Browsing articles from "January, 2014"

Refactoring Computer Engineer Barbie

Jan 30, 2014   //   by Karen Lopez   //   Awesome, Blog, Data, Need Your Help, Snark, WIT, WTF  //  23 Comments

imageIn mid-January I came across a link to a story about a new book by Random House called Barbie I Can Be…A Computer Engineer.  As you know, I travel with a Computer Engineer Barbie (@data_model) and Venus Barbie (@venusbarbie) in my work advocating that girls take more STEM courses.  So let’s say I have a strong interest in making sure my wonder girl Barbie has a great book.

But the story said that the book actually put Barbie in not so great place.  So I bought the book and read it.  And it made me cringe.  I read it a few times and decided it needed to be fixed.  Or in Computer Engineering terms, it need to be refactored.

So that’s what I’ve done.  In this review of Barbie I Can Be…A Computer Engineer, I will point out the parts that set a lousy role model for girls and offer suggestions on how it can be refactored to make it better.  Just like in software refactoring, I’m not going to change the functionality of the book, but I’m going to improve the code words to leave it better.

And to make it easy for you to fix you copy, I’ve included a Refactoring Computer Engineer Barbie PDF. You are welcome.

Synopsis (SPOILER ALERT!)

Barbie is working on a design for a new puppy computer game when her laptop catches a virus.  Luckily, she wears a heart USB drive around her neck and has backups of her files.  So she uses her little sister’s (Skipper) laptop to try to retrieve the files.  Oh, CURSORS! she has infected Skipper’s laptop, too.  She promises to make it all right and rushes off to school to ask her computer teacher (who is a female!) how to fix it. Her teacher gives her some tips and Barbie heads to the library to get get both her data and Skipper’s data back.  She gets two friends to help and they get it done.  Skipper, with her restored data, makes an excellent presentation in her class where she says that Barbie is the person she most admires. Cue tears.  Barbie presents her game in computer class.  She does such a wonderful job, her teacher even gives her extra credit.

The End.

Well that sounds Awesome! Isn’t it?

Sounds like a great story with good female leadership, doesn’t it?  Female teacher, Barbie and friends fix the problem, Skipper and Barbie give great presentations.  We need more great females to speak, right? Well, just like in database design, the Devil is in the details.

Unfortunately, some of the details really make it look like Barbie is more of a Booth Babe than a Computer Engineer.  This is making the IT community cringe. Twitter is blowing up with campaigns to get the book removed from shelves or to get Random House to fix it.  Well, I’m going to save Random-House the effort by fixing refactoring it for them.  It’s one thing to raise the issue, but as a designer-architect-project manager-methodologist-computer engineer, I just want to FIX it.

Let’s start with the first troublesome passage:

Computer Engineer Barbie Laughs and is Needy

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"I’m designing a game that shows kids how computers work", explains Barbie. "You can make a robot puppy do cute tricks by matching up a color blocks!"

"Your robot puppy is so sweet," says Skipper. "Can I play your game?"

"I’m only creating the design ideas," Barbie says, laughing. "I’ll need Steven’s and Brian’s help to turn it into a real game."

That last line is a problem. First, saying “I’m only” makes it look like design work is some how lesser than building.  I know there are some techs out there that would agree with that, but it’s still not true.  In fact, in technical professions, the designer / architect is the senior position on the project.  Secondly, she is laughing this line, as if it is hilarious to think that Barbie can build something.  Finally, Steven and Brian are recurring characters throughout the I Can Be… book series.  They are friends and friends help each other.  But this passage seems to reinforce a position that boys build, girls draw.

So I’ve refactored this passage by changing out that line with this one:

"Not yet," explains Barbie. "I need to finish the design then work with Steven and Brian to turn it into a game."

See how that says basically the same thing, but it doesn’t devalue Barbie’s design work? It also reinforces the more realistic situation that teams work together to make a product.  Barbie doesn’t “need help”; she is part of a team to get it done.

Steve and Brian Will Get It Done Faster

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After class Barbie meets with Steven and Brian in the library.

"Hi guys!" says Barbie. "I tried to send you my designs but I ended up crashing my laptop and Skipper’s, too. I need to get back to lost files and repair both of our laptops."

"It will go faster if Brian and I help," offers Steven.

