Voice of the DBA

Category: Editorial

  • Believing the Data

    This is interesting to me. Let’s leave aside the moral, ethical, or political sides of this. Let’s just look at the data. A cop gave a ticket to a self driving car. Apparently the officer thought the car was within 10 feet of a pedestrian. The logs for the car show that it was 10.4 feet away. A negligible difference to me, but that might matter in a court of law.

    As we use digital data more and more to control vehicles, devices, even behavior, we are going to have problems, complaints, and unforeseen issues amongst humans and computers. Certainly our laws need reforming to deal with the digital world, but we also will have some cultural transformations to undertake.

    Much of our arbitration in the world has dealt with how well humans argue or debate topics. We are inconsistent, easily confused creatures, yet we often use our judgment and impressions to make decisions about whether we believe one individual over another. This has often been the case in law, even as more science with cameras, DNA, and other forensic techniques have tried to provide definitive proof one way or the other.

    As we use more digital devices, there will be, or should be, more logs and audit records of how systems behave. This worries me a bit in Machine Learning systems, but experts seem to believe we can unpack the rationale for decision making if necessary. In any case, we need to learn to trust and believe in the data, even if our eyes and instincts lead us to different conclusions. This doesn’t mean that the data makes the decision, but we can’t discard the data because we don’t like it. Certainly context matters, and in the original case above, we’d want to consider velocity and acceleration, and possibly other factors to determine if the car was too close.

    Ultimately, I believe digital records will start to prevail in more circumstances than we might be comfortable with. We’ll slowly change, and likely subsequent generations will trust data more than we do, perhaps even more than their senses. To me, this means that those of us that deal with data systems need to ensure there is extremely strong security and integrity of data records, and that we disclose algorithms and data processing techniques in a transparent way. Trust requires knowledge, which requires transparency. That’s something we certainly need to improve on as an industry.

    Steve Jones

    The Voice of the DBA Podcast

    Listen to the MP3 Audio ( 3.1MB) podcast or subscribe to the feed at iTunes and Libsyn.

  • Considering Other Views

    I love my Pebble 2 watch. It’s simple, the charge lasts for days, and it does what I want out of a device. However, it’s a device that isn’t made anymore, and after a fall, I have a crack in the screen. Since I like having some sort of watch in my wrist, and I like gathering some health data, I started looking for other options. I was reading a review of the Fitbit Versa the other day, and the first part of the review was a literal problem with much software design I’ve seen recently.

    The first item in the review talks about notifications. Those are valuable on a device like this, and one of problems is text size. There’s a quote in there: “The text size is tiny, even when you select the item”. That’s a problem I’ve had with many devices, including the Pebble. In fact, I see this in software overall as a problem with design. It’s one that comes about because I think that far too often we don’t consider a wider range of viewpoints.

    I’m getting older. A consequence of that is my eyes do not focus as well as they used to and I need to increase the fonts on screens. I can easily do this in browsers, and make SSMS fonts larger in most cases, but not all. I can increase the size of some things in Windows, but that can cause issues in others. My phone allows some font changes, but that can be limited. There are times when notifications or other text is hard to read, and this limits the usefulness of these features.

    Technology has been growing and expanding as I’ve aged. However, it seems that more and more often companies are using people in their 20s and 30s to design systems that will increasingly be used by an aging population. From dashboards in vehicles to labels in applications, it seems that far too many designers don’t consider the impact of their font, icon, and graphic choices on older eyes. Even the design of our operating systems don’t seem to have deeply embedded extensive flexibility of changing text and icon sizes. Sure we can alter resolution, but that’s a very intrusive operation and may break other things. Often we just need labels enlarged.

    Software and UX design are hard, and often we get caught up in our own viewpoint of how to build an application. We won’t ever completely solve that as users will always have different ways they want to work with our systems. The ability to change options, and especially deal with accessibility choices will grow as our systems move out to a wider and wider audience. What might have seemed simple and intuitive may be more complex for new users that haven’t evolved with out system.

    Our database software likely isn’t going to be often seen by end users, and certainly we don’t have control over the tools they use, but we still ought to consider  how our objects will be used by others. More descriptive names, extended properties that tools can read, and even views to remap complex structures are good ways to provide an easier interface to the data for report designers and third party tools. Those items come with a cost and have to be maintained as we change schemas, but that might be a small price to pay if we can prevent lots of support tickets requesting details about what OrdrLnPrc means.

