Voice of the DBA

Category: Editorial

  • More Open Data

    Steve Ballmer retired from Microsoft almost three years ago. It seems like a small eternity, and since his purchase of the NBA Los Angeles Clippers, I haven’t heard much about any ventures with which he’s been involved. Apparently, he’s spent some of his time, and quite a bit of money to build a site that discloses data about revenue and expenditures for the US Government. There’s a piece in the NYT about this project, as well as a shorter Engadget summary of the site, which provide a short look at the project.

    USAFacts.org is the site, and it’s a treasure of data sets. I look at this as a really interesting way to examine data sets that might be more difficult to gather than you’d expect. The Data Act deadline takes effect in May of 2017, which should also provide another way for anyone to look at public data and perform an analysis. I am disappointed the downloads aren’t working yet, but I hope that this will come soon, along with some sourcing information about where the data comes from and how it was gathered.

    Having data sets to analyze is important for any organization. Certainly within our organizations we spend a lot of time producing reports and queries that help various people analyze data. In fact, finding, collating, cleaning, and organizing information can be a taxing proposition in any size organization. Our data sets and sources are so diverse and often inconsistently producing data that it’s amazing at times that our organizations run well. It seems on a regular basis someone wants to rebuild the methodology used to gather and organize information. I am not surprised that I constantly find incorrect calculations in software because the basis we use changes too often.

    The big issue for me is that so many of us are amateurs when it comes to analyzing information. There aren’t many organized classes or a good structure for most data professionals to learn how to analyze data. We learn on the job, we make guesses and assumptions, and overall do a good job. However, data analysis is highly inconsistent from person to person. I’d like to see that change, and as I see more and more people blogging and talking about how they look at a particular data set, I hope more people are thinking about how to analyze information and how the choices we make for calculations, visualizations, and even ordering can affect how the results are interpreted.

    I’m glad Mr. Ballmer has started this project, and I look forward to seeing how people might use this data and other data sets to provide some analysis of the world.

    Steve Jones

  • Starting to Use SQL Server 2017

    We’ll have a new version of SQL Server this year. If you missed the Data Amp keynote, in it Scott Gu announced the name as SQL Server 2017, which I assume means we’ll have installable RTM bits sometime this year. Maybe in June, maybe August, maybe later. In any case, there are some interesting changes coming, though not a ton. We will get a new platform (Linux) and certainly some nice improvements in a few areas, but overall a limited release. Given this will be a year or so after the last one, that’s not surprising.

    This rapid release cycle means that all of us will support more versions of SQL Server. I don’t know many organizations that wholesale upgrade all their servers. The last time I saw that at any size was in SQL Server 2000, and even then it was painful. Since then it seems many organizations will add some instances of new versions, but continue to support old versions. The more people I talk to, the more I think the ten year rule does exist in many companies. I met someone years ago that said their company (Fortune 100) expected any server installed to run for ten years. Period.

    That seems to be the case. Lots of people still have SQL 2005, or at least SQL 2008 instances. A few SQL 2000, and certainly newer versions, but a mix. Keep that in mind, as most of your companies will move forward with new work even as you support old server. This week I wanted to ask, when do you think you’ll have SQL Server 2017 in production.

    Realistically, when will you have a 2017 platform running a live workload. I don’t care how big or small, Windows or Linux, bare metal or in a container. When will you start to use resumable index rebuilds, graph structures, adaptive query processing or more? Will it be in 2017? 2018? For budget or other reasons, later than that?

    I’m at an interesting place. We still run SQL 2008 at SQLServerCentral, and it works fine. The site needs a basic relational system, though certainly some of the T-SQL changes in 2012+ would be welcome and make some code easier to write. The thing is, code is already written and most things work. We’re debating going to 2016, but I wonder if we shouldn’t just aim at 2017, get one more version ahead, and delay the next upgrade for another decade. I’m certainly tempted as most of the work we through at the database is simple relational work that really would run on SQL 2000 if it had to.

