There is a first time for everything, and now it is my time to have one of these moments. I have been selected to deliver a Hands-on Lab at SQLSaturday #369 in Lisbon this may, I look very much forward to be part of this legendary event.
It was by pure accident I saw that the deadline for abstracts was only a few hours away, so I took a look at my abstracts and found the ones I really thought would be interesting – and then crossed fingers.
To my surprise I got an email this Friday, stating that my abstract had been selected to the event. I am very honoured to be part of this event, I think it is one of the most visited SQLSaturdays in Europe and many of my friends from the #SQLFamily have had their debut at this event.
I will be delivering a session that will enable you to automate deployment of Azure Bigdata solutions – instead of using the portal.
Here is the abstract, I hope to see a lot of you at the session
By now you’ve probably heard about Big Data 1.000 times or more so why a new session about big data you might ask. Show how to make creation and deletion of AZURE elements automatically as part of your ETL process or by Powershell, automate the trivial procedures and work on the interesting parts This session will show you how :
- Downloads and prepares several years of demo data and storing it in a dedicated
- Azure Blob Storage account.
- Create a storage account and container for the HDInsight Cluster.
- Create a SQL database server instance and a SQL database for the Hive Metastore.
- We will also setup the necessary firewall rules so that you can access the server directly
- The HDInsight cluster is provisioned and configured for access to the sample data.
- A partitioned Hive table is created over top of the sample data
- Exploration of the result
- And how to automate these task either in Powershell or SSIS.
And if you would like to get updated on either Execution Plans or Data mining, you should sign up for one of the two great pre-conference workshops!
Mastering Execution Plan Analysis by Paul White (@SQL_Kiwi)
Data Mining Algorithms in SQL Server, Excel, R and Azure ML by Dejan Sarka (@DejanSarka)