DBA Reactions [humor]
You may not like every post but several are keepers.
I have mixed feeling about the auto-replay. Once is enough for many of them.
Enjoy!
PS: One where the replay works is: When I see the developers using an ORM and it actually performs well.
UK plastic surgery statistics 2012: brows up, breasts down by Ami Sedghi.
From the post:
Despite a recession and the government launching a review into cosmetic surgery following the breast implant scandal, plastic surgery procedures in the UK were up last year.
A total of 43,172 surgical procedures were carried out in 2012 according to the British Association of Aesthetic Plastic Surgeons (BAAPS), an increase of 0.2% on the previous year. Although there wasn’t a big change for overall procedures, anti-ageing treatments such as eyelid surgery and face lifts saw double digit increases.
Breast augmentation (otherwise known as ‘boob jobs’) were still the most popular procedure overall although the numbers dropped by 1.6% from 2011 to 2012. Last year’s stats took no account of the breast implant scandal so this is the first release of figures from BAAPS to suggest what impact the scandal has had on the popular procedure.
Just for comparison purposes:
| Country | Procedures | Population | Percent of Population Treated |
|---|---|---|---|
| UK | 43,172 | 62,641,000 | 0.00068% |
| US | 9,200,000 | 313,914,000 | 0.02900% |
Perhaps beauty isn’t one of the claimed advantages of socialized medicine?
How long is too long? Not long enough? Just right? (updated) by Karen Suhaka.
From the post:
A little frivolous confection for your holiday enjoyment: comparing how long bills are in different states. Thanks to Rich for a lovely job on the maps, as usual.
As a first comment, the average word length across the country of words in bills is 6.16 letters, vs about 5 letters in common writing. Given the technical language, one would certainly expect words to be longer on average, and 20% longer seems reasonable. But really I wanted to compare how long bills were, in word count, not in letter count. To start with, let’s simply look at the average length length of bills (in words) by state. I was quite surprised by the variation between states. Ohio bills are, on average, longer then bills in Tennessee, by almost 500 words!
Interesting visualization of the word length of legislation, state by state in the United States.
I suspect your observations about word length and states will be more pointed than mine.
Intro to Cypher Console by Peter Neubauer.
Peter has posted a 5 minute video introduction to the Cypher console.
Imagine a dynamic a friend of a friend graph for a Christmas or New Year’s party. Updated every 5 minutes and projected on a big screen.
Or you could allow guests to attach comments to the nodes/edges.
Rife with opportunities for humor. 😉
Google Imagines a Real World That’s as Irritating as the Internet by Rebecca Cullers.
From the post:
Google Analytics has put together a series of videos demonstrating what poor web design can do to an online commerce site—crap we’d never put up with in a brick-and-mortar store. There’s unintuitive search and site design that prevents you from finding the item you’re looking for—in this case, it’s a grocery store that makes it impossible to find an everyday item as simple as milk. There’s the obnoxious online checkout, where you’re forced to log in, agree to terms and prove you’re a real person before you get timed out, forcing you to start all over again. Then there’s a misplaced dig at Amazon’s highly successful, often copied suggestion of other items you might like. Produced in-house by Google Creative Lab, all the spots have the absurdity of a Monty Python skit. It seems weird for Google to be dissing online search and e-commerce, but here it serves the greater goal of telling people to learn more about their customers via Analytics. And in this case, it’s funny cause it’s true.
I won’t even attempt to describe the videos.
You will have to hold onto your chair to remain upright.
Seriously, they capture the essence of bad online shopping experiences.
Or should I say user interfaces?
An unlikely key sequence that triggers this behavior in a graph interface to a topic map could be quite amusing. 😉
I first saw this in a tweet by Christophe Viau.
A Real-Time Map of the Song “I Have Been Everywhere” by Johnny Cash
From the post:
Freelance web developer Iain Mullan has developed a map mashup titled “Johnny Cash Has Been EVERYWHERE (Man)!” [iainmullan.com].
The concept is simple yet funny: using a combination of an on-demand music service, an online lyrics catalog and some Google Maps programming magic, all the cities mentioned in the song are displayed simultaneously as they are mentioned during the song, as performed by Johnny Cash.
