Friday, 22 of February of 2019

Category » Management

Data mining book on the horizon…

Watch for a Spring 2014 release for this new data mining book. I wrote a section devoted to text analytics.

Right now, the title on the description, the title on the image, and the title I have from the editor are all different. And you won’t see me or the other coauthors in the description. Nor are the details of the contents here yet. Hope they’ll get that all sorted out by Spring!

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Be a Text Analytics Heretic

New piece on SmartData Collective:

Be a Text Analytics Heretic

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What Big Data Success Stories and Barbie Have in Common

New article on All Analytics. What Big-Data Stories & Barbie Have in Common

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The FTC will change the way you do business

New piece on All Analytics:

FTC & the Data Brokers: Why You Should Care

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Lauren Bacon is really on the money

Once And For All: Tech is Not a Meritocracy, a recent post by Lauren Bacon, is really on the money. A lot goes into the mix that leads to success in industry, and the loose collection of things we call “merit” are only a bit of that mix.

It’s hard to imagine that anyone would believe otherwise. Consider a few of the people you know who are in positions of power and influence. Are they all fireballs of talent? Does each and every one seem to be the best person for the job? Don’t you also know many people whose jobs seem unworthy of their merits?

Lauren’s post focuses on biases – unrealistic views of ourselves, as well as others, that stand in the way of progress for women and others. She points out that we must recognize the existence of unconscious bias as well as overt discrimination.

Ian Muir responded with a question – what can allies be doing to help? Lauren says she intends to write about that, and I’m looking forward to reading what she has to say! In the meanwhile, let me make a few suggestions of my own.

Every day, each of us has the opportunity to do a little something to help others advance in their professions. If you simply make a point of doing one thing each day for someone in a group that is underrepresented in tech, it will add up to a lot over time. Don’t think you have to be a big shot to make a difference. Every bit helps, and little each day helps a whole lot.

Let me start with an example. Do you know of a conference that is coming up, one that is a good showcase for the speakers and a worthwhile networking venue? Do you also know someone – perhaps a woman or an African American who is not [yet] well known- who would be a good presenter? What can you do to help get that person on the platform? Don’t just say, “Hey, so and so, you ought to apply.” That’s not what the good ‘ol boy network does, and we have a lot to learn from the good ‘ol boys. Instead, call the conference organizers, and plug that person. Do what you can to get them motivated to call your colleague and invite her or him to present.

Taking the conference theme a little farther, next time you are thinking about a conference – look over the list of speakers and take note of the level of diversity. If it isn’t what it should be (for example, 25% of the people in tech are women, so 10% female speakers should set off your bullshit* detector. Try suggesting some qualified speakers. If that doesn’t work, make noise about the problem in public – write a blog post, tweet, put the word on the street. Use whatever channels you like, but call them on it, and do it in public.

The next day, do another thing.

Need ideas? Here are a few. I hope you’ll respond not only by doing some of these, but also by posting some suggestions of your own.

More things you can do to help others advance [I’m going to say women here, but of course, this isn’t just for women]:

    Encourage your local professional group to showcase women speakers, especially new speakers, and to place women into chapter office and key committee positions

    When somebody’s hiring, suggest a women for the job

    Ask others to inform you about talented women they know, or know about

    Ask women what kind of help they need. If you can’t provide that help yourself, look into your network – perhaps you have a contact who can.

    Prepare yourself to call others out when you hear false statements. This might mean emotional preparation, getting ready to disagree with someone in public, or research, such as learning a few relevant statistics, or other facts, that will help to make your point.

    Read a good article written by a woman? Share it with others.

    Maybe you know someone who has every advantage in the world already. He still needs help. Do you know a woman who can help him? Make the introduction! People appreciate those who help them, and often return the favor.

    Don’t let anybody convince you that it isn’t your business to help. Yes, there are people so small and so stupid that they will try to do that. If you encounter such nonsense, just shake the sand out of your shoes and move on.

