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Author: Kevin Feasel

Machine Learning Skepticism

Julia Evans gives reasons to tamp down expectations with machine learning:

When explaining what machine learning is, I’m giving the example of predicting the country someone lives in from their first name. So John might be American and Johannes might be German.

In this case, it’s really easy to imagine what data you might want to do a good job at this — just get the first names and current countries of every person in the world! Then count up which countries Julias live in (Canada? The US? Germany?), pick the most likely one, and you’re done!

This is a super simple modelling process, but I think it’s a good illustration — if you don’t include any data from China when training your computer to recognize names, it’s not going to get any Chinese names right!

Machine learning projects are like any other development projects, with more complex algorithms.  There’s no magic and there’s a lot of perspiration (hopefully figuratively rather than literally) involved in getting a program which behaves correctly.

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Template Replacement

Andy Mallon shows SSMS template replacements:

In the above example, there’s not much value-add by using the template replacement. It’s probably easier to just use @variables and highlight-replace.

The template replacement really shines when you have examples where you’d otherwise need to use dynamic SQL. If you have object names or database names that need replacement, this is a great answer. If you work in a multi-tenant hosting environment, and a client name is part of the DB name, this can make your life a lot easier.

Templates work great with auto-replace (a feature several third-party toolkits include).  My favorite auto-replace that I’ve created is “die” which asks for an schema and procedure name and generates the DROP PROCEDURE script.  Naturally, I also have diet (table), diev (view), and dief (function).

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BACPACs In Azure

Mike Fal uses Powershell to import and export Azure SQL Database data:

What makes this black voodoo magic work? Is this some proprietary technique Microsoft has snuck in on us? Surprisingly, this is a bit of technology that have existed for sometime now as part of SQL Server Data Tools called BACPACs. A BACPAC is essentially a logical backup of a database, storing the schema and data as SQL statements.

This differs from a typical SQL Server backup, which stores your database pages directly in a binary format. Because of this, native backups are smaller and can be made/restored faster. However, they are more rigid, as you can only restore a native backup in specific scenarios. A logical backup, since it is a series of SQL statements, can be more flexible.

Mike’s going to follow up with a way to take advantage of this to migrate normal SQL Server databases, so that should be interesting as well.

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Installing SQL Server R Services Packages

Julie Koesmarno shows how to install an R package on a SQL Server 2016 instance which has SQL Server R Services installed:

When you start playing with R in SQL Server, sooner or later you would need to install some packages, for example ggplot2. You may run into a problem that sounds like this “Error in library(“ggplot2”) : there is no package called ‘ggplot2’“.

The following script is used in the iris_demo.sql (SQLServer2016CTP3Samples\Advanced Analytics\iris_demo.sql), and would cause a missing library error if you don’t have the packages installed on SQL Server R Services yet.

Julie shows two methods, one a Good Idea and the other a Bad(?) Idea.

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MDM Is Hard

Knut Juergensen gives an overview of Master Data Management:

The sad reality in many companies is that there is no MDM, or that it exists but is implemented and managed poorly. Often, this is due to lack of managerial-level understanding of its real value and, subsequently, a lack of investment.

I’ll recount some of the problems that we encountered with our MDM system, at least partly due to this lack of understanding and investment from management. Although the example is specific to engineering manufacturing, I know that similar fundamental flaws affect other MDM systems in other environments.

The primary master data in this case comprises the parts and products used in our assembly lines, which are provided and created by our in-house and external design engineers. A core issue with our MDM system is the source of this master data.

Knut gives a good explanation of what MDM is, how it works, and then an example of how it doesn’t work.  Read the whole thing.

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Faster Extended Events Reader

The CSS SQL Server Engineers note that with SQL Server 2016, we’ll get faster Extended Events readers:

SQL Server 2016 improves the XEvent Linq reader scalability and performance.    The XEvent UI in SQL Server Management Studio uses the XEvent Linq reader to process the events for display.   Careful study of the XEvent Linq reader revealed opportunities for scalability and performance improvements.

I don’t know if this will push anyone in the direction of using Extended Events who isn’t already doing so, but I like the performance improvement here.

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POCs As A Problem

Bill Vorhies argues that data science proofs of concept fall short of the mark:

If you do a quick read through of some of the Gartner or O’Reilly studies you’ll quickly see that a lack of executive sponsorship is one of the major barriers to adoption.  So isn’t the POC a good way to get the attention of the C-level?  Yes and no.

If as we described above it leads to the adoption of a series of stand alone ‘technology projects’, then no.  If it was really necessary to start with little firecracker POCs to demonstrate the explosive strategic value of becoming data-driven, then maybe so.

Here’s a simple change of mindset (borrowed from John Weathington referenced above) that instead of focusing on Proof of Concept, we should instead create projects to demonstrate Proof of Value.  By focusing on value we change the orientation so that any projects are aligned with value to the company.  In other words, they are aligned with the company’s strategic objectives.

This is an interesting argument which goes against my inclinations.  Check it out.

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Downgrading Databases

Stephen West shows how to migrate a database to an earlier version of SQL Server:

The error occurs as SQL Server database files and backups are not backward compatible restricting restore of database created from higher SQL Server version to lower version. Below are some of the steps to migrate the SQL Server Database from higher version to lower version:

1. Use Generate Scripts wizard of SQL Server Management Studio in Higher version

In this step, we will first script the schema of the desired Database on SQL Server 2012 instance to migrate the database to SQL Server 2008 R2 using Generate Scripts wizard of the SQL Server Management Studio.

There’s no easy way to do this; database upgrades are generally a one-way action.

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Dave Mason Interviews Chrissy LeMaire

Dave Mason recently interviewed Chrissy LeMaire on topics Powershell:

[Dave]: It’s natural to have bias toward the tools and technology we know, which can lead to spirited debate. Most of the time, it’s friendly and thoughtful. I’ve been getting a sense of “us and them” regarding T-SQL vs PowerShell. Do you get that sense too?

[Chrissy]: Yes, which has been pretty surprising to me. As a PowerShell MVP, it sometimes feels like fellow DBAs may see me as an invader of SQL territory, when in fact, I’ve been a DBA for 17 of the 20 years that I’ve been in IT. I even updated my Twitter profile to make it clear that I’ve been a SQL Server DBA since 1999. I believe this issue will resolve itself as DBAs begin to see how PowerShell can make their jobs way easier. I’m also hoping that mySQL Server Migration script, which has no T-SQL (or even C#) equivalent, will be as persuasive as it is useful.

I remember reading an article in SQL Server Magazine back around 2002 that made the case for DBAs to learn T-SQL and other scripting languages. My first thought was “Wait, there are DBAs that don’t know T-SQL?” I always thought T-SQL was part of the job description, and it’s the same now with PowerShell. This belief was further enforced by the fact that when I was getting started with PowerShell and SQL, Simple Talk’s Phil Factor and Laerte Junior already had a ton of stuff out there and a few books about SQL Server and PowerShell had already been written. I thought I was late to the party.

This is a fun read; check it out.

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Predicting ER Deaths

Konur Unyelioglu uses a neural network to predict emergency department deaths:

In this article we used an artificial neural network (ANN) from Spark machine learning library as a classifier to predict emergency department deaths due to heart disease. We discussed a high-level process for feature selection, choosing number of hidden layers of the network and number of computational units. Based on that process, we found a model that achieved very good performance on test data. We observed that Spark MLlib API is simple and easy to use for training the classifier and calculating its performance metrics. In reference to Hastie et. al, we have some final comments.

Articles like this are what got me interested in data analysis to begin with.

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