Some maps are meant to amuse.
BTW, Johnny prefers Safari or Chrome (as in won’t work with FireFox and I suspect IE as well).
Robert Cerny, a well known topic map maven, tweeted his favourite #GaryLarson cartoon, this one on dereferencing:
Inge Hendriksen tweets: “The #SemanticWeb explained in a single cartoon frame…“
Data Gift Guide by Nathan Yau.
From the post:
Now that we’re done giving thanks for all the intangibles like love, friends, family, and drunkenness, it’s time to turn our attention to the physical objects we don’t have yet. It’s the most wonderful time of year! Here are gift ideas for your data geek friends and family. A few of these take a while to make, so be sure to order them now so that you get them in time for Christmas.
Nathan has collected some interesting sources of gifts for the season.
From things I have never wondered about, pillows shaped like statistical distributions, to the more familiar books and electronics.
I mention this in lieu of any topic map specific gift sources that come to mind. Perhaps that will be different by next Christmas!
One possibility: Instead of a book of politicians and their dumb ideas, what if you had a book of dumb ideas with the politicians that hold them?
A reverse index of dumb ideas.
Other suggestions? (Volunteers to watch the news to create such an item? I have avoided it for years. What it doesn’t get wrong, is largely irrelevant.)
7 Symptoms you are turning into a Hadoop nerd
Very funny!
Although, as you imagine, my answer for #2 differs. 😉
Enjoy!
Just Joking: An Irreverent Look At Tech News by Fritz Nelson.
From the post:
Sometimes we take ourselves too seriously in this profession … after all, it’s technology. It’s not at all funny. Or is it? Maybe not, but the people and the companies are pretty funny, or at least deserve to be made fun of. Every year at the InformationWeek 500, we kick off the awards ceremony with a fun look back at the year in technology news.
Also, each month, we do the same to kick off our Valley View live Web TV program (the next show is October 24 at 11 a.m. PT). The two video clips below are from the InformationWeek 500 event, and from the September 26 Valley View.
Rock groups “arrive” by appearing on the cover of the Rolling Stone.
Topic maps will “arrive” by appearing in the comedy portion of InformationWeek 500.
Start refining jokes today!
DNA Big Data Research Stuns Stephen Colbert
Stephen is given 20 million copies of George Church’s Regenesis. His quick wit appears to retreat.
Watch the video at the link. What do you think?
Is this a good test for technology?
That it can stun Stephen Cobert into silence?
That may be too high a bar for topic maps. 😉
(Thought you might like something amusing. My next post is fairly grim.)
Err, you will just have to see this one. It…, defies description.
Not management appropriate, too many words. That would lead to questions.
Let’s start the week by avoiding management questions because of too many words in a video.
Learn to Speak DBA Slang by Brent Ozar.
Too amusing to not pass along.
Given my interest in documentation, my favorite is:
Updating the last step in the Disaster Recovery Plan:…..
(see Brent’s post for the definition)
T-Shirt Ideas for the Hadoop Team
Start the week with smile!
Now suggest t-shirt ideas for topic maps!
From Simply Statistics, a link titled We used, you know, that statistics thingy, which in the original read: We really don’t care what statistical method you used, all of which pointed to an abstract in BMC Systems Biology 2011, 5(Suppl 3):S4 that contains:
(insert statistical method here)
It happens. Even with proof reading by authors, copy editors, publishers.
But proof reading reduces the error rate greatly.
World’s Most Accurate Pie Chart
🙂
OK, I had to pass that one along but it has an important message:
Even with a picture, say what you have to say, then stop.
Graphing every idea in history by Nathan Yau.
I did a spot check and my idea about …., well, never mind, it wasn’t listed. (good thing)
Then I read that “every” idea meant only those in Wikipedia with an “”influenced by” or “influences” field.’
Started to breath a little easier. 😉
Interesting work but think about the number of facts that you know. Facts that influence your opinions and judgements that aren’t captured in any “fact” database.
Feds Look to Fight Leaks With ‘Fog of Disinformation’
From the Wired Story:
Pentagon-funded researchers have come up with a new plan for busting leakers: Spot them by how they search, and then entice the secret-spillers with decoy documents that will give them away.
