Power BI gives you the ability to use a wide variety of data sources in your data visualization project. This walkthrough shows you how to access files in a Azure Data Lake and import them into a Power BI data models.
Power BI lacks the ability to add KPI calculations when creating a data model in Power BI Desktop. I will show you how to get the same functionality by using the recently released feature “Conditional Formatting by a Different Field”. This will allow you to take a calculated score and have an Icon displayed for each row in your table. A working Live Interactive Power BI Sample is attached at the bottom of this post.
This article reviews the process of using Azure Data Factory V2 sliding windows triggers to archive fact data from SQL Azure DB. This process will automatically export records to Azure Data Lake into CSV files over a recurring period, providing a historical archive which will be available to various routines such as Azure Machine Learning, U-SQL Data Lake Analytics or other big data style workloads.
One of the challenges for users with Power BI is being able to use a data source that you can update and flow those changes to your Power BI dashboards and reports. Using an Excel file in OneDrive for Business allows you to have multiple users update data, connect to a data source and schedule an automated refresh without having a lot of infrastructure. The following walkthrough will show you how you can leverage this feature for your own solution.
Minimize the impact on SQL Automation workflows when migrating to SQL Azure by automating stored procedures using Runbooks and E-mail. This step by step tutorial and walkthrough will review a solution to provide scheduling via Azure Runbooks with integrated O365 email alerts.