This last line could be interpreted that Steven and Brian, not Barbie, can get this done faster.  I realize this is just one interpretation and the intention could be that if everyone works together, we can get it done faster.  We know in software engineering this may or may not be true – in form of the Mythical Man Month.  But in general, three people fixing two laptops might make this all go faster – debugging, troubleshooting, copying files and those sorts of things typically do turn out better with more people at the desk. 

But I’m still concerned about the fact that the less generous interpretation could be that boys can fix things; girls just come to them with their problems. So I’ve refactored this to say:

"We can all work on this together; it will be faster," says Steven.

The work continues with this on the next page:

"I got Skipper’s assignment from the hard drive!" exclaimed Steven.

"Fantastic!" says Barbie. "And her other files as well?"

"I got everything," says Steven. "Now let’s retrieve the files from your hard drive. Both laptops will be good is new in no time!"

It’s here where the dialogue really makes it look like Steven did all the work and Barbie waited anxiously for the results of his work. So I’ve refactored these to show Barbie being more engaged in the process.  Not just the Holder of the Compact Disc.

"We’ve got Skipper’s assignment from the hard drive!" exclaimed Steven.

"Fantastic!" says Barbie. "Let me get her other files as well!"

"Great! Now we’ve got everything," says Steven.

See how Barbie has a more engaged role here? No confusion about her fixing this problem, too.

One More Thing…

One of the key things that an engineer should do when disasters happen is to ensure that it never happens again.  One of the steps missing from this story is making sure Barbie and Skipper’s laptops are safe from future viruses. So I’ve added a new line to a passage:

The next morning Barbie gives her sister a big surprise. Skipper turns on your laptop – and it works!

"My lost assignment! cries Skipper. "You are just too cool, Barbie. You fixed my computer and saved my homework!

"I set up new security software on both laptops to make sure this doesn’t happen again," exclaims Barbie.

Skipper gives Barbie a huge hug.

You can’t just retrieve the files; you have to ensure those pesky viruses don’t come back.

How Do We Fix the Book, Though?

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I fixed my copy by refactoring the printed pages.  You can do that, too. I’m sharing the Refactoring Computer Engineer Barbie PDF I created with the refactored dialogue.  Just print it on sticker paper and cut out the revised sections to update your copy of the book.  You might also want to head over to read that open letter to Random House, too.

I love my Technical Barbies and I want girls (and their parents) to have great role models in real life, not just with dolls action figures.  So books like this need the Best Practices in their writing.  I hope you do, too.

I have another post coming about the computer security parts of this story.  But for now, go fix your copy of this book.  Don’t leave it sitting around in production, waiting for someone to read it when it’s wrong.  Love your Data and Love your @Data_Model.

Parallels Access–Use Desktop Applications on your iPad the Right Way–WIN!

Jan 30, 2014   //   by Karen Lopez   //   Blog, Data, Fun, Gadgets  //  No Comments

I’ve been using Parallels Desktop for Mac ever since I purchased my MacBook Air a couple of years a go.  This virtualization software lets me run Windows on my Mac so that I can use all the data modeling and database tools I need.

Just this week, Parallels asked if I wanted to try out a new product, Parallels Access.  (So as to not confuse this with Microsoft Access, I’m going to use the full name of the product in this post.)  This product lets me use desktop applications as if they were built for the iPad.  It works by installing an app on my iPad, plus a service on my desktops (Windows or Mac).  Then when I want to run a “real” application from one of my computers, I can fire up the app on my iPad and start using it. And it pretty much works.

I’m hosting a contest to give away five, yes FIVE, subscriptions for this product.  Details at the bottom of this post.

Isn’t This the Same as Remoting In to Your Desktop?

I’m betting right now you’re thinking: “I have RDP or some other remote app and I can use that, but it’s a real pain to navigate around on an iPad.”  Yes, yes it is.  I’ve tried several remoting apps over the last few years. I usually use them when I am out of my office and have to grab a file or fix something without having to find a computer to use a real keyboard and mouse.  And it’s painful.  Very painful.

What’s different about Parallels Access is that they’ve added iOS-like gestures and interactions to make it feel like the application you are running is a native iPad app.  Instead of telling you about it, let me show you a few:

 

Quick view of gesture features.

 

Precision pointer

 

iOS keyboard, with a Windows Key and a Mac Key.