Computer scientists call it it “Fog Computing” — a play on today’s cloud computing craze. And in a recent paper for Darpa, the Pentagon’s premiere research arm, researchers say they’ve built “a prototype for automatically generating and distributing believable misinformation … and then tracking access and attempted misuse of it. We call this ‘disinformation technology.’”
Two small problems: Some of the researchers’ techniques are barely distinguishable from spammers’ tricks. And they could wind up undermining trust among the nation’s secret-keepers, rather than restoring it.
There is a third problem as well: What about lobbyists, members of Congress, to say nothing of the Executive Branch who develop and lobby for policies based on information in decoy documents? No unauthorized disclosure but wasted effort based on bogus information. As distinguished from wasted effort on non-bogus information.
After the assassination of Osama bin Laden, there was an agreement among an identifiable group of executive branch officials on no detailed leaks. Next day, detailed leaks. Don’t need disinformation to know where to start rendering suspects on that one.
If they are serious about tracking leaks, whether to encourage (one department trying to discredit another) or discourage them (unlikely other than to avoid bad press/transparency), may I suggest using a topic map? Best way to follow unstructured information trails.
On the other side, to be fair, people leaking or using leaked information can use topic maps to avoid over-use of particular sources or information that can only be tracked to particular sources. Or intentionally developing information to identify (falsely), particular administration officials as the sources of information.
I was reminded of Cheech and Chong (Los Cochinos (1973)) when I read:
A mathematical model that has been used for more than 80 years to determine the hunting range of animals in the wild holds promise for mapping the territories of street gangs, a UCLA-led team of social scientists reports in a new study.
“The way gangs break up their neighborhoods into unique territories is a lot like the way lions or honey bees break up space,” said lead author P. Jeffrey Brantingham, a professor of anthropology at UCLA.
Further, the research demonstrates that the most dangerous place to be in a neighborhood packed with gangs is not deep within the territory of a specific gang, as one might suppose, but on the border between two rival gangs. In fact, the highest concentration of conflict occurs within less than two blocks of gang boundaries, the researchers discovered. (emphasis added)
Like the routine says: “…ain’t no time to be in my neighborhood….”
Almost forty (40) years later, the fundamental soundness of Los Cochinos is confirmed by other research. 😉
A new product has appeared that promises:
The Cirro product suite provides a solution for accessing any data on any platform in any environment without having to be a developer or programmer. Cirro’s solution represents a new paradigm “to consistently ask questions and extract value from structured and unstructured data sources” using tools already available on user desktops. Designed to be used by non-technical analysts, Cirro’s products are cloud based and can run on public, virtual private and on-premise cloud environments. This solution seamlessly integrates with existing data warehouse and leverages existing in-house BI analytic investments and can also be used as a standalone departmental solution for data marts and mash up analytics. The result is unparalleled data accessibility, new insights to your business and more informed decisions – faster.
And when I looked for more detail I found:
The Cirro Data Hub offers a revolutionary method that simplifies total data access by federating queries across multiple sources of structured, semi-structured, and unstructured data. With Cirro single query joins can be done between data residing in HDFS and a RDBMS. In short, Cirro removes the complexity of accessing any data, at any time, on any platform. Cirro Data Hub is a fresh approach to the challenge of federated processing. Federation of query processing is about taking the processing to the data. When using Cirro Data Hub users do not need to concern themselves with the complexities of having to stage data, various operating systems and multiple query languages. Rather, users need only concern themselves with what data they want and what they want to do with it. Cirro Data Hub determines where the processing of a query occurs and issues appropriate data requests to all data sources involved. Supporting this new approach to the federation of query processing are a number of patent pending technologies such as a federated cost based optimizer, smart caching, dynamic query plan re-optimization, normalization of cost estimates and a metadata repository for unstructured data sources.
Total data processing, encompassing NO SQL, Hadoop, or large traditional RDBMS data, requires new approaches for the querying of massive volumes of a variety of data sources. Existing approaches of bringing all of the data to a single location for query processing are no longer practical. Cirro Data Hub is the industry leading solution for providing scalability of processing for the challenges of total data.
After reading this more than once, I have the distinct impression of the Dilbert management summary that reads: Good.