    Steve Jones

    The Voice of the DBA Podcast

    Listen to the MP3 Audio ( 4.6MB) podcast or subscribe to the feed at iTunes and Libsyn.

  • IoT Success

    After quite a bit of press the last few years, the IoT crazy has slowed a bit. I suspect this is because many of the consumer type IoT devices, such as refrigerators and washing machines, haven’t proven to be as useful or exciting as their developers originally thought. With all of the security issues that we’ve seen as well, having more interconnected “things” doesn’t seem to be so desirable for many individuals.

    In the industrial world, IoT is still thriving and growing, as businesses see just how inefficient they have been in the past. The way that many people have gotten business done is with lots of hard work and good luck along the way. Certainly farmers and ranchers have counted on instincts and good weather more often than science. Those items still matter, but smaller sensors and connected IoT devices can help reduce some of the risk and ensure better yields from your efforts.

    There’s an example of this in a short article about how various IoT devices are being used to help shrimp farmers in Columbia. Some of the uses, such as cameras to detect theft, are obvious, but the additional use of computing power and logic to reduce the need for a human to stare at a screen, vastly increases the chances of knowing when a theft is about to occur. Others sensors are used to check weather and actually monitor the shrimp in their environment, tasks which weren’t feasible for individual companies in the past to perform cost effectively.

    The key here really is being able to gather more data and process it efficiently. Lower hardware costs, better algorithms  and a variety of programmable sensors enable the capture and examination of this data in a way that can be customized for individual companies. Data can be very powerful for most organizations that perform actions in the analog world. IoT is helping them learn to better understand data they they wouldn’t previously have been able to capture.

    There are certainly still potential security problems with off the shelf sensors and grid connections. Anyone that wants to start to use these types of devices needs to understand the networking and potentially limit access to your main databases and systems, perhaps with tightly controlled ETL processes to funnel the data to staging areas. If you can do that, however, there are going to be opportunities to increase the efficiency of your operations, with plenty of data analysis and visualization jobs for the data professionals.

    Steve Jones

    The Voice of the DBA Podcast

    Listen to the MP3 Audio ( 3.9MB) podcast or subscribe to the feed at iTunes and Libsyn.

  • The Best Ever

    Every few years, or every year now, we see a new version of SQL Server proclaimed as the best ever. A few weeks ago, I saw a number of people leaving hte MVP Summit, rating it as the best ever summit. At SQL Bits or the PASS Summit every year, there’s no shortage of people posting about that event being the best conference.

    Is this a human view, that the latest one is often the best one ever if we enjoyed it? Perhaps we learn something and we’re excited about the latest new SQL thing and so we’re excited to proclaim it the best?

    What’s the best SQL Server version? Is there one for you? Some of you might be new to SQL Server or have worked with few versions, but perhaps one stands out. I’ve had the opportunity to work with a lot of versions, so the choices are hard. I’ve written code for SQL Server: 4.2, 6.0, 6.5, 7.0, 2000, 2005, 2008, 2008R2, 2012, 2014, 2016, 2017.

    I have two votes here. You might like one, and likely will disagree with one. First, I’ll say that I have a fondness for SQL Server 2000. This was a stable, long awaited version that dramatically improved my life from SQL 6.5. It was more reliable and faster, and since it came after a relatively short time after v7, I ended up standardizing on this at a few jobs. Most of my upgrades were to SQL Server 2000 and it lasted a long time as the standard version. It was 5 years before SQL Server 2005 was released, an eternity in today’s software lifecycle. There were some bumps in the road (SQL Slammer), but a better security coding model came about at Microsoft during this version as well as SSRS (added later).

    My other choice, maybe the top one, is SQL Server 2016. A number of security changes (AE, RLS, etc) as well as the inclusion of many features in Standard Edition (with SP1) make this my favorite. We got stability from the second version of OLTP tables and the third version of Availability Groups. I think SQL Server 2016 was perhaps the best version of SQL Server I’ve seen.

    You might have other votes, and let me know today. Is there a version that’s near and dear to your heart.

    Steve Jones

    The Voice of the DBA Podcast

    Listen to the MP3 Audio ( 3.0MB) podcast or subscribe to the feed at iTunes and Libsyn.