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Intelligence. This blog provides me (and others on occasion) with a venue for ideas and opinions
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limited in length, scope, or development to require the larger venue.
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April 11th, 2015
Sometimes in life the fates attack from all sides and leave us heaving for breath, overwhelmed. The last few months have been such a period for me. So much that’s been happening in my personal life has been nuts—the product of idiocy, incompetence, and at times pure meanness. A few days ago, in utter frustration I exclaimed, “I want to live in a world that makes sense.” Wouldn’t that be wonderful? To live in a world that works according to thoughtful and compassionate principles. Brainless bureaucracies would be a thing of the past. People who complicate our lives through incompetence or pettiness would suddenly grow up and give a damn. Systems that have developed to promote the interests of some to the detriment of others would be torn asunder. To the degree that natural inequities still exist, we could balance the playing field by identifying the causes and addressing them. The world wouldn’t be perfect, but we could address life’s problems thoughtfully and compassionately.
As I was thinking this, it occurred to me that this wish might be common among people who, like me, work to make sense of data. Perhaps we’re drawn to data sensemaking because we long for a sensible world, and this is our attempt to create a bit more order in the midst of chaos. I meet many fellow data sensemakers in my work and, based on the fine and dedicated people who attend my courses and read my books, I suspect that this correlation is real. If we pair this desire with the right skills and tools to make better sense of the world, we can use that knowledge to make the world a more sensible place. This dream is too precious to fritter away. The signals that live in our data are too precious to miss in the midst of deafening noise. Let’s focus our vision and double our effort. Let’s turn down the noise.
March 17th, 2015
The number of viable visual data exploration and analysis tools can be counted on the fingers of one hand. TIBCO Spotfire is among them. The merits of this product are undermined, however, by the irresponsible ways that TIBCO is currently promoting it. A new marketing campaign by TIBCO illustrates what happens when marketing professionals who either don’t understand analytics or care little for the truth are allowed free rein.
Here are a few lines from TIBCO Spotfire’s new “Finally…Answers Made Easy” campaign (emphasis mine), supposedly written by the company’s CTO, Matt Quinn:
At TIBCO, we believe just visualizing data isn’t enough. Embedded deep in the brains of data scientists lies a knowledge set that can truly benefit any one of us who has ever struggled with the dilemma of which graph to choose for a given data set. How many times have you highlighted a data set in Excel, selected Insert Chart and ended up with nonsense? You try a different chart, play with the axes, change the numerous options – before you know it, you’ve wasted an hour and haven’t made any progress. You certainly haven’t gotten anywhere near insight or understanding. Imagine if your software knew what you needed to see, even if you didn’t?
We have mined the data in the data scientists’ brains and shared what they know about visualizations: all the arcane rules about using measures on density plots, when to use aggregations and how to use time series correctly. Spotfire will automatically examine your data and recommend the best visualizations for it. Allowing our algorithm to choose the correct visualization will let you focus on what you know best – your business.
When you took your driving test, they didn’t ask you to explain the principles of the internal combustion engine – you just trust it works. Whereas your grandparents may have been a dab hand with a spanner and an oil can, life has moved on. So it will be for the future of analytics – it will work smarter, so you don’t have to.
Similar to Tableau, Spotfire attempts to determine an appropriate chart based on the data that you’ve selected. This is a useful time saver when it’s done well, but it can’t peek into your mind to determine what you want to see, so its guesses are frequently wrong. This feature can also serve as a useful guide for data analysis novices, but in this potential also lies the problem: you can’t let software do your thinking for you. The big lie that’s being told here appears in the last few words: “It will work smarter, so you won’t have to.” This is not only a lie—it’s a dangerous lie that keeps organizations trapped in ignorance, wasting their time, unable to tap into the value of their data.
Well-designed software can indeed help you “work smarter,” but not “so you won’t have to” work smart yourself. Data exploration and analysis software, no matter how good it is, cannot provide a workaround for your lack of analytical skill. Software vendors hurt you and ultimately hurt themselves when they claim that their products can be used effectively without the requisite analytical skills. They hurt themselves because, when customers learn that they were sold a lie and can’t actually use the software effectively, they become disgruntled and eventually move on to another product. Sadly, they rarely make a better choice the next time around, and the doomed process begins anew. No one wants to believe that a product that they spent a great deal of money to buy won’t solve their problems.
This marketing lie is in line with the “self-service BI” lie that’s been told for ages. The notion that BI software can auto-magically enable people without analytical skills to make sense of data is ludicrous, yet it’s an appealing lie. We want something for nothing, but the world doesn’t work this way. Analytical tools can’t help us do better and faster what we don’t already know how to do ourselves. It can only augment our intelligence—extend our reach and help us work around limitations—never replace our need for intelligence and skill.
TIBCO is certainly not alone in its willingness to spread misinformation in its attempts to sell its products. Every one of the viable visual data exploration and analysis software vendors have played fast and loose with the truth and mislead potential buyers to varying degrees. Most of the wannabe (i.e., not viable) vendors in the space are even worse.
I suspect that the first vendor in the analytics space that’s willing to tell the truth about its product and what’s required to use it will eventually lead the market, assuming that its product is good, even though they’ll lose many sales in the process. A vendor could differentiate itself from the pack by being truthful. The people who spend their days trying to make sense of data tend to respect truth. They’d find it refreshing to witness honesty coming from a software vendor. This vendor could honestly say, “Here’s the good news. The skills needed to analyze data can be learned by any reasonably intelligent person, given the right resources and enough practice.” This is indeed good news, but it’s not as sexy as the claim that a software product can replace the need for skill.
