Data Quality and #FollowFriday the 13th

As Alice Hardy arrived at her desk at Crystal Lake Insurance, it seemed like a normal Friday morning.  Her thoughts about her weekend camping trip were interrupted by an eerie sound emanating from one of the adjacent cubicles:

Da da da, ta ta ta.  Da da da, ta ta ta.

“What’s that sound?” Alice wondered out loud.

“Sorry, am I typing too loud again?” responded Tommy Jarvis from another adjacent cubicle.  “Can you come take a look at something for me?”

“Sure, I’ll be right over,” Alice replied as she quickly circumnavigated their cluster of cubicles, puzzled and unsettled to find the other desks unoccupied with their computers turned off, wondering, to herself this time, where did that eerie sound come from?  Where are the other data counselors today?

“What’s up?” she casually asked upon entering Tommy’s cubicle, trying, as always, to conceal her discomfort about being alone in the office with the one colleague that always gave her the creeps.  Visiting his cubicle required a constant vigilance in order to avoid making prolonged eye contact, not only with Tommy Jarvis, but also with the horrifying hockey mask hanging above his computer screen like some possessed demon spawn from a horror movie.

“I’m analyzing the Date of Death in the life insurance database,” Tommy explained.  “And I’m receiving really strange results.  First of all, there are no NULLs, which indicates all of our policyholders are dead, right?  And if that wasn’t weird enough, there are only 12 unique values: January 13, 1978, February 13, 1981, March 13, 1987, April 13, 1990, May 13, 2011, June 13, 1997, July 13, 2001, August 13, 1971, September 13, 2002, October 13, 2006, November 13, 2009, and December 13, 1985.”

“That is strange,” said Alice.  “All of our policyholders can’t be dead.  And why is Date of Death always the 13th of the month?”

“It’s not just always the 13th of the month,” Tommy responded, almost cheerily.  “It’s always a Friday the 13th.”

“Well,” Alice slowly, and nervously, replied.  “I have a life insurance policy with Crystal Lake Insurance.  Pull up my policy.”

After a few, quick, loud pounding keystrokes, Tommy ominously read aloud the results now displaying on his computer screen, just below the hockey mask that Alice could swear was staring at her.  “Date of Death: May 13, 2011 . . . Wait, isn’t that today?”

Da da da, ta ta ta.  Da da da, ta ta ta.

“Did you hear that?” asked Alice.  “Hear what?” responded Tommy with a devilish grin.

“Never mind,” replied Alice quickly while trying to focus her attention on only the computer screen.  “Are you sure you pulled up the right policy?  I don’t recognize the name of the Primary Beneficiary . . . Who the hell is Jason Voorhees?”

“How the hell could you not know who Jason Voorhees is?” asked Tommy, with anger sharply crackling throughout his words.  “Jason Voorhees is now rightfully the sole beneficiary of every life insurance policy ever issued by Crystal Lake Insurance.”

Da da da, ta ta ta.  Da da da, ta ta ta.

“What?  That’s impossible!” Alice screamed.  “This has to be some kind of sick data quality joke.”

“It’s a data quality masterpiece!” Tommy retorted with rage.  “I just finished implementing my data machete, er I mean, my data matching solution.  From now on, Crystal Lake Insurance will never experience another data quality issue.”

“There’s just one last thing that I need to take care of.”

Da da da, ta ta ta.  Da da da, ta ta ta.

“And what’s that?” Alice asked, smiling nervously while quickly backing away into the hallway—and preparing to run for her life.

Da da da, ta ta ta.  Da da da, ta ta ta.

“Real-world alignment,” replied Tommy.  Rising to his feet, he put on the hockey mask, and pulled an actual machete out of the bottom drawer of his desk.  “Your Date of Death is entered as May 13, 2011.  Therefore, I must ensure real-world alignment.”

