So let’s get down to brass tacks and actually create an alert. To do this, we need some info first:
The Resource Group we will create the alert in.
An Azure location where the alert will live.
An Azure SQL Database server and database we are creating the alert for.
What metric we will monitor and what is the threshold we will be checking.
(optional) An email to send an alert to.
Mike follows this up with code and shows it’s not scary at all to create these alerts from within Powershell.
Before I started, I was already quite comfortable programming Python and did some R programming in the past. This turned out pretty handy, though not really needed to start off with – because starting with Azure ML, the data flow can be created much like BI specialists are used to in SSIS.
A good place to start for me was the Tutorial competition (Iris Petal Competition). It provides you with a pre-filled workspace with everything in place to train and test your first ML model:
I’d like to see Azure ML get more traction; I’m not optimistic that it will.
To collect the data on all the first generation pokemon, I employ Hadley Wickam’s rvest package. I find it very intuitive and can handle all of my needs in collecting and extracting the data from a pokemon wiki. I will grab all the Pokemon up until to Gen II, which constitutes 251 individuals. I did find the website structure a bit of a pain as each pokemon had very different looking web pages. But, with some manual hacking, I eventually got the data in a nice format.
This probably means a lot more to you if you grew up in front of a Game Boy, but there’s some good technique in here regardless.
This article focuses on migrating data to Azure SQL Data Warehouse with tips and techniques to help you achieve an efficient migration. Once you understand the steps involved in migration, you can practice them by following a running example of migrating a sample database to Azure SQL Data Warehouse.
Migrating your data to Azure SQL Data Warehouse involves a series of steps. These steps are executed in three logical stages: Preparation, Metadata migration and Data migration.
It’s a lengthy read, but well worth it.
JupyterLab uses a web-based UI that’s akin to the tab-and-panel interface used in IDEs like Visual Studio or Eclipse. Notebooks, command-line consoles, code editors, language references, and many more items can be arranged in various combinations, powered by the PhosphorJSframework.
“The entire JupyterLab [project] is built as a collection of plugins that talk to kernels for code execution and that can communicate with one another,” the developers wrote. “We hope the community will develop many more plugins for new use cases that go far beyond the basic system.”
It looks like they’re making major changes to keep up with Zeppelin on the back end. The biggest advantage Jupyter had for me over Zeppelin was its installation simplicity, so I hope they keep it just as easy as installing Anaconda and then loading JupyterLab.
At first, you have to read the file you want to copy into a SQL Server. You have to choose a database to perform that action. It can be Test database or you can create a new database to perform that action or it can be even TempDB. There is only two requirements for the database:
– It must not be a production Database;
– Database should have enough of space to accommodate the file you want to copy.
The idea is that if the database engine’s service account has rights to a file you want to access but don’t have permissions to access, you can bulk copy the contents as a binary blob and then grab the contents and write the results to your local system using bcp. Sure, it becomes your company’s most expensive file copy tool, but I love the mad ingeniousness behind it.
The Aster Plot allows a category that dives the chart and up to 2 measures.
The first measure controls the depth of each section
The second measure controls the width of each section
I have to admit that I’m not a fan of the Aster Plot. It has all the disadvantages of pie and torus charts (specifically, that humans have a hard time discerning differences in angles) while making it more complex and comparing across a second dimension as well.
It gives you a map on how to manage your security as you move into the cloud. Note: one of the main points is that your on premise security is equally as important and has to be managed with and as a part of your cloud security.
Now if you are like me and want more than just dry reading they also provide a link to a Microsoft Virtual Academy training course called Security in a Cloud-Enabled World that follows this roadmap and provides more detail and guidance.
Read the whole thing.
Before I’m going into detail, I want to give full kudos to Ola Hallengren (Website | @olahallengren). He has spend a lot of his time to build a SQL Server Maintenance Solution that is completely free for everyone to use. And he did such an excellent job a lot companies (also huge companies) use his solution to run maintenance tasks on their databases.
None of the scripts below are written by me, but only small changes are made in order to make things more clear when the solution is deployed to an environment. The original scripts can be downloaded via the download page on Ola’s website.
Most of the to-dos are the same between on-premises and Azure SQL DB, but some of the implementation steps are a bit different. This is worth checking out if you have any Azure SQL Database instances.
I’ve reproduced Sharon’s code and charts below. I did make a couple of tweaks to the code, though. I added a call to checkpoint(“2016-08-22”) which, if you’ve saved the code to a file, will install all the necessary packages for you. (I also verified that the code runs with package versions as of today’s date, and if you’re trying out this code at a later time it will continue to do so, thanks to checkpoint.) I also modified the data download code to make it work more easily on Windows. Here are the charts and code
It’s really easy to get basic visualizations within R, and these are better than basic visualizations.