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Day: December 28, 2015

Introducing Microsoft SQL Server 2016 Preview

Published 2015-12-28 by Kevin Feasel

Denny Cherry alerts us to a free preview of a new Microsoft Press book:

The best thing about this book, is that it is free, there isn’t even a soul sucking registration to go through.  Just click and download.  It’s available is a standard 8.5×11″ PDF (standard US Pages) as well as a smaller PDF for mobile.  If you are looking for EPUB and MOBI files you’ll need to wait a few more weeks as they are supposed to be available starting in January (don’t hold me to that, I’m just going off the MSDN post.

Denny has a chapter on SQL Server security improvements that looks particularly interesting to me.

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Performance Monitoring For SSAS

Published 2015-12-28 by Kevin Feasel

Bill Anton has more information on performance monitoring for Analysis Services:

For query workloads, we can see important information about every single query that hits the system including details such as the total duration of the query, query text (MDX/DAX), start and end times, as well as the associated user account. We can also determine details as to how the query was executed such as the number of partitions scanned, aggregation hits/misses, cache hits/misses, other queries running at the same time, etc…all of which have an effect on the performance of any one particular query. A secondary benefit is that we’ll be able to identify the usage pattern(s) of folks using the cube. For example, is usage low/moderate throughout the week with a heavy spike on Friday mornings?

Bonus note:  it looks like there will be an xEvents for Analysis Services GUI in SQL Server 2016.

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Auto-Deploying Documentation

Published 2015-12-28 by Kevin Feasel

Steph Locke has more on documentation auto-deployment (and the original Curated SQL entry):

So I went through and converted everything in my Rtraining to this and realised it messed up my slide decks – it’s been so long since I had built a pure knitr solution that I forgot that rmarkdown::render != knitr::knit. For my slidedecks, if I wanted the ioslides_presentation format, I needed to use rmarkdown::render. The problem with that has been the relative references to the CSS and the logo.

To solve this I read about the custom render formats capability and created afunction that produces an ioslides_presentation but with my CSS preloaded by default. This now means that I can produce slides with better file referencing.

Steph has put up all of her R-related presentations and documentation as well, so check that out.

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DocumentDB

Published 2015-12-28 by Kevin Feasel

Robert Sheldon walks us through DocumentDB:

DocumentDB organizes documents into collections, with each database capable of hosting one or more collection. Because DocumentDB is a cloud service, it offers quick and easy implementations, while delivering the flexibility and scalability necessary to meet the demands of todays web and mobile applications.

DocumentDB integrates JSON and JavaScript right into the database engine. JSON, short for JavaScript Object Notation, is a widely implemented lightweight format for exchanging data between different source types, similar to how XML can be used to exchange data. JSON is based on a subset of the JavaScript programming language and is easy for computers to parse and generate, as well as being human readable.

Read the whole thing if you’re interested in Microsoft’s competitor to MongoDB.

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Monitoring For Suspect Pages

Published 2015-12-28 by Kevin Feasel

John Martin shows us about dbo.suspect_pages:

dbo.suspect_pages is a table that resides in the MSDB database and is where SQL Server logs information about corrupt database pages (limited to 1,000 rows) that it encounters, not just when DBCC CHECKB is run but during normal querying of the database. So if you have a DML operation that accesses a corrupt page, it will be logged here, this means that you have a chance of identifying a corruption in your database outside of the normal DBCC CHECKDB routine.

This is a nice tool we can use to check for corruption.

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Fraud Detection With R And Azure

Published 2015-12-28 by Kevin Feasel

David Smith shows us an online fraud detection template:

Detecting fraudulent transactions is a key applucation of statistical modeling, especially in an age of online transactions. R of course has many functions and packages suited to this purpose, including binary classification techniques such as logistic regression.

If you’d like to implement a fraud-detection application, the Cortana Analytics gallery features an Online Fraud Detection Template. This is a step-by step guide to building a web-service which will score transactions by likelihood of fraud, created in five steps

Read through for the five follow-up articles.  This is a fantastic series and I plan to walk through it step by step myself.

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