Da da da, ta ta ta.  Da da da, ta ta ta.  Da da da, ta ta ta.  Da da da, ta ta ta.  Data Quality.

The End.

(Note — You can also listen to the OCDQ Radio Theater production of this DQ-Tale in the Scary Calendar Effects episode.)

#FollowFriday Recommendations

#FollowFriday is when Twitter users recommend other users you should follow, so here are some great tweeps who provide tweets mostly about Data Quality, Data Governance, Master Data Management, Business Intelligence, and Big Data Analytics:

(Please Note: This is by no means a comprehensive list, is listed in no particular order whatsoever, and no offense is intended to any of my tweeps not listed below.  I hope that everyone has a great #FollowFriday and an even greater weekend.)

Twitter, Data Governance, and a #ButteredCat #FollowFriday

I have previously blogged in defense of Twitter, the pithy platform for social networking that I use perhaps a bit too frequently, and about which many people argue is incompatible with meaningful communication (Twitter that is, not me—hopefully).

Whether it is a regularly scheduled meeting of the minds, like the Data Knights Tweet Jam, or simply a spontaneous supply of trenchant thoughts, Twitter quite often facilitates discussions that deliver practical knowledge or thought-provoking theories.

However, occasionally the discussions center around more curious concepts, such as a paradox involving a buttered cat, which thankfully Steve Sarsfield, Mark Horseman, and Daragh O Brien can help me attempt to explain (remember I said attempt):

So, basically . . . successful data governance is all about Buttered Cats, Breaded CxOs, and Beer-Battered Data Quality Managers working together to deliver Bettered Data to the organization . . . yeah, that all sounded perfectly understandable to me.

But just in case you don’t have your secret decoder ring, let’s decipher the message (remember: “Be sure to drink your Ovaltine”):

  • Buttered Cats – metaphor for combining the top-down and bottom-up approaches to data governance
  • Breaded CxOs – metaphor for executive sponsors, especially ones providing bread (i.e., funding, not lunch—maybe both)
  • Beer-Battered Data Quality Managers – metaphor (and possibly also a recipe) for data stewardship
  • Bettered Data – metaphor for the corporate asset thingy that data governance helps you manage

(For more slightly less cryptic information, check out my previous post/poll: Data Governance and the Buttered Cat Paradox)

 

#FollowFriday Recommendations

Today is #FollowFriday, the day when Twitter users recommend other users you should follow, so here are some great tweeps for mostly non-buttered-cat tweets about Data Quality, Data Governance, Master Data Management, and Business Intelligence:

(Please Note: This is by no means a comprehensive list, is listed in no particular order whatsoever, and no offense is intended to any of my tweeps not listed below.  I hope that everyone has a great #FollowFriday and an even greater weekend.)

 

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#FollowFriday Spotlight: @PhilSimon

FollowFriday Spotlight is an OCDQ regular segment highlighting someone you should follow—and not just Fridays on Twitter.


Phil Simon is an independent technology consultant, author, writer, and dynamic public speaker for hire, who focuses on the intersection of business and technology.  Phil is the author of three books (see below for more details) and also writes for a number of technology media outlets and sites, and hosts the podcast Technology Today.

As an independent consultant, Phil helps his clients optimize their use of technology.  Phil has cultivated over forty clients in a wide variety of industries, including health care, manufacturing, retail, education, telecommunications, and the public sector.

When not fiddling with computers, hosting podcasts, putting himself in comics, and writing, Phil enjoys English Bulldogs, tennis, golf, movies that hurt the brain, fantasy football, and progressive rock.  Phil is a particularly zealous fan of Rush, Porcupine Tree, and Dream Theater.  Anyone who reads his blog posts or books will catch many references to these bands.

 

Books by Phil Simon

My review of The New Small:

By leveraging what Phil Simon calls the Five Enablers (Cloud computing, Software-as-a-Service (SaaS), Free and open source software (FOSS), Mobility, Social technologies), small businesses no longer need to have technology as one of their core competencies, nor invest significant time and money in enabling technology, which allows them to focus on their true core competencies and truly compete against companies of all sizes.

