Application areas

Posts focusing on the use of database and analytic technologies in specific application domains. Related subjects include:

September 28, 2014

Some stuff on my mind, September 28, 2014

1. I wish I had some good, practical ideas about how to make a political difference around privacy and surveillance. Nothing else we discuss here is remotely as important. I presumably can contribute an opinion piece to, more or less, the technology publication(s) of my choice; that can have a small bit of impact. But I’d love to do better than that. Ideas, anybody?

2. A few thoughts on cloud, colocation, etc.:

3. As for the analytic DBMS industry: Read more

September 21, 2014

Data as an asset

We all tend to assume that data is a great and glorious asset. How solid is this assumption?

*”Our assets are our people, capital and reputation. If any of these is ever diminished, the last is the most difficult to restore.” I love that motto, even if Goldman Sachs itself eventually stopped living up to it. If nothing else, my own business depends primarily on my reputation and information.

This all raises the idea – if you think data is so valuable, maybe you should get more of it. Areas in which enterprises have made significant and/or successful investments in data acquisition include:  Read more

September 15, 2014

Misconceptions about privacy and surveillance

Everybody is confused about privacy and surveillance. So I’m renewing my efforts to consciousness-raise within the tech community. For if we don’t figure out and explain the issues clearly enough, there isn’t a snowball’s chance in Hades our lawmakers will get it right without us.

How bad is the confusion? Well, even Edward Snowden is getting it wrong. A Wired interview with Snowden says:

“If somebody’s really watching me, they’ve got a team of guys whose job is just to hack me,” he says. “I don’t think they’ve geolocated me, but they almost certainly monitor who I’m talking to online. Even if they don’t know what you’re saying, because it’s encrypted, they can still get a lot from who you’re talking to and when you’re talking to them.”

That is surely correct. But the same article also says:

“We have the means and we have the technology to end mass surveillance without any legislative action at all, without any policy changes.” The answer, he says, is robust encryption. “By basically adopting changes like making encryption a universal standard—where all communications are encrypted by default—we can end mass surveillance not just in the United States but around the world.”

That is false, for a myriad of reasons, and indeed is contradicted by the first excerpt I cited.

What privacy/surveillance commentators evidently keep forgetting is:

So closing down a few vectors of privacy attack doesn’t solve the underlying problem at all.

Worst of all, commentators forget that the correct metric for danger is not just harmful information use, but chilling effects on the exercise of ordinary liberties. But in the interest of space, I won’t reiterate that argument in this post.

Perhaps I can refresh your memory why each of those bulleted claims is correct. Major categories of privacy-destroying information (raw or derived) include:

Read more

September 7, 2014

An idealized log management and analysis system — from whom?

I’ve talked with many companies recently that believe they are:

At best, I think such competitive claims are overwrought. Still, it’s a genuinely important subject and opportunity, so let’s consider what a great log management and analysis system might look like.

Much of this discussion could apply to machine-generated data in general. But right now I think more players are doing product management with an explicit conception either of log management or event-series analytics, so for this post I’ll share that focus too.

A short answer might be “Splunk, but with more analytic functionality and more scalable performance, at lower cost, plus numerous coupons for free pizza.” A more constructive and bottoms-up approach might start with:  Read more

May 6, 2014

Notes and comments, May 6, 2014

After visiting California recently, I made a flurry of posts, several of which generated considerable discussion.

Here is a catch-all post to complete the set.  Read more

April 16, 2014

The worst database developers in the world?

If the makers of MMO RPGs (Massive Multi-Player Online Role-Playing Games) aren’t quite the worst database application developers in the world, they’re at least on the short list for consideration. The makers of Guild Wars didn’t even try to have decent database functionality. A decade later, when they introduced Guild Wars 2, the database-oriented functionality (auction house, real-money store, etc.) would crash for days at a time. Lord of the Rings Online evidently had multiple issues with database functionality. Now I’m playing Elder Scrolls Online, which on the whole is a great game, but which may have the most database screw-ups of all.

ESO has been live for less than 3 weeks, and in that time:

1. There’s been a major bug in which players’ “banks” shrank, losing items and so on. Days later, the data still hasn’t been recovered. After a patch, the problem if anything worsened.

2. Guild functionality has at times been taken down while the rest of the game functioned.

3. Those problems aside, bank and guild bank functionality are broken, via what might be considered performance bugs. Problems I repeatedly encounter include:

In general, it seems like that what should be a collection of database records is really just a list, parsed each time an update occurs, periodically flushed in its entirety to disk, with all the performance problems you’d expect from that kind of choice.

Read more

March 23, 2014

DBMS2 revisited

The name of this blog comes from an August, 2005 column. 8 1/2 years later, that analysis holds up pretty well. Indeed, I’d keep the first two precepts exactly as I proposed back then:

I’d also keep the general sense of the third precept, namely appropriately-capable data integration, but for that one the specifics do need some serious rework.

For starters, let me say: Read more

February 23, 2014

Confusion about metadata

A couple of points that arise frequently in conversation, but that I don’t seem to have made clearly online.

“Metadata” is generally defined as “data about data”. That’s basically correct, but it’s easy to forget how many different kinds of metadata there are. My list of metadata kinds starts with:

What’s worse, the past year’s most famous example of “metadata”, telephone call metadata, is misnamed. This so-called metadata, much loved by the NSA (National Security Agency), is just data, e.g. in the format of a CDR (Call Detail Record). Calling it metadata implies that it describes other data — the actual contents of the phone calls — that the NSA strenuously asserts don’t actually exist.

And finally, the first bullet point above has a counter-intuitive consequence — all common terminology notwithstanding, relational data is less structured than document data. Reasons include:

Related links

February 2, 2014

Some stuff I’m thinking about (early 2014)

From time to time I like to do “what I’m working on” posts. From my recent blogging, you probably already know that includes:

Other stuff on my mind includes but is not limited to:

1. Certain categories of buying organizations are inherently leading-edge.

Fine. But what really intrigues me is when more ordinary enterprises also put leading-edge technologies into production. I pester everybody for examples of that.

Read more

January 9, 2014

The games of Watson

IBM excels at game technology, most famously in Deep Blue (chess) and Watson (Jeopardy!). But except at the chip level — PowerPC — IBM hasn’t accomplished much at game/real world crossover. And so I suspect the Watson hype is far overblown.

I believe that for two main reasons. First, whenever IBM talks about big initiatives like Watson, it winds up bundling a bunch of dissimilar things together and claiming they’re a seamless whole. Second, some core Watson claims are eerily similar to artificial intelligence (AI) over-hype three or more decades past. For example, the leukemia treatment advisor that is being hopefully built in Watson now sounds a lot like MYCIN from the early 1970s, and the idea of collecting a lot of tidbits of information sounds a lot like the Cyc project. And by the way:

Read more

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