Power BI Desktop is een prachtige tool om snel data-analyses te kunnen uitvoeren. Je connecteert op een databron, importeert en combineert wat datasets, definieert daarbovenop je favoriete calculaties en visualiseert de informatie. Je bent een echte data virtuoso.
The data landscape has changed dramatically over recent years, the world of data is evolving. In the past, we mainly heard that we needed to do as much as possible “cloud-only”—but this trend has become more nuanced now.
Azure Data Factory (ADF) is a cloud-based Extract-Transform-Load (ETL) and data integration service. It allows you to create data-driven workflows for orchestrating data movement and transforming data at scale.
Managers, analysts, engineers, and information workers who use it know that SQL Server Analysis Services Tabular (SSAS Tabular) is a valuable ICT asset. On the other hand, Power BI (PBI) is a great tool too that has a bit more functionality under its belt. Yet, there are cases where SSAS Tabular might prove useful which we’ll detail in this blog.
APIs are one of the things we often come across when working with data. In this blogpost we’ll have a look at some ways of extracting data out of them with Python in an efficient way.
When trying to do a standard install of SQL Server, you may have noticed that the 2017 or newer versions of SQL Server Reporting Services (SSRS) aren’t installed as well. That’s because SSRS now has its own separate installer. In this blog, we’ll show some of the changes compared to older versions of the software and detail how to install and update the 2019 version.
Weirdly formatted files, we’ve all had to import them into our reports at some point. Despite knowing what data we want to extract from the file, until now there was no easy way of showing that to the Power Query Editor.
Since its announcement as a first-party service on Microsoft Azure at the end of 2017, Databricks has seen a remarkable growth in usage. However, the service and its success were around long before Microsoft came into play. Going by the fact that you are reading this blog at this very moment, I’ll assume that you have used Databricks before, or at least have heard that Databricks is in the data business. And cousin, business is a-boomin’! One aspect that may have left users of the service frazzled, is the steady stream of updates it receives.
Splitting datasets and reports into separate PBIX files is a very common way of managing Power BI reports. This approach keeps data and calculations in a more central repository which acts as a “Single Source of Truth”.
The first thing that comes to mind when you think of Infrastructure-as-Code (IaC) in Azure is Azure Resource Manager (ARM) templates. After all, for every service – regardless of how you deploy it – an ARM template is created in the background. However, when you think of ARM, you probably also think of JSON files that are difficult to maintain and read. At least that’s what I think. Microsoft had the same thought as I did. So they launched Project Bicep, a domain specific language (DLS) or mini language. This means that Bicep is designed specifically for declarative development of Azure resources.