The New Small serves as a practical guide to this brave new world of small business.

 

My review of The Next Wave of Technologies:

The constant challenge faced by organizations, large and small, which are using technology to support the ongoing management of their decision-critical information, is that the business world of information technology can never afford to remain static, but instead, must dynamically evolve and adapt, in order to protect and serve the enterprise’s continuing mission to survive and thrive in today’s highly competitive and rapidly changing marketplace.


The Next Wave of Technologies is required reading if your organization wishes to avoid common mistakes and realize the full potential of new technologies—especially before your competitors do.

 

My review of Why New Systems Fail:

Why New Systems Fail is far from a doom and gloom review of disastrous projects and failed system implementations.  Instead, this book contains numerous examples and compelling case studies, which serve as a very practical guide for how to recognize, and more importantly, overcome the common mistakes that can prevent new systems from being successful.

Phil Simon writes about these complex challenges in a clear and comprehensive style that is easily approachable and applicable to diverse audiences, both academic and professional, as well as readers with either a business or a technical orientation.

 

Blog Posts by Phil Simon

In addition to his great books, Phil is a great blogger.  For example, check out these brilliant blog posts written by Phil Simon:

 

Knights of the Data Roundtable

Phil Simon and I co-host and co-produce the wildly popular podcast Knights of the Data Roundtable, a bi-weekly data management podcast sponsored by the good folks at DataFlux, a SAS Company.

The podcast is a frank and open discussion about data quality, data integration, data governance and all things related to managing data.

 

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#FollowFriday Spotlight: @hlsdk

FollowFriday Spotlight is an OCDQ regular segment highlighting someone you should follow—and not just Fridays on Twitter.

Henrik Liliendahl Sørensen is a data quality and master data management (MDM) professional with over 30 years of experience in the information technology (IT) business working within a large range of business areas, such as government, insurance, manufacturing, membership, healthcare, and public transportation.

For more details about what Henrik has been, and is, working on, check out his My Been Done List and 2011 To Do List.

Henrik is also a charter member of the IAIDQ, and the creator of the LinkedIn Group for Data Matching for people interested in data quality and thrilled by automated data matching, deduplication, and identity resolution.

Henrik is one of the most prolific and popular data quality bloggers, regularly sharing his excellent insights about data quality, data matching, MDM, data architecture, data governance, diversity in data quality, and many other data management topics.

So check out Liliendahl on Data Quality for great blog posts written by Henrik Liliendahl Sørensen, such as these popular posts:

 

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#FollowFriday Spotlight: @DataQualityPro

FollowFriday Spotlight is an OCDQ regular segment highlighting someone you should follow—and not just Fridays on Twitter.

Links for Data Quality Pro and Dylan Jones:

Data Quality Pro, founded and maintained by Dylan Jones, is a free and independent community resource dedicated to helping data quality professionals take their career or business to the next level.  Data Quality Pro is your free expert resource providing data quality articles, webinars, forums and tutorials from the world’s leading experts, every day.

With the mission to create the most beneficial data quality resource that is freely available to members around the world, the goal of Data Quality Pro is “winning-by-sharing” and they believe that by contributing a small amount of their experience, skill or time to support other members then truly great things can be achieved.

Membership is 100% free and provides a broad range of additional content for professionals of all backgrounds and skill levels.

Check out the Best of Data Quality Pro, which includes the following great blog posts written by Dylan Jones in 2010:

 

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#FollowFriday and Re-Tweet-Worthiness

There is perhaps no better example of the peer pressure aspects of social networking than FollowFriday—the day when Twitter users recommend other users that you should follow (i.e., “I recommended you, why didn’t you recommend me?”).

