Business intelligence

Analysis of companies, products, and user strategies in the area of business intelligence. Related subjects include:

March 23, 2014

Wants vs. needs

In 1981, Gerry Chichester and Vaughan Merlyn did a user-survey-based report about transaction-oriented fourth-generation languages, the leading application development technology of their day. The report included top-ten lists of important features during the buying cycle and after implementation. The items on each list were very similar — but the order of the items was completely different. And so the report highlighted what I regard as an eternal truth of the enterprise software industry:

What users value in the product-buying process is quite different from what they value once a product is (being) put into use.

Here are some thoughts about how that comes into play today.

Wants outrunning needs

1. For decades, BI tools have been sold in large part via demos of snazzy features the CEO would like to have on his desk. First it was pretty colors; then it was maps; now sometimes it’s “real-time” changing displays. Other BI features, however, are likely to be more important in practice.

2. In general, the need for “real-time” BI data freshness is often exaggerated. If you’re a human being doing a job that’s also often automated at high speed — for example network monitoring or stock trading — there’s a good chance you need fully human real-time BI. Otherwise, how much does a 5-15 minute delay hurt? Even if you’re monitoring website sell-through — are your business volumes really high enough that 5 minutes matters much? eBay answered “yes” to that question many years ago, but few of us work for businesses anywhere near eBay’s scale.

Even so, the want for speed keeps growing stronger. :)

3. Similarly, some desires for elastic scale-out are excessive. Your website selling koi pond accessories should always run well on a single server. If you diversify your business to the point that that’s not true, you’ll probably rewrite your app by then as well.

4. Some developers want to play with cool new tools. That doesn’t mean those tools are the best choice for the job. In particular, boring old SQL has merits — such as joins! — that shiny NoSQL hasn’t yet replicated.

5. Some developers, on the other hand, want to keep using their old tools, on which they are their employers’ greatest experts. That doesn’t mean those tools are the best choice for the job either.

6. More generally, some enterprises insist on brand labels that add little value but lots of expense. Yes, there are many benefits to vendor consolidation, and you may avoid many headaches if you stick with not-so-cutting-edge technology. But “enterprise-grade” hardware failure rates may not differ enough from “consumer-grade” ones to be worth paying for.

Read more

March 5, 2014

Analytics for everybody!

For quite some time, one of the most frequent marketing pitches I’ve heard is “Analytics made easy for everybody!”, where by “quite some time” I mean “over 30 years”. “Uniquely easy analytics” is a claim that I meet with the greatest of skepticism.*  Further confusing matters, these claims are usually about what amounts to business intelligence tools, but vendors increasingly say “Our stuff is better than the BI that came before, so we don’t want you to call it ‘BI’ as well.”

*That’s even if your slide deck doesn’t contain a picture of a pyramid of user kinds; if there actually is such a drawing, then the chance that I believe you is effectively nil.

All those caveats notwithstanding, there are indeed at least three forms of widespread analytics:

It would be nice to say that the first two bullet points represent a fairly clean operational/investigative BI split, but that would be wrong; human real-time dashboards can at once be standalone and operational.

Read more

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

November 10, 2013

RDBMS and their bundle-mates

Relational DBMS used to be fairly straightforward product suites, which boiled down to:

Now, however, most RDBMS are sold as part of something bigger.

Read more

October 31, 2013

Specialized business intelligence

A remarkable number of vendors are involved in what might be called “specialized business intelligence”. Some don’t want to call it that, because they think that “BI” is old and passé’, and what they do is new and better. Still, if we define BI technology as, more or less:

then BI is indeed a big part of what they’re doing.

Why would vendors want to specialize their BI technology? The main reason would be to suit it for situations in which even the best general-purpose BI options aren’t good enough. The obvious scenarios are those in which the mismatch is one or both of:

For example, in no particular order: Read more

October 30, 2013

Splunk strengthens its stack

I’m a little shaky on embargo details — but I do know what was in my own quote in a Splunk press release that went out yesterday. :)

Splunk has been rolling out a lot of news. In particular:

I imagine there are some operationally-oriented use cases for which Splunk instantly offers the best Hadoop business intelligence choice available. But what I really think is cool is Splunk’s schema-on-need story, wherein:

That highlights a pretty serious and flexible vertical analytic stack. I like it.

October 30, 2013

Glassbeam instantiates a lot of trends

Glassbeam checked in recently, and they turn out to exemplify quite a few of the themes I’ve been writing about. For starters:

Glassbeam basics include:

All Glassbeam customers except one are SaaS/cloud (Software as a Service), and even that one was only offered a subscription (as oppose to perpetual license) price.

So what does Glassbeam’s technology do? Glassbeam says it is focused on “machine data analytics,” specifically for the “Internet of Things”, which it distinguishes from IT logs.* Specifically, Glassbeam sells to manufacturers of complex devices — IT (most of its sales so far ), medical, automotive (aspirational to date), etc. — and helps them analyze “phone home” data, for both support/customer service and marketing kinds of use cases. As of a recent release, the Glassbeam stack can: Read more

October 18, 2013

Entity-centric event series analytics

Much of modern analytic technology deals with what might be called an entity-centric sequence of events. For example:

Analytic questions are asked along the lines “Which sequences of events are most productive in terms of leading to the events we really desire?”, such as product sales. Another major area is sessionization, along with data preparation tasks that boil down to arranging data into meaningful event sequences in the first place.

A number of my clients are focused on such scenarios, including WibiData, Teradata Aster (e.g. via nPath), Platfora (in the imminent Platfora 3), and others. And so I get involved in naming exercises. The term entity-centric came along a while ago, because “user-centric” is too limiting. (E.g., the data may not be about a person, but rather specifically about the actions taken on her mobile device.) Now I’m adding the term event series to cover the whole scenario, rather than the “event sequence(s)” I might appear to have been hinting at above.

I decided on “event series” earlier this week, after noting that:  Read more

October 10, 2013

Aster 6, graph analytics, and BSP

Teradata Aster 6 has been preannounced (beta in Q4, general release in Q1 2014). The general architectural idea is:

There’s much more, of course, but those are the essential pieces.

Just to be clear: Teradata Aster 6, aka the Teradata Aster Discovery Platform, includes HDFS compatibility, native MapReduce and ways of invoking Hadoop MapReduce on non-Aster nodes or clusters — but even so, you can’t run Hadoop MapReduce within Aster over Aster’s version of HDFS.

The most dramatic immediate additions are in the graph analytics area.* The new SQL-Graph is supported by something called BSP (Bulk Synchronous Parallel). I’ll start by observing (and some of this is confusing):

Use cases suggested are a lot of marketing, plus anti-fraud.

*Pay no attention to Aster’s previous claims to do a good job on graph — and not only via nPath — in SQL-MR.

So far as I can infer from examples I’ve seen, the semantics of Teradata Aster SQL-Graph start:

Within those functions, the core idea is:  Read more

October 6, 2013

What matters in investigative analytics?

In a general pontification on positioning, I wrote:

every product in a category is positioned along the same set of attributes,

and went on to suggest that summary attributes were more important than picky detailed ones. So how does that play out for investigative analytics?

First, summary attributes that matter for almost any kind of enterprise software include:

*I picked up that phrase when — abbreviated as RAS — it was used to characterize the emphasis for Oracle 8. I like it better than a general and ambiguous concept of “enterprise-ready”.

The reason I’m writing this post, however, is to call out two summary attributes of special importance in investigative analytics — which regrettably which often conflict with each other — namely:

Much of what I work on boils down to those two subjects. For example: Read more

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