    Regardless of when you might upgrade, are you interested in doing so? Anything catch your eye in the new version? Or have you not even bothered to pay attention? All valid answers, and I’m interested in your view of the new platform.

    Steve Jones

  • SQL Server on Linux is Just SQL Server

    I’ve been working with the SQL Server on Linux (SSoL) version for quite some time, almost a year. In all of that time, I’ve for the most part found that SQL Server is SQL Server. When I connect, run demos, check code, almost everything just works. If I didn’t bother to check @@version, this would appear to be just another SQL Server to me. That’s what a new video on Channel 9 shows as well. SQL Server is pretty much the same on both platforms. I’ve tested the Redgate tools and to all of them, SSoL is just SQL Server.

    There are some differences, which is to be expected. Any operations that access the file system and require paths work a bit differently, and for those people that end up administering the product, there will be some changes to get used to. The advanced HA features are similar, but again, some work is required. However, this isn’t all bad. I’m impressed with the apt-get process (I’m testing on Ubuntu), which is way, way easier than any patching or updating process I’ve gone through on Windows. In fact, setting up an Ubuntu VM last year was easy, and installing SQL Server was about as easy as it could be.

    The tooling on Linux isn’t as mature, and I don’t know when we will see a GUI client, but as I move more and more to PoSh or scripting to make changes in SQL Server, I expect more and more people to manage both Windows and Linux versions in the same way. Certainly using SSMS to write queries is a much nicer experience, and I would guess that many developers that might run SQL Server on OSX or Linux will want a Windows VM for SSMS. Of course, since Visual Studio is now on OSX, maybe we’ll see SSMS running natively on other platforms.

    I don’t know how many enterprises will run SQL Server on Linux, but I’m sure there are some that will. I don’t think a lot of organizations will move from Windows to Linux, unless they have loved SQL Server enough to install a single Windows host for the database and want to get rid of it now. I do think lots of developers will run SQL Server on Linux/OSX, especially in containers, where it is really easy to get a container running on their platforms.

    If you’ve experimented with SQL Server on Linux, or you are excited, let us know. If you think your organization might use this platform, let us know as well. I suspect a few of you will just because you can, which is as good a reason as any.

    Steve Jones

     

  • Becoming a Data Scientist

    Data Science is hot. There are lots of companies excited by using machine learning and AI to enhance their applications. There are new jobs, some of them well paying, and certainly not enough people to fill them. In many ways this reminds me of previous “hot” areas, such as Novell Networking in the late 80s/early 90s. Companies wanted new CNEs and paid dearly for them. The same thing happened in the mid 90s with MCSE’s for Microsoft networks. Many of the people hired weren’t remotely qualified, having just completed some multi-week boot camp.

    You could go to school. If you have completed college, there are a list of data science graduate programs that you could choose from and pursue a masters degree. There’s even a blog where someone is documenting their masters degree path to becoming a data scientist. This isn’t a quick or east path, but it is one way to gain data science skills.

    If you don’t want to spend the time or expense of a formal college program, Microsoft has a data science curriculum on the EdX platform that you can complete. These are low cost programs that you can complete to get a certificate. The value of that certificate is debatable, but the same could be said for any program. A few people that are working through this program have found it to be a good set of resources that is teaching them valuable skills.

    There are other options, no shortage of books, blogs, and other resources on data science and data analysis techniques. It’s up to you, however, to learn what you need to know and become competent at a level that is useful for some organization to pay you. I dislike people choosing to study a topic for a job, so I would say that if you wish to go down this path, do so because you enjoy the work and find it interesting. Build some skills, build a portfolio of data science projects, and best of luck.

    Our industry has thrived for a long time on simple analysis, and I think there will be jobs in this area for some time to come. I do expect that better looking reports and dashboards are going to be expected rather than simple tables, so I’d suggest everyone work on their visualization and report polishing skills. I also think that more complex data science techniques will be in demand, though I wouldn’t expect job growth here that overwhelms current jobs. Tackle data science if you like, but be aware this isn’t a simple or easy chore. There are lots of math and statistics involved and it looks like this is more science than just data.

    Steve Jones