However, every day of the week re-tweeting (the forwarding of another user’s Twitter status update, aka tweet) is performed.  Many bloggers (such as myself) use Twitter to promote their content by tweeting links to their new blog posts, and therefore, most re-tweets are attempts—made by the other members of the blogger’s collablogaunity—to help share meaningful content.

But I would be willing to wager that a considerable amount of re-tweeting is based on the act of reciprocity—and not based on evaluating the Re-Tweet-Worthiness of the shared content.  In other words, I believe that many people (myself included) sometimes don’t read what they re-tweet, but simply share content from a previously determined re-tweet-worthy source, or a source that they hope will reciprocate in the future (i.e., “I re-tweeted your blog post, why didn’t you re-tweet my blog post?”).

 

How do YOU determine Re-Tweet-Worthiness?

 

#FollowFriday Recommendations

By no means a comprehensive list, and listed in no particular order whatsoever, here are some great tweeps, and especially for truly re-tweet-worthy tweets about Data Quality, Data Governance, Master Data Management, and Business Intelligence:

 

PLEASE NOTE: No offense is intended to any of my tweeps not listed above.  However, if you feel that I have made a glaring omission of an obviously Twitterific Tweep, then please feel free to post a comment below and add them to the list.  Thanks!

I hope that everyone has a great FollowFriday and an even greater weekend.  See you all around the Twittersphere.

 

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#FollowFriday and The Three Tweets

Today is Friday, which for Twitter users like me, can mean only one thing . . .

It is FollowFriday—the day when Twitter users recommend other users that you should follow.  In other words, it’s the Twitter version of peer pressure: “I recommended you, why didn't you recommend me?”

So why does anyone follow anyone on Twitter?  There are many theories, mine is called . . .

 

The Three Tweets

From my perspective, there are only three kinds of tweets:

  1. Informative Tweets — Providing some form of information, or a link to it, these tweets deliver the practical knowledge or thought-provoking theories, allowing you to almost convince your boss that Twitter is a required work activity.
  2. Entertaining Tweets — Providing some form of entertainment, or a link to it, these tweets are often the funny respites thankfully disrupting the otherwise serious (or mind-numbingly boring) routine of your typical business day.
  3. Infotaining Tweets — Providing a combination of information and entertainment, or a link to it, these tweets make you think a little, laugh a little, and go on and sway (just a little) along with the music that often only you can hear.

Let’s take a look at a few examples of each one of The Three Tweets.

 

Informative Tweets

 

Entertaining Tweets

 

Infotaining Tweets

 

#FollowFriday Recommendations

By no means a comprehensive list, and listed in no particular order whatsoever, here are some great tweeps, and especially for mostly informative tweets about Data Quality, Data Governance, Master Data Management, and Business Intelligence:

 

PLEASE NOTE: No offense is intended to any of my tweeps not listed above.  However, if you feel that I have made a glaring omission of an obviously Twitterific Tweep, then please feel free to post a comment below and add them to the list.  Thanks!

I hope that everyone has a great FollowFriday and an even greater weekend.  See you all around the Twittersphere.

 

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Dilbert, Data Quality, Rabbits, and #FollowFriday

For truly comic relief, there is perhaps no better resource than Scott Adams and the Dilbert comic strip

Special thanks to Jill Wanless (aka @sheezaredhead) for tweeting this recent Dilbert comic strip, which perfectly complements one of the central themes of this blog post.

 

Data Quality: A Tail of Two Rabbits

Since this recent tweet of mine understandably caused a little bit of confusion in the Twitterverse, let me attempt to explain. 

In my recent blog post Who Framed Data Entry?, I investigated that triangle of trouble otherwise known as data, data entry, and data quality, where I explained that although high quality data can be a very powerful thing, since it’s a corporate asset that serves as a solid foundation for business success, sometimes in life, when making a critical business decision, what appears to be bad data is the only data we have—and one of the most commonly cited root causes of bad data is the data entered by people.

