AWS is 5 times more expensive than Azure for Windows Server and SQL Server workloads. Comparing SQL Server running as a PaaS service shows an even bigger difference: You can pay even less when you use my scheduled autoscaling solution based on Azure Automation. It’s very easy to setup and among the most popular Azure contributions on Technet Scriptnet. I have created versions for Azure SQL Database and Azure Analysis Services – which also includes a pausing/unpausing option. It has been a while since I wrote the blog posts regarding these solutions and I have received a lot of feedback a ..read more

Many of my blog posts are focused on Azure cost reduction as this is essential to keep in mind when designing cloud solutions. Azure is a very cost-effective platform when it’s used in the right way, meaning you always have to consider the fact Azure is elastic and make sure your solutions scale up and down in an efficient way. Previously I showed how to autoscale Azure Analysis Services and Azure SQL Database. This time I show how to process Azure Analysis Services objects (models) in a cost-conscious way. In my last blog post I showed how to Process Azure Analysis Services objects from ..read more

In this blog post I will show how you can orchestrate processing of your Azure Analysis Services objects from Azure Data Factory v2. This makes it possible to process an Analysis Services model right after your Azure Data Factory ETL process finishes, a common scenario. I will guide you through creating a Logic App that communicates with the Azure Analysis Services REST API and show how you can trigger it’s execution using a webhook from Azure Data Factory v2. The whole process will be executed using an Azure Active Directory App registration that has been granted access to process Azure Analy ..read more

Modern data analytics platforms often follow a hub and spoke architecture in which a data hub is used as central data ingestion area that contains all data, usually in raw format. Data spokes deliver data to the majority of the end users in a data store that meets their specific requirements. The data hub can be build on Azure Data Lake Store (ADLS) and/or Azure SQL Data Warehouse. Data spokes can basically come in any form, dependent on the specific requirements. They are often build on Azure Blob Storage, Azure SQL Database (ASQLDB) and/or Azure Analysis Services (Azure AS). When ADLS i ..read more

The last day of PASS Summit 2017 was definitely not the least! Yet again we had some great engagement with one of the Microsoft product teams, this time the Analysis Services team which discussed the roadmap with us and a group of other MVPs and insiders. Today’s sessions we visited were about the Azure Service Bus, advanced SQL security (incl. the new SQL Vulnerability Assessment), and a demo heavy session by Christian Wade, one of the Analysis Services program managers. Get on the Azure Service Bus by Stuart Moore Sessions about services like the Azure Service Bus are not really common at a ..read more

Day two of the PASS Summit brought Dave and me a brilliant and powerful keynote about Azure Cosmos DB, high quality deep dive sessions about Azure SQL Data Warehouse and Azure Data Lake, and again, it provided us opportunities to connect to the Microsoft product teams. Day Two Keynote: Globally distributed databases made “simple” by Rimma Nehme Today’s keynote was all about Microsoft’s latest addition to the data platform: Azure Cosmos DB. This service was designed for the cloud with the requirements that it should offer turnkey global distribution, guaranteed low latency at the 99 percentile ..read more

Day one of the PASS Summit has ended and wow, what a great day! Not only because of the great sessions and awesome keynote, but also because we met many people from the Microsoft product teams and the community. PASS Summit is so much more than an event to learn! In this first blog post of a series of 3, Dave and I will highlight important keynote announcements, zoom into what the “Industrial Revolution 4.0.” brings us, describe how you can deliver enterprise BI on big data with Azure Analysis Services and tell you why you should attend the focus group sessions in which you can provide direct ..read more

I am attending PASS Summit 2017 in Seattle, and this year I am together with my Macaw colleague Dave Ruijter. We will get all latest product updates from the Microsoft Program Managers and will attend deep dive sessions about various Microsoft Data Platform related topics. Besides learning we will also be giving feedback to the Microsoft product teams! If you have anything we should definitely share with them, let us know by commenting on this blog post! After each day Dave and I will share the highlights here on my blog. So make sure to follow my blog via email and don’t miss a thing! Expect ..read more

One of the major benefits of Azure is scalability, the cloud is built to be elastic, to be as cost-effective as possible. Azure solutions can be scaled in ways that would never be possible with your own hardware. You are able to scale up and out when the demand arises, and more importantly you can scale down and in, or even pause, when you don’t need all the resources anymore, thereby saving a lot of money. Autoscaling based on a schedule allows you to scale your solution according to predictable resource demand. For example you could require the highest capacity on Monday during peak hours, w ..read more

Finally, at Ignite Azure Data Factory Version 2 is announced! A giant step forward if you ask me. In this blog post I will give an overview of the highlights of this exciting new preview version of Azure’s data movement and transformation PaaS service. ADF V2 pricing can be found here. First good thing to mention is the documentation that has been written by Microsoft, there is a lot and it is very detailed. You can find it here: Azure Data Factory V2 Preview Documentation. On the left side you will find links to the different articles and on the main page links to the excellent step-by-step t ..read more