*[with apologies to]

[bool-shit] noun, verb, interjection Slang: Vulgar.
unconscious bias.
verb (used with object)
conscious bias
verb (used with object)
3.something rotten

1910–15; bull1 (perhaps reinforced by bull3 ) + shit

Related forms
bull•shit•ter, noun


Do data scientists really need IT? Yes!

My post, Kiss & Make Up With IT (, has kicked up a lot of discussion.

One reader asks “Do data scientists really need IT?” He thinks not. He’s dead wrong. You can read the article and discussion on All Analytics. Here is a bit about why it is important for data analysts to work constructively with IT:

Let’s consider what data analysts in corporations are expected to do. It is their responsibility to provide corporate management with information that supports decision making. These executives are empowered, and obligated, to manage the business in the interest of shareholders, and within the law.

The most relevant data to any business is internal data. This data is the private property of the business, and not available through any other source. The responsibility for maintaining and controlling such data falls to the IT organization within the business. This is no trivial matter. There are significant legal and financial concerns tied to the handling of data.

If the data is properly managed, there will be no route to obtain it other than through the proper channels, and those channels are controlled by the IT organization. This is not merely the way data is managed in the business world. Nonprofits and government agencies use similar processes.

I have encountered many data analysts over the years who resorted to any means they could devise to avoid dealing with IT. They often get away with this, because their results are viewed only by their own sympathetic team members and by executives who do not question them on matters of data management. That is, they get away with it until the work comes under serious scrutiny. That scrutiny commonly happens when the business becomes involved in a lawsuit or other legal action, or when a new manager enters the business asking questions and taking no prisoners.

Early in my career, I discovered an issue with some of the data that I and my team depended on. My manager was unwilling to take action to correct the problem. There was a loud public shouting match between us over that. But the problem got fixed in the end. Why? Because an auditor came in to examine our records, spotted the issue and brought it to the attention of upper management.

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Kiss and Make Up with IT

New post on All Analytics today.

Kiss and Make Up with IT

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Secrets of a Software Vendor

New piece on All Analytics today: Secrets of a Software Vendor

Think of it as “True Confessions” for the industry.

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The other 16%

Phil Simon commented on my piece, Gut Feel Isn’t Good Enough,, and he included a link to his article, Seinfeld, Data and the Other 16 Percent His piece is a good one, and you ought to read it. You may not agree with all of his thoughts – I don’t – but his heart is in the right place, and the material is all good food for thought. What follows is my response to Mr. Simon.

What bad news! And yet, I have reason to believe the picture is even worse than you think.

Remember, what you’ve got in that infographic is the results of a survey. If this were behavioral data, the picture would look a lot worse. Some of those who say that data helps aren’t really using data at all, others aren’t using it consistently. Few are using it well.

So, is this an old-guard problem? In my experience, while some older execs have gotten by without analytics and don’t care, many others, especially in direct marketing, retail and advertising, know better. I would say that use of analytics in marketing has actually declined over the past few decades – this is not an old-guard problem that will just correct itself as a new crop of execs comes in.

While there are showpiece organizations like Amazon, Groupon and Netflix who have built analytics into their culture from the start, many others are unaware and uninterested. And many are interested in analytics, but aren’t good at it!

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Takeaways from Obama’s analytics team

I attended a talk by some of the folks from the Obama campaign’s analytics team Wednesday night. They discussed the use of testing on elements of their email and website designs. So much of what they described applies to everyone using these channels for communication, whether in a commerical, political or other context. A few takeaways:

  • Test every element of a form, including those which are not on-page. They found that using a design that loaded quickly (60% more quickly than the alternative) yielded a 14% lift in contributions.
  • Test on samples before deciding which version to present to a large list. One subject line test showed a wide range of predicted contribution levels – from $400,000 to $2.5 million. They went with the best and the result was over $2.6 million in contributions.
  • Ugly often wins. They found that ugly yellow highlights and “old-school” links often outperformed other alternatives. (Sorry, designers. Direct marketers have been aware of that for a long time – that’s why your junk mail is sooo ugly.)

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