For those DBAs are using SQL for data discovery, the move to data science can involve a brand-new set of varied tools and technologies. This article is a walkthrough of setting up the tooling to do some data discovery using Python. By setting up your workflow using, GitHub, VSCode and Python you will have the basic architecture set up for Data Exploration.
This article will review a major trap you can find yourself in when using PowerShell in your Runbooks as Azure Automation does not keep your referenced modules up to date.
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.
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.
An often overlooked, yet powerful feature of Power BI allows you to publish a report to a website using an embed code. This puts the report and underlying data out for everyone who has access to that web page. The sample page below shows a sample book I published for a training session. The following how-to will walk you through will the steps leverage this feature on your site.
Connection Strings for named instances as sources for R in SQL Server. All about the double slashes!!