Optional reading exercise for my topic maps class? Or do graduate students have enough experience reading vacuous vendor prose (VVP)?
BTW, so your time spent reading this post wasn’t a complete waste: Dilbert.
I first saw this at KDNuggets.
Wordcloud of the Arizona et al. v. United States opinion by Michael J Bommarito II.
From the post:
Here’s one purely for fun – a wordcloud built from the Supreme Court’s opinion on Arizona et al. v United States. Word clouds, though certainly not the most scientific of visualization techniques, are often engaging and “fun” ways to lead into discussion on NLP or topic modeling.
Includes the code to automate the process. One assumes you can amuse yourself as legal decisions, speeches, etc. emerge during an election year in the United States.
Suggestion: create a word cloud of questions by reporters and a separate word cloud of the responses by candidates.
The number of terms in common would be vanishingly low I suspect.
Pulp Fiction presented in chronological order
Nathan Yau reports:
Quentin Tarantino’s Pulp Fiction twists and turns through plot lines and time. Designer Noah Smith untangled the story and put it in a linear flowchart.
Just the sort of thing you will need if you want to experiment with topic mapping “Pulp Fiction.”
And if not that, certainly an amusing way to begin the week.
Makes me wonder what untangling Downton Abbey would take?
Data Mining Music by Ajay Ohri.
Ajay points to a 1985 paper by Donald Knuth, “The Complexity of Songs.”
Not the right time of year but I will forget it by the appropriate time next year.
Why My Soap Film is Better than Your Hadoop Cluster
From the post:
The ever amazing slime mold is not the only way to solve complex compute problems without performing calculations. There is another: soap film. Unfortunately for soap film it isn’t nearly as photogenic as slime mold, all we get are boring looking pictures, but the underlying idea is still fascinating and ten times less spooky.
As a quick introduction we’ll lean on Long Ouyang, who has really straightforward explanation of how soap film works in Approaching P=NP: Can Soap Bubbles Solve The Steiner Tree Problem In Polynomial.
And no, this isn’t what I am writing about on Hadoop for next Monday. 😉
I point this out partially for humor.
But considering unconventional computational methods may give you ideas about more conventional things to try.
Monday Fun: Seven Databases in Song
From the post:
If you understand things best when they’re formatted as a musical, this video is for you. It teaches the essentials of PostgreSQL, Riak, HBase, MongoDB, CouchDB, Neo4J and Redis in the style of My Fair Lady. And for a change, it’s very SFW.
This is a real hoot!
It went by a little too quickly to make sure it covered everything but it covered a lot. 😉
All kidding aside, there have been memorization techniques that relied upon rhyme and song.
Not saying you will have a gold record with an album of Hadoop commands with options but you might gain some noteriety.
If you start setting *nix commands to song, I don’t think Stairway to Heaven is long enough for sed and all its options.
Flowchart: Connections in Stephen King novels by Nathan Yau.
For your modeling exercise and amusement, a flowchart of connections in Stephen King novels (excluding the Dark Tower series). I not sure what impact excluding the Dark Tower series has on the flowchart. If you discover it, please report back.
Topic map and other semantic modeling groups could use this flowchart as the answer to Google employment questions. 😉
Speaking of modeling, I wonder how many degrees of separation there are between characters in novels?
And how would they be connected? Family names, places of employment, physical locations, perhaps even fictional connections?
That could be an interesting mapping exercise.
Always label your axes by Nathan Yau.
It’s visual humor in part so skip over the Nathan’s blog to see the image. I’ll wait.
Maybe that will help you remember the rule!
Now if I just had something like that for documenting data.
Suggestions?
A post by Mark Liberman that begins with this quote:
Sindya N. Bhanoo, “Real Words or Gibberish? Just Ask a Baboon“, NYT 4/16/2012:
While baboons can’t read, they can tell the difference between real English words and nonsensical ones, a new study reports.
“They are using information about letters and the relation between letters to perform the task without any kind of linguistic training,” said Jonathan Grainger, a psychologist at the French Center for National Research and at Aix-Marseille University in France who was the study’s first author.
Mark finds a number of sad facts, some in the coverage of the story and the others in the story itself.
His analysis of the coverage and the story proper are quite delightful.
Enjoy.
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