Damn, damn, damn…getting value from data requires skill and effort. After all of these years of trying and failing to get value from data without paying our dues, why are we still so willing to believe otherwise? There are no shortcuts to enlightenment.
January 6th, 2015
Perhaps you’ve noticed that I didn’t write a year-in-review blog post about 2014, extolling the wonderful progress that we made and predicting the even-more-wonderful breakthroughs that we’ll make in 2015. That’s because, in the field of data sensemaking and presentation in general and data visualization in particular, we didn’t make any noticeable progress last year, despite grand claims by vendors and so-called thought leaders in the field. Since the advent of the computer (and before that the printing press, and before that writing, and before that language), data has always been BIG, and Data Science has existed at least since the time of Kepler. Something did happen last year that is noteworthy, however, but it isn’t praiseworthy: many organizations around the world invested heavily in information technologies that they either don’t need or don’t have the skills to use.
I know that during the last year many skilled data sensemakers used their talents to find important signals in data that made a difference to their organizations. Smart, dedicated, and properly skilled people will always manage to do good work, despite the limitations of their tools and the naiveté of their organizations. I don’t mean to diminish these small pockets of progress in the least. I just want data sensemaking progress to become more widespread, less of an exception to the norm.
Data sensemaking is hard work. It involves intelligence, discipline, and skill. What organizations must do to use data more effectively doesn’t come in a magical product and cannot be expressed as a marketing campaign with a catchy name, such as Big Data or Data Science.
Dammit! This is not the answer that people want to hear. We’re lazy. We want the world to be served up as a McDonald’s Happy Meal. We want answers at the click of a button. The problem with these expectations, however, is not only that they’re unrealistic, but also that they describe a world that only idiots could endure. Using and developing our brains is what we evolved to do better than any other animal. Learning can be ecstatic.
Most of you who read this blog already know this. I’m preaching to the choir, I suppose, but I keep hoping that, with enough time and effort, the word will spread. A better world can only be built on better decisions. Better decisions can only be made with better understanding. Better understanding can only be achieved by thoughtfully and skillfully sifting through information about the world. Isn’t it time that we abandoned our magical thinking and got to work?
January 5th, 2015
This blog entry was written by Bryan Pierce of Perceptual Edge.
It’s just over one week until Stephen will be teaching his new advanced course Signal: Understanding What Matters in a World of Noise in Berkeley, CA on January 13–14. If you’re interested in attending, there are still some seats available. We look forward to seeing you in Berkeley!
December 16th, 2014
This blog entry was written by Bryan Pierce of Perceptual Edge.
In 2015, Stephen Few will offer different combinations of five data visualization courses at public workshops around the world. He’ll teach his three introductory courses, Show Me the Numbers: Table and Graph Design (now as a two-day course, with additional content and several more small-group exercises and discussions), Information Dashboard Design, and Now You See It: Visual Data Analysis. He’s also introducing two new advanced courses for people who have already attended the prerequisite introductory courses or read the associated books and are looking to hone their skills further: Signal: Understanding What Matters in a World of Noise and Advanced Dashboard Design.
Stephen will teach the following public workshops in 2015:
- Berkeley, California on Jan 13 – 14: Signal: Understanding What Matters in a World of Noise
Berkeley, California on Jan 27 – 29: Advanced Dashboard Design (Sold Out!)
- Copenhagen, Denmark on Feb 24 – 26: Show Me the Numbers: Table and Graph Design and Now You See It: Visual Data Analysis
- London, U.K. on Mar 2 – 3: Show Me the Numbers: Table and Graph Design
- London, U.K. on Mar 4 – 6: Advanced Dashboard Design
- Sydney, Australia on Mar 23 – 24: Signal: Understanding What Matters in a World of Noise
- Sydney, Australia on Mar 25 – 27: Advanced Dashboard Design
- Stockholm, Sweden on Apr 21 – 23: Show Me the Numbers: Table and Graph Design and Information Dashboard Design
- Portsmouth, Virginia on Apr 28 – 30: Show Me the Numbers: Table and Graph Design and Now You See It: Visual Data Analysis
- Soest, Netherlands on May 6 – 8: Show Me the Numbers: Table and Graph Design and Information Dashboard Design
- Soest, Netherlands on May 11 – 12: Signal: Understanding What Matters in a World of Noise
- Minneapolis, Minnesota on Jun 2 – 4: Show Me the Numbers: Table and Graph Design and Information Dashboard Design
- Portland, Oregon on Sep 22 – 24: Show Me the Numbers: Table and Graph Design and Information Dashboard Design
- Dublin, Ireland on Oct 6 – 8: Show Me the Numbers: Table and Graph Design and Now You See It: Visual Data Analysis
- Wellington, New Zealand on Nov 4 – 6: Show Me the Numbers: Table and Graph Design and Information Dashboard Design (Registration not yet open)
- Sydney, Australia on Nov 11 – 13: Show Me the Numbers: Table and Graph Design and Now You See It: Visual Data Analysis (Registration not yet open)
These workshops are a great way to learn the data visualization principles that Stephen teaches in his books.