Learning About Big Data Clusters

Kevin Chant shares resources for getting started with SQL Server Big Data Clusters:

In a previous post I shared current SQL Server 2019 learning resources, which you can view in detail here.

However, SQL Server 2019 Big Data Clusters are very involved. So, I thought I better dedicate a whole post to further learning resources for it.

Because some people have different learning methods I have included references to both documents and videos in this post. In addition, I have created the below links in case somebody wants to go directly to a specific section.

Kevin’s put together quite a few useful links here.

What Makes for Good Coding Style

Brent Yorgey spends some time thinking about good coding style:

What is good code style? You probably have some opinions about this. In fact, I’m willing to bet you might even have some very strong opinions about this; I know I do. Whether consciously or not, we tend to frame good coding practices as a moral issue. Following good coding practices makes us feel virtuous; ignoring them makes us feel guilty. I can guess that this is why Yom said “I don’t think I could bring myself to be satisfied with partial functions” [emphasis added]. And this is why we say “good code style”, not “optimal” or “rational” or “best practice” code style.

It’s an interesting post. There are some bits on competitive programming which don’t apply in general, but there’s a lot to unpack there.

Long Weekend Learning Items

Kevin Chant has a few things you should check out if you’ve got several days of downtime:

Install and learn Docker
You can take the time over the Easter weekend to download and install Docker to see how you can use it. In addition, there are multiple posts online by people online that you can use as a starting point.
However, to start with you can read how to download and install it in detail here.

There are some good things on this list. Even if you don’t have a long weekend ahead of you, pick up some of these items gradually.

The State of SQL Server Monitoring Survey

Kendra Little would like a few minutes of your time:

Calling all Database Administrators, Developers, Analysts, Consultants, and Managers: Redgate has a survey open asking how you monitor your SQL Servers.

Take the survey before April 5, 2019.

Your time is valuable. The survey will take 5 – 10 minutes to complete. That’s not a ton of time, but it’s a noticeable part of your day, and there should be something in it for you. Here’s why it’s worthwhile to take the survey.

Read the whole thing and take that survey.

Visualization Failures

Stephanie Evergreen talks about two specific instances of self-inflicted visualization failure:

There’s a solid argument to be made that the scales in these charts shouldn’tstart at zero because we wouldn’t see any difference between the two years; all the lines would look flat. But there’s also a solid reason why they should start at zero—maybe I’m exaggerating the change if I don’t. Only the people who work closely with this data would know what kind of scale would fit best given the context of this foundation.

However, people on social media took notice of what they thought was a failure of mine and one commenter tweeted that “there’s no way [a dataviz Godfather] would approve this visual.” So, I got up the guts and sent the whole thing to the Godfather himself.

The Godfather wrote back: “To be honest, almost everything about your redesign is deceitful.” Ouch. I may have actually shed tears over this one. I was devastated.

There’s a good reminder here that failure is a critical part of learning.

The Thought Behind Metrics

Shannon Holck takes a book as a jumping-off point for failure by metric success:

There were some great use cases in the book.  Doctors that stopped taking cases that were difficult because it would ruin their surgical success metric.  Police that stopped responding to calls because it would ruin their case closure rate if they couldn’t solve it.

Muller states “The problem is not measurement, but excessive measurement, and inappropriate measurements – not metrics, but metric fixation.”

Shannon’s case study and recommendations were interesting.

Pobody’s Nerfect: The Andy Mallon Story

Andy Mallon shares a great story of a critical business mistake and then overcoming that self-inflicted adversity in a hotel room in Kalamazoo:

I still have vivid memories of that night. I’d ordered pizza so that I could stay back at my hotel room and finish my punch list of things before go-live the next day. It was after 2am, and I was sitting at the kitchen counter of the Residence Inn in Kalamazoo, MI, the pizza box still open next to me as I worked my way through a large pepperoni.

I got to the item on my punch list for “delete all test appointments.” The logic here was pretty simple: All the test appointments were for the same imaginary test patient. Just find all of that person’s appointments, and delete them. I decided I would do this one doctor at a time to make sure I didn’t mess it up too badly.

It’s a harrowing story with a happy ending.

Data Professional Salary Survey Results Released

Brent Ozar has a new year of data professional salary results:


How much do database administrators, analysts, architects, developers, and data scientists make? We asked, and 882 of you from 46 countries answered this year. Y’all make a total of $84,114,940 USD per year! Hot diggety. (And at first glance, it looks like on average, y’all got raises this year.)

Download the 2019, 2018, & 2017 results in Excel.

Read on for some notes about the data and start playing around.

Becoming An Expert

Adrian Colyer wraps up The Morning Paper for the year by reviewing a big picture paper on developer expertise:

You’ll know an expert programmer by the quality of the code that they write. Experts have good communication skills, both sharing their own knowledge and soliciting input from others. They are self-aware, understanding the kinds of mistakes they can make, and reflective. They are also fast (but not at the expense of quality).
Experience should be measured not just on its quantity (i.e., number of years in the role), but on its quality. For example, working on a variety of different code bases, shipping significant amounts of code to production, and working on shared code bases. The knowledge of an expert is T-shaped with depth in the programming language and domain at hand, and a broad knowledge of algorithms, data structures, and programming paradigms.

Click through for the full review.

Thoughts On The Year’s Big Data Platform News

Kevin Chant shares some thoughts on some of the biggest news stories of 2018 for data platform professionals:

Hortonworks and Cloudera announcement about their merger is certainly an interesting for the Big Data landscape. These two are thought to be the leaders in the Hadoop industry.
Undeniably, a lot of people have seen what these two Big Data giants have delivered over the years within the Hadoop ecosystem.
With this merger they are aiming to use their combined expertise to deliver an enterprise data cloud. We’ve already seen what Hadoop based cloud offerings like HDInsight are capable of, so the potential here is huge.
Certainly, there’s potential for this to have massive implications in the Big Data industry. And this merger could also encourage even more Data Platform offerings to emerge.

Read on for Kevin’s thoughts on five major stories this year.

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