can see how to ingest data into Microsoft Fabric.
How to run basic T-SQL commands against our data warehouse.
How to build Lakehouses on Microsoft Fabric.
How we can ingest data into Lakehouses using data pipelines and Data Flow Gen2.
How to use Apache Spark in Microsoft Fabric to work with data sets.