Voice of the DBA

Category: Editorial

  • Republish: I Feel Like a Magician

    I’m off in the UK and buried with other work, so a republish today.

    I Feel Like a Magician

  • We Don’t Have Perfect Information

    I was discussing the PASS Summit with someone and they were wondering about building their schedule. Actually, they wanted to pick sessions, but see the choices in a calendar format, but the schedule wasn’t out. My suggestion was to just build the schedule and then sort out conflicts later.
    A few people have mentioned over the years that they want to build a schedule and be ready for the event to maximize their experience and be efficient. I think that’s a common, normal, technical person thing to do. We’re Type-A, we like knowing and having a set schedule.
    The problem is that we don’t have perfect information. Even if the descriptions and abstracts included perfect information about the agendas, what is covered, and to what depth, including demos, we’d still not necessarily assimilate and recognize all that data. We’d think a session on database design covered fourth normal form, even when the text said third normal, or we’d expect that an SSIS data load talk included something on CSVs when the presenter described the talk as being with flag text files.
    We’re human, and that means we have flaws in how we deal with the world. This includes the ways in which we model and analyze data. While we can make mistakes in our analysis, we often may simplify our view of a problem to the point where our analysis is inherently flawed.
    I try to remember this when I write reports from systems that others will use. I won’t have every piece of information that might affect a system, but I try to ensure I have the most important, or significant, data. At least, the data I (and the users) feel is significant. The important thing to remember is that out data is always incomplete, and it’s entirely possible that we have missed a valuable piece of data.
    When that happens, we have to adapt and adjust our systems, just like our conference schedule. We’ll learn more across time and we can use that information to change our system. I know that my view of a conference like the PASS Summit today, or even a week before the event, will be different than what I know, and how I feel, at the event. I should have a plan, but be willing to flex as circumstances change.
    Steve Jones

  • Data Clarity

    There was an Associated Press (AP) report recently that noted Google applications track your location, even if you’re turned off Location History on your Android phone. The article has details about what the AP noted, as well as the report from some researchers that were testing the functionality. You can read the details, but the issue doesn’t seem to be as simple as the headline of the report.

    Google has responded to the claims, saying that they document and explain the various settings that need to be changed in the applications themselves to prevent any tracking. That might be the case in the eyes of the engineers that built the functionality, but I would tend to argue that the expectations, the descriptions, and explanations we use as technology professionals might not be clear enough for most users. We ought to be documenting, explaining, and even coding systems for users that aren’t as familiar as we are with the technology.

    This is an interesting issue. Not the location tracking, since I assume Apple, Google, government, and more can track my phone if they really want. To me, the issue is that we have data practices that are not clear to the end user. What Google documents, what they do with new services and features, and what the clients expect are not necessarily the same. That’s an issue, and I suspect it’s a similar issue for many companies.

    Most of us collect some level of detail from our software on how the user interacts with it. This might be a local log, or it might be some sort of telemetry, similar to what Microsoft collects from SQL Server. In either case, I think it’s important to spell out what data is being collected and to what extent this data is related to a specific individual or company. The changes to data handling as a result of the GDPR and other legislation might require that we do a better job of disclosing any data we collect, and in which specific circumstances.

    I know that data matters, but I also think that lots of the information that is collected doesn’t need to be related to a specific individual. Aggregates or tokenized data is often enough, though if you need to track a particular individual over time, such as the features they use in their install, be sure that you are very careful with any sensitive data, such as names, locations, etc. Most of us don’t have Google’s resources to combat legal action if customers find we are infringing on their privacy.

    Steve Jones

    The Voice of the DBA Podcast

    Listen to the MP3 Audio ( 3.6MB) podcast or subscribe to the feed at iTunes and Libsyn.

  • Protecting Our Stream of Data

    Protecting the data our companies collect is important. Many of us go to great lengths to secure our databases, firewall connections, limit access, and more. However, we can’t secure the data before it gets to us, and that can be a problem. I ran across a link on Bruce Schneier’s blog that shows a criminal placing a skimmer on a credit card scanner in a convenience store. The original video is gone, but there are plenty more.

    In general, the loss of data from the application (and physical hardware in this case), isn’t really a database issue. After all, the data is essentially split into two streams, with some going to the legitimate database and other processes while another stream goes to the skimmer. If this happens, and the skimmer isn’t discovered, however, it’s entirely possible that any data loss might be blamed on the database or IT infrastructure.

    If someone suspected you were hacked because of data being lost, could you prove you weren’t hacked? Or that the data didn’t come from your database? This is impossible, since you can’t prove a negative, but would you have any evidence that could be used to bolster your claims? Is there auditing or other tracking of activity? Does your organization keep any logs that would show a lack of activity and are protected against tampering? Ideally you would find the source that lost the data, but if you can’t, it can be difficult to prove that the losses didn’t come from your systems.

    For most of us, we might not have much in the way that would show our systems have only had legitimate access. Instead we’d depend on the limited SQL Server logging, as well as other infrastructure tracking, such as firewall activity logs. The strength of our presentation would likely determine whether security staff or management accepted our claims as valid.

    Point of Sale systems are different than the applications that most of us use, but certainly we have database security concerns that we should address. I would hope that SQL Server would bolster its capabilities in this area, providing a way to set up a tamper proof log easily that accepts writes of activity from a database in some structured text file that uses minimal resources. I’m not even sure what I’d want here that I can’t get from XE, but I do think having something more robust and standardized would be nice. If nothing else, a local SQL Server could stream XE events out to a file target in a remote location that only supports writing. This wouldn’t necessarily prove anything if the connection were disrupted, but it would ensure that a business was aware of the breakdown between the instance and audit log.

    I know the ways in which people attempt to access and steal data will continue to evolve and become more complex and creative. We can’t protect against many of them from the database side, but I’d like to think that we could protect the data we have. We should ensure it is safe from theft, loss, or inappropriate access and prove we have done so.

    Steve Jones

    The Voice of the DBA Podcast

    Listen to the MP3 Audio ( 4.2MB) podcast or subscribe to the feed at iTunes and Libsyn.