How I Use Parallels Access

Today I used Parallels access to work with some Excel spreadsheets, which I have done in the past with either iPad apps or via remoting in to a desktop.  Both ways are painful. It’s almost impossible to widen a column or cut and paste data in Excel using the iPad and the iPad apps don’t always support all the features I need.  I won’t be using this as my main method for working with Excel, database or data modeling tools.  But having the ability to pinch to zoom in applications  is very nice.  In ERwin Data Modeler, I was even able to reposition entities and fine tune relationship lines.  That just doesn’t work using a basic Remote Desktop tool.  Heck, it doesn’t even work as well on my touch screen desktop.

I also love that the keyboard is an iPad keyboard that features a Windows Key when you are on a Windows desktop and a Mac one when you are on a Mac.  That’s how keyboards should work.

I’ll post a more detailed review of how I am using Access to work with my desktop applications in the future.  For now, some gratuitous screen shots.

Access touch on iPad - LauncherAccess touch on iPad - Data Model

Win a 1 Year Subscription to Parallels Access

There’s a 14-day trial for Parallels Access available, but I have a better deal for you: enter to win one of FIVE one-year subscriptions (worth $4.99 a month or $49 a year) I have to give away via Twitter.  Here’s what you need to do:

  1. Follow me @datachick
  2. Tell me where you would use Parallels Access.  For example, “I would use Parallels Access from my deck, sipping a beverage with @datachick” or “I’d love my data with @datachick”.
  3. Contest ends Friday, 1 February at midnight EST, so tweet before then.

I’ll pick 4 random winners from the tweets and one special one chosen as the best tweet.  Just make sure you mention me (include @datachick  in your tweet) and the product (Parallels Access) so I see your entry.

Rules:

  • Your tweet has to mention me and Parallels Access
  • Your tweet must be posted publicly – not a DM.
  • Your tweet must be published before 1 Feb 2014 at midnight EST
  • If you live in one of those places that has laws against these contests (Allô Québec!): Sorry, you can’t be part of this.
  • If you live in one of those places that has a law requiring a skills testing question (O Canada!) I will give you a fancy data modeling question to do.  No worries, it will be an easy one.
  • A winning tweet and your twitter account have to be Safe For Work.  Let’s call it “SFW USA”.  That works.
  • No more than 5 entries from you.
  • You don’t have to own an iPad (2nd through current generation), but you’ll need one to use this product.
  • No returns or exchanges.  No whining.  No bad data. No tipping. Bribes are discouraged by Management.

Good luck and get touching and tweeting!

Worst Bar Chart* of 2014–We May Already Have a Winner

Jan 29, 2014   //   by Karen Lopez   //   Blog, Data, Data Visualization, Fun, Snark, WTF  //  7 Comments

 

Update: It appears that this chart and other data visualizations have been removed from the website and report.  I’m hoping that means that the authors will be refactoring them with improved graphics.  Meanwhile, I’m going to leave my post below as is.  There are good lessons and tips to be shared. 

I know.  I hear you. It’s still January and we might just have a winner, one that will be impossible to beat during the next 12 months. Incredible. As you may recall, in late 2011 I awarded Stupidest Bar Chart to a doozy from Klout.  That bar chart was confusing, but not in the way this one is.  First, put down your beverage of choice.  Then take a look at this:

 

image

 

Yeah.  That…chart.  It’s kind of like a horizontal stacked bar chart.  I don’t understand anything about it, though.   This chart comes from an infographic at Deloitte.com  on Analysis Trends for 2014.

Maybe zooming in might help?

 

image

 

Nope, doesn’t make it any clearer. In fact, it’s just as crazy, but bigger.  Call it Big Crazy DataTM.

Here are the issues and questions I have about it:

  1. What do the colours mean? If this were a stacked bar chart, the grey and blue areas would indicate different data.  It appears that only some sections have data. But I’m not sure.
  2. What is the scale?  Normally a bar chart would have an axis that indicates some measure and all the bars would be graphed against that axis.  This has no axis.
  3. Why do some bars have signed numbers and one have a range?  Why are some numbers unsigned? Even some delta numbers are unsigned.
  4. What do the relative sizes of the sections mean?  In one bar we see a blue section labeled 285, but it’s larger than a section labeled 425-475
  5. Where numbers appear, do they describe the section they are on or the section next to the number? I’m not sure
  6. What does the relative position of the blue section mean? I’m not sure.
  7. Why are some of the labels in light grey and some in dark grey? I’m not sure
  8. What are the units of measurement for these numbers? Are some percentages? Units of 1000s? 100,000s? Are they of people? Positions? Something else? I’m not sure.
  9. Do the endnotes there explain the numbers? No, they are just citations for reference materials used to create the report.