However, as my good friend Phil Simon facetiously commented, “there’s no such thing as a people-related data quality issue.”

And, as always, Phil is right.  All data quality issues are caused—not by people—but instead, by one of the following two rabbits:

Roger Rabbit
Roger Rabbit

Harvey Rabbit
Harvey Rabbit

Roger is the data quality trickster with the overactive sense of humor, which can easily handcuff a data quality initiative because he’s always joking around, always talking or tweeting or blogging or surfing the web.  Roger seems like he’s always distracted.  He never seems focused on what he’s supposed to be doing.  He never seems to take anything about data quality seriously at all. 

Well, I guess th-th-th-that’s all to be expected folks—after all, Roger is a cartoon rabbit, and you know how looney ‘toons can be.

As for Harvey, well, he’s a rabbit of few words, but he takes data quality seriously—he’s a bit of a perfectionist about it, actually.  Harvey is also a giant invisible rabbit who is six feet tall—well, six feet, three and a half inches tall, to be complete and accurate.

Harvey and I sit in bars . . . have a drink or two . . . play the jukebox.  And soon, all the other so-called data quality practitioners turn toward us and smile.  And they’re saying, “We don’t know anything about your data, mister, but you’re a very nice fella.” 

Harvey and I warm ourselves in these golden moments.  We’ve entered a bar as lonely strangers without any friends . . . but then we have new friends . . . and they sit with us . . . and they drink with us . . . and they talk to us about their data quality problems. 

They tell us about big terrible things they’ve done to data and big wonderful things they’ll do with their new data quality tools. 

They tell us all about their data hopes and their data regrets, and they tell us all about their golden copies and their data defects.  All very large, because nobody ever brings anything small into a data quality discussion at a bar.  And then I introduce them to Harvey . . . and he’s bigger and grander than anything that anybody’s data quality tool has ever done for me or my data.

And when they leave . . . they leave impressed.  Now, it’s true . . . yes, it’s true that the same people seldom come back, but that’s just data quality envy . . . there’s a little bit of data quality envy in even the very best of us so-called data quality practitioners.

Well, thank you Harvey!  I always enjoy your company too. 

But, you know Harvey, maybe Roger has a point after all.  Maybe the most important thing is to always maintain our sense of humor about data quality.  Like Roger always says—yes, Harvey, Roger always says because Roger never shuts up—Roger says:

“A laugh can be a very powerful thing.  Why, sometimes in life, it’s the only weapon we have.”

Really great non-rabbits to follow on Twitter

Since this blog post was published on a Friday, which for Twitter users like me means it’s FollowFriday, I would like to conclude by providing a brief list of some really great non-rabbits to follow on Twitter.

(Please Note: This is by no means a comprehensive list, is listed in no particular order whatsoever, and no offense is intended to any of my tweeps not listed below.  I hope that everyone has a great #FollowFriday and an even greater weekend.)

 

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Twitter, Meaningful Conversations, and #FollowFriday

In social media, one of the most common features of social networking services is allowing users to share brief status updates.  Twitter is currently built on only this feature and uses status updates (referred to as tweets) that are limited to a maximum of 140 characters, which creates a rather pithy platform that many people argue is incompatible with meaningful communication.

Although I use Twitter for a variety of reasons, one of them is sharing quotes that I find thought-provoking.  For example:

 

This George Santayana quote was shared by James Geary, whom I follow on Twitter because he uses his account to provide the “recommended daily dose of aphorisms.”  My re-tweet (i.e., “forwarding” of another user’s status update) triggered the following meaningful conversation with Augusto Albeghi, the founder of StraySoft who is known as @Stray__Cat on Twitter:

 

Now of course, I realize that what exactly constitutes a “meaningful conversation” is debatable regardless of the format.

