January 22, 2018

The chaotic politics of privacy

Almost nobody pays attention to the real issues in privacy and surveillance. That’s gotten only slightly better over the decade that I’ve written about the subject. But the problems with privacy/surveillance politics run yet deeper than that.

Worldwide

The politics of privacy and surveillance are confused, in many countries around the world. This is hardly surprising. After all:

Technical cluelessness isn’t the only problem. Privacy issues are commonly framed in terms of civil liberties, national security, law enforcement and/or general national sovereignty. And these categories are inherently confusing, in that:

Data sovereignty regulations — which are quite a big part of privacy law — get their own extra bit of confusion, because of the various purposes they can serve. Chief among these are:  Read more

December 15, 2017

The technology industry is under broad political attack

I apologize for posting a December downer, but this needs to be said.

The technology industry is under attack:

These attacks:

You’ve surely noticed some of these attacks. But you may not have noticed just how many different attacks and criticisms there are, on multiple levels.

Read more

December 12, 2017

Notes on artificial intelligence, December 2017

Most of my comments about artificial intelligence in December, 2015 still hold true. But there are a few points I’d like to add, reiterate or amplify.

1. As I wrote back then in a post about the connection between machine learning and the rest of AI,

It is my opinion that most things called “intelligence” — natural and artificial alike — have a great deal to do with pattern recognition and response.

2. Accordingly, it can be reasonable to equate machine learning and AI.

3. Similarly, it can be reasonable to equate AI and pattern recognition. Glitzy applications of AI include:

4. The importance of AI and of recent AI advances differs greatly according to application or data category.  Read more

August 22, 2017

Imanis Data

I talked recently with the folks at Imanis Data. For starters:

Read more

August 17, 2017

More notes on the transition to the cloud

Last year I posted observations about the transition to the cloud. Here are some further thoughts.

0. In case any doubt remained, the big questions about transitioning to the cloud are “When?” and “How?”. “Whether”, by way of contrast, is pretty much settled.

1. The answer to “When?” is generally “Over many years”. In particular, at most enterprises the cloud transition will span multiple CIO’s tenure in their positions.

Few enterprises will ever execute on simple, consistent, unchanging “cloud strategies”.

2. The SaaS (Software as a Service) vs. on-premises tradeoffs are being reargued, except that proponents now spell SaaS C-L-O-U-D. (Ali Ghodsi of Databricks made a particularly energetic version of that case in a recent meeting.)

3. In most countries (at least in the US and the rest of the West), the cloud vendors deemed to matter are Amazon, followed by Microsoft, followed by Google. And so, when it comes to the public cloud, Microsoft is much, much more enterprise-savvy than its key competitors.

Read more

August 10, 2017

Notes on data security

1. In June I wrote about burgeoning interest in data security. I’d now like to add:

We can reconcile these anecdata pretty well if we postulate that:

2. My current impressions of the legal privacy vs. surveillance tradeoffs are basically: Read more

June 30, 2017

Analytics on the edge?

There’s a theory going around to the effect that:

There’s enough truth to all that to make it worth discussing. But the strong forms of the claims seem overblown.

1. This story doesn’t even make sense except for certain new classes of application. Traditional business applications run all over the world, in dedicated or SaaSy modes as the case may be. E-commerce is huge. So is content delivery. Architectures for all those things will continue to evolve, but what we have now basically works.

2. When it comes to real-world appliances, this story is partially accurate. An automobile is a rolling network of custom Linux systems, each running hand-crafted real-time apps, a few of which also have minor requirements for remote connectivity. That’s OK as far as it goes, but there could be better support for real-time operational analytics. If something as flexible as Spark were capable of unattended operation, I think many engineers of real-world appliances would find great ways to use it.

3. There’s a case to be made for something better yet. I think the argument is premature, but it’s worth at least a little consideration.  Read more

June 16, 2017

Generally available Kudu

I talked with Cloudera about Kudu in early May. Besides giving me a lot of information about Kudu, Cloudera also helped confirm some trends I’m seeing elsewhere, including:

Now let’s talk about Kudu itself. As I discussed at length in September 2015, Kudu is:

Kudu’s adoption and roll-out story starts: Read more

June 14, 2017

The data security mess

A large fraction of my briefings this year have included a focus on data security. This is the first year in the past 35 that that’s been true.* I believe that reasons for this trend include:

*Not really an exception: I did once make it a project to learn about classic network security, including firewall appliances and so on.

Certain security requirements, desires or features keep coming up. These include (and as in many of my lists, these overlap):

More specific or extreme requirements include:  Read more

June 14, 2017

Light-touch managed services

Cloudera recently introduced Cloudera Altus, a Hadoop-in-the-cloud offering with an interesting processing model:

Thus, you avoid a potential security risk (shipping your data to Cloudera’s service). I’ve tentatively named this strategy light-touch managed services, and am interested in exploring how broadly applicable it might or might not be.

For light-touch to be a good approach, there should be (sufficiently) little downside in performance, reliability and so on from having your service not actually control the data. That assumption is trivially satisfied in the case of Cloudera Altus, because it’s not an ordinary kind of app; rather, its whole function is to improve the job-running part of your stack. Most kinds of apps, however, want to operate on your data directly. For those, it is more challenging to meet acceptable SLAs (Service-Level Agreements) on a light-touch basis.

Let’s back up and consider what “light-touch” for data-interacting apps (i.e., almost all apps) would actually mean. The basics are:  Read more

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