Maybe the chart has an explanation inside the full document, Analytics Trends 2014: (And why some may not materialize)… No, same chart, no text that directly explains any of the numbers. To add some irony to this, the report itself is about Analytics and even covers trends in visualizations.

A Picture is Worth A Thousand Words, Unfortunately.

image

The report has something to say about data visualizations used in data analytics:

There’s no question that visualization has become a critical capability for organizations of virtually every shape and size. Easy-to-use software makes complex data accessible and understandable for almost any business user. From discovery and visual exploration to pattern and relationship identification, today’s visualization tools easily affirm the adage that a picture is worth a thousand words. Or, in this case, numbers.

This is especially true with big data, where visualization may even be a necessary capability for driving insights. That’s why visually oriented tools are rising in prominence for many big data applications. Users get to understand, explore, share, and apply data efficiently and collaboratively—often without the need for analytics professionals. And that’s where the risk comes in. In their eagerness to dive into data, users may choose polished graphics over thorough data preparation and normalization and rigorous analysis—glossing over important insights and analysis opportunities and potentially producing erroneous results. [emphasis mine]

Keep reading the report from that section.  The irony burns.

What’s Going on with this Bar Chart?

I’d bet that the Analytics professionals at Deloitte know much better than this.  The webpage and report for Analytics trends is beautiful to look at.  I’m guessing that a graphics designer has taken these numbers and created a beautiful, yet meaningless graphic with numbers. And just as the report predicts, people who don’t understand how to best use visualizations can gloss over important insights and analysis opportunities and potentially produce erroneous results.  This report has some great points. And it’s pretty.  Very, very pretty.  But the distraction of bad visualizations makes difficult for me to actually see the points the authors are trying to make.

My guess is also that this data, as a set, had no business being put together in one chart.  I’m not sure, but they don’t seem to have the same measures or even be the same type of data.  So putting them in one chart won’t help.  This was a page in a report needing a graphic, so someone made one.

*Updates:

Jamie Calder ( @jamiecalder) helped me “see” the story this chart is trying to tell: think of it as a math equation.  That might get you there.  But it’s still not an appropriate use of a bar chart.  And Josh Fennessy ( @joshuafennessy)  has pointed out that this isn’t supposed to be a bar chart at all. It’s supposed to be a waterfall chart.  But it’s dressed up as a bar chart, so I’m going to still leave as a contender for Worst Bar Chart of 2014.  Let’s just call it a self-nominated chart.  Martin Ribunal has found what is most likely the original chart from which this chart was most likely copied inspired by and has listed that in comments below.

What Have We Learned About Data Visualizations?

  1. The best data analysis can be invalidated with bad data visualizations.
  2. If you develop content, insist that you say in the final published work.  I know this is difficult in large corporate entities, but it’s important to ensuring that your goals are met.
  3. The more accessible we make self-serve BI and data visualization tools available, the more responsibility we have to educate, train, and mentor those using these tools.
  4. Show your visualizations to other people.  Ask them what they see. Ask them if they are confused, what conclusions they might have and what questions they still have.
  5. Choose the right chart type to fit your data.  Then use that chart correctly.
  6. If you needs a graphic image, don’t mimic a recognized chart type. 
  7. If you add a chart to a document, you should actual reference it in the text in the way that helps the reader understand it.
  8. If your chart has numbers, you have to say what those are number of, including some sort of unit of measure.  And your graphics should correctly portray their relative size.
  9. If a chart leaves viewers saying “I’m not sure” more than once, it’s not working.
  10. Loving your data means loving how it is presented, too.

What Would You Ask?

What other questions do you have about this…graphic.? How would you improve it?

I can’t bring myself to call it a bar chart any more.  But it’s still dressed as a bar chart, so it fits the nomination category.  If you find a bar chart or any other data visualization to nominate, let me know.  I wouldn’t want something worse than this one to go unrecognized.

Data Will Confess to Anything….

Jan 10, 2014   //   by Karen Lopez   //   Blog, Data, Data Governance, Fun, Snark  //  No Comments

Star Trek Data being interrogated

via Thomas LaRock ( blog | @sqlrockstar )

Remember this the next time you see some statistics.  Or a report.  Or anything that appears on Wikipedia.

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