Can Data Quality avoid the Dustbin of History?

After reading two blog posts about the 2011 predictions for data management by Steve Sarsfield and Henrik Liliendahl Sørensen, I was pondering writing a 2011 prediction post of my own—and then I read this recent Dilbert comic strip.

What if Dogbert is right and the only things that matter are social networks, games, and phones?  What implications does this have for the data management industry, and more specifically, the data quality profession?  How can data quality practitioners avoid being cast into the Dustbin of History in 2011 and beyond?

Perhaps we need to create a social network for data?  Let’s call it DataTweetBook.  Although we would be allowed to follow any data with a public profile, data would have to approve our friend requests—you know, in order to respect data’s privacy.

(Quick Side Bar Question: Do you think that your organization’s data would accept your friend request—or block you?)

Next, we would partner with Zynga and create DataVille and Data Quality Wars, which would be online games exclusive to the DataTweetBook platform.  These games would include fun challenges, like “consolidate duplicates in your contact database” and “design a user interface that prevents data quality issues from happening.”  You and your data can even ask other people and data in your social network for help with completing tasks, such as “ask postal reference data to validate your mailing addresses.”

Of course, we would then need to create iPhone and Android apps for DataTweetBook, DataVille, and Data Quality Wars, so that everyone can access the new social network and games on their mobile phones.  And eventually, we would start a bidding war between Apple and Google over the exclusive rights to make an integrated mobile device, either iDataPad or DataGoogler.

So that’s my 2011 prognostication for the data quality industry—it’s going be all about social networks, games, and phones.

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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

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.)

Henrik Liliendahl Sørensen – @hlsdk Dylan Jones – @DataQualityPro Phil Simon – @PhilSimon Gordon Hamilton – @DQStudent Julian Schwarzenbach – @jschwa1 Rich Murnane – @murnane Mark Horseman – @MarkHorseman Graham Rhind – @GrahamRhind Rob Paller – @RobPaller Stephen Putman – @SJPutman Prashanta Chandramohan – @ColdPC Ken O’Connor – @KenOConnorData William Sharp – @dqchronicle Augusto Albeghi – @Stray__Cat Jill Wanless – @sheezaredhead Jacqueline Roberts – @JackieMRoberts Terri Rylander – @BIMarcom Loraine Lawson – @LoraineLawson Sarah Burnett – @SarahBurnett Corinna Martinez – @Futureratti Beth Breidenbach – @bbreidenbach Julie Hunt – @juliebhunt Nicola Askham – @Nicola_Askham Teresa Cottam – @Teresacottam Loretta Mahon Smith – @silverdata April Reeve – @Datagrrl Karen Lopez – @datachick Rob Drysdale – @projmgr Ted Louie – @TedLouie John Owens – @JohnIMM Dalton Cervo – @dcervo Phil Wright – @faropress Jaime Fitzgerald – @jaimefitzgerald Simon Daniels – @mktginsightguy Ajay Ohri – @decisionstats Marcus Borba – @marcusborba Alexej Freund – @alexej_freund Vish Agashe – @VishAgashe Jean-Michel Franco – @jmichel_franco Chris Sorensen – @wjdataguy Mark Lorion – @mark_lorion Brett Stupakevich – @Brett2point0 Steve Dine – @steve_dine Doug Newdick – @dougnewdick Garnie Bolling – @GarnieBolling Jarrett Goldfedder – @JGoldfed David Pratt – @DataMgmtWonk Benjamin Wolfe – @BenjaminWolfe Nick Giuliano – @Nick_Giuliano Ina Mutschelknaus – @InaSAP Lyndsay Wise – @wiseanalytics Kelle O’Neal – @FirstSanFranMDM Tamara Dull – @tamaradull Nicole Carriere – @carrni Robin Stehlik – @RobinPStehlik Giedre Aleknonyte – @googlea Natalie Eschen – @NatalieEschen

IAIDQ – @IAIDQ Daragh O Brien – @daraghobrien Jill Dyché – @JillDyche David Loshin – @DavidLoshin Neil Raden – @NeilRaden James Taylor – @jamet123 Shawn Rogers – @shawnrog Wayne Eckerson – @weckerson Peter Thomas – @PeterJThomas Timo Elliott – @TimoElliott Dan Power – @dan_power William McKnight – @williammcknight Gwen Thomas – @gwenthomasdgi Claudia Imhoff – @Claudia_Imhoff Gartner Research – @Gartner_inc Ted Friedman – @ted_friedman Andy Bitterer – @bitterer ANALYSTerical – @ANALYSTerical Merv Adrian – @merv Forrester Research – @forrester Robert Karel – @rbkarel Initiate, an IBM Company – @IBMInitiate DataFlux, a SAS Company – @DataFlux Data Roundtable – @DataRoundtable Kalido – @Kalido Bill Hewitt – @Kalido_CEO John Evans – @jmevans00 Lorita Ba Vannah – @lorita Informatica – @InformaticaCorp Clarke Patterson – @ClarkePatterson Talend – @Talend Steve Sarsfield – @SteveSarsfield Trillium Software – @TrilliumSW Michele Goetz – @mlgoetz Pervasive Software – @DataIntegrate Paige Roberts – @RobertsPaige Experian QAS – @Experian_QAS Datamartist – @Datamartist Utopia, Inc. – @UtopiaInc Melissa Data – @MelissaData Ira Warren Whiteside – @irawhiteside DataMentors – @DataMentors Enterworks – @enterworks Fergus Cloughley – @Master_OBASHI Match2Lists – @Match2Lists MIKE2.0 – @OpenMethodology Information Management – @InfoMgmt Tony Carrini – @TonyCarrini Julie Langenkamp – @JulieLangenkamp Jim Ericson – @JimEricson Eric Kavanagh – @Eric_Kavanagh Justin Kern – @IMJustinKern Valerie Valentine – @ValValentineIM Enterprise CIO Forum – @ECIOForum HPinstantOn – @HPinstantOn John Dodge – @Thedodgeretort Paul Calento – @pcalento

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Social Karma (Part 7)

Comic Relief: Dilbert on Project Management

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

Since I don’t read newspapers very often (does anyone anymore?), nowadays I get my Dilbert fix online.  However, I don’t always find the time to read the comic strip on a regular basis.  Therefore, I catch up by reading several weeks of it all at once. 

I like to find one or more recurring themes (which is very easy to do with Scott Adams) and then share some of my favorites.

Today’s blog post provides some recent Dilbert Views on the wonderful world of project management.  Enjoy!

Dilbert on Project Management

The first step in project management is proper planning, which starts by selecting a good acronym:

The next step is to properly establish realistic estimates for the primary tasks in the project plan:

Of course, the most important resource allocation is the project leader, so you must choose wisely:

Finalizing the delivery date can involve some tricky math, it’s much easier to just add more resources:

However if simply adding additional resources won’t really help, there is always an alternative approach:

 

Once it becomes impossible to meet the project’s carefully determined deadline, you know what must be done:

But fear not, your project can be brought to a graceful conclusion following this standard best practice:

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Comic Relief: Dilbert to the Rescue

Comic Relief: Dilbert to the Rescue

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

Therefore, today's blog post simply provides some Dilbert Views on the following topics:

• Enterprise Architecture

• Strategic Planning

• Collaboration

• Consultants

Enterprise Architecture

Strategic Planning

Collaboration

Consultants