Therefore, let me first provide my definition, which is comprised of the following three simple requirements:

  1. At least two people discussing a topic, which is of interest to all parties involved
  2. Allowing all parties involved to have an equal chance to speak (or otherwise share their thoughts)
  3. Attentively listening to the current speaker—as opposed to merely waiting for your turn to speak

Next, let’s examine why Twitter’s format can be somewhat advantageous to satisfying these requirements:

  1. Although many (if not most) tweets are not necessarily attempting to start a conversation, at the very least they do provide a possible topic for any interested parties
  2. Everyone involved has an equal chance to speak, but time lags and multiple simultaneous speakers can occur, which in all fairness can happen in any other format
  3. Tweets provide somewhat of a running transcript (again, time lags can occur) for the conversation, making it easier to “listen” to the other speaker (or speakers)

Now, let’s address the most common objection to Twitter being used as a conversation medium:

“How can you have a meaningful conversation when constrained to only 140 characters at a time?”

I admit to being a long-winded talker or, as a favorite (canceled) television show would say, “conversationally anal-retentive.”  In the past (slightly less now), I was also known for e-mail messages even Leo Tolstoy would declare to be far too long.

However, I wholeheartedly agree with Jennifer Blanchard, who explained how Twitter makes you a better writer.  When forced to be concise, you have to focus on exactly what you want to say, using as few words as possible.

I call this reduction of your message to its bare essence—the power of pith.  In order to engage in truly meaning conversations, this is a required skill we all must master, and not just for tweeting—but Twitter does provide a great practice environment.

 

At least that’s my 140 characters worth on this common debate—well okay, it’s more like my 5,000 characters worth.

 

Great folks to follow on Twitter

Since this blog post was published on a Friday, which for Twitter users like me means it’s FollowFriday, I would like to conclude by providing a brief list of some great folks to follow on Twitter. 

Although by no means a comprehensive list, and listed in no particular order whatsoever, here are some great tweeps, and especially if you are interested in Data Quality, Data Governance, Master Data Management, and Business Intelligence:

 

PLEASE NOTE: No offense is intended to any of my tweeps not listed above.  However, if you feel that I have made a glaring omission of an obviously Twitterific Tweep, then please feel free to post a comment below and add them to the list.  Thanks!

I hope that everyone has a great FollowFriday and an even greater weekend.  See you all around the Twittersphere.

 

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The Fellowship of #FollowFriday

During the dawn of the Second Age of Digital-Earth, in the land of Twitter there was formed a group of like-minded tweeps who were well known for their wisdom about Data Quality, Data Governance, Master Data Management, and Business Intelligence.

They battled against the dark forces of poor data quality, undisciplined organizations, multiple conflicting versions of the truth, flawed business decisions, vast boiling oceans of unmanaged data assets, uncontrolled costs, and unmitigated compliance risks.

Collectively, these valiant heroes were known as: The Fellowship of FollowFriday.

Okay, so clearly I am a total dork—geek, nerd, and dweeb are also completely acceptable alternatives.

J. R. R. Tolkien's The Lord of the Rings three-volume book and Peter Jackson’s adapted movie trilogy were awe inspiring epics, and also the theme of this blog post about FollowFriday, the weekly tradition of recommending great folks to follow on Twitter.

Please note that simply for the purposes of organizing the following lists, I have made the United States the kingdom of Gondor, Canada the kingdom of Rohan, and all of Europe collectively The Shire.  No offense intended to my tweeps from other lands.

I hope that everyone has a great FollowFriday and an even greater weekend.  See you all around the Twittersphere.

 

Tweeps of Gondor

 

Tweeps of Rohan

 

Tweeps of The Shire

 

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Video: Twitter #FollowFriday – January 15, 2010

In this OCDQ Video, I broadcast (from within The Tweet-rix) my Twitter FollowFriday recommendations for January 15, 2010.

 

If you are having trouble viewing this video, then you can watch it on Vimeo by clicking on this link: OCDQ Video

 

Tweeps mentioned in the video:

 

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