I love getting to see new technologies changing the world. The opening of the new Vancouver Microsoft Canada Excellence Centre included prominent Microsoft and Canadian leaders, including our Geek Prime Minister. Take a few minutes to see how all my favourite buzzwords come together:
Microsoft + my Canadian BF + Jobs + Deep Learning + AI + Machine Learning + Investing + Accessibility + YVR + SEA + Innovation + Prime Minister "knows how to code already" + Geek + Big news for Canada
This sort of “making a difference” is why I keep getting out of bed in the morning.
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:
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?
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:
- 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.
- 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.
- Why do some bars have signed numbers and one have a range? Why are some numbers unsigned? Even some delta numbers are unsigned.
- 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.
- Where numbers appear, do they describe the section they are on or the section next to the number? I’m not sure
- What does the relative position of the blue section mean? I’m not sure.
- Why are some of the labels in light grey and some in dark grey? I’m not sure
- 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.
- 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.
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.
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?
- The best data analysis can be invalidated with bad data visualizations.
- 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.
- 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.
- 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.
- Choose the right chart type to fit your data. Then use that chart correctly.
- If you needs a graphic image, don’t mimic a recognized chart type.
- 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.
- 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.
- If a chart leaves viewers saying “I’m not sure” more than once, it’s not working.
- 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.
If you think about it, interviewing, on both sides of the desk, is a lot like online dating. You have a profile (your resume and LinkedIn profile) and the company has a profile (annual reports, online databases) and both of you are matched up via those profiles. Sometimes it’s done via a computer algorithm (online sites), sometimes you have a matchmaker (agency).
This past weekend my friend Thomas LaRock ( blog | @sqlrockstar ) and I presented on 10 Things I Hate About Interviewing with You at SQLSaturday San Diego. We drew upon that analogy to talk about the myths and missteps that people make while being the interviewer and interviewee. You can download the slides in my document library, but I wanted to share the 10 Tips and the additional resources we gave.
10 Tips for Better Interviewing
1. Do your homework
Your job in an interview is to come across as smart and confident. There are things you need to do to get ready. Having read the resume and the company profiles is just one important step.
2. Study the resume & job posting
You don’t want to be reviewing the resume or the job posting as you are interviewing. You won’t be able to think of great questions or to listen while answers are being given.
3. Have a plan, but be prepared to detour
All that prep is good, but you need to be able to come up with questions and answers if the interview starts heading in a different direction. I once interviewed for a project, only to have the interviewer realize that I was a better fit for a much higher role and project. That meant more money and a better gig.
4. Ask real questions
We give a list of some of the interviewer questions we think have proven to be trite, tired and nearly useless. Let’s just say they involve mirrors and kryptonite.
5. Listen, then ask follow up questions
It kills me to see an interviewer asking questions but not really processing them; they might as well be a webform recording my responses. And I’ve seen interviewees give responses to questions, even crazy questions, and not ask any follow ups or ask context-seeking questions. That says to me they aren’t really “there” in the interview.
6. Be engaging and sincere, even if you have to fake it
It really hurts to see an interviewee be flat and less than passionate about what they do. It know interviewing is stressful and nerves get in the way. But to fail at being engaging comes across as flat.
7. Your job is to sell, without being salesy
Never rate yourself as 11 out of 10 or to say you know everything. Interviewers don’t actually like overconfidence. There needs to be a few “it depends” discussions and a few “I don’t knows” if the interview questions are good. On the other side of the desk, an interviewer that spends more time selling the company or the project might be desperate for a resource for reasons you don’t want them to be.
8. Show humility, but don’t downplay your strengths
Be yourself. Admit to when you don’t know something. But don’t downplay your knowledge or skills. And ladies, we are really bad about doing this. Some guys, too, I know. But ladies, seriously. Take credit for what you know and the successes you’ve had. Other candidates are telling the interviewers that they the only person on the planet that can be successful in this job. You need to rate strong.
9. Follow up if you promised to do something
If you promised to send references or more details about your background, or even to share a book title you really liked, do it. Even if you don’t make it for this job, you’ll want a great reason to keep your name in front of that interviewer. Interviewers, if you promised to seen updates about the status of the process, do it or don’t make the promise.
10. Be willing help each other, even if there isn’t a good fit
If you find out during the interview that the job isn’t for you, that’s not a fail. If you know someone who might fit, forward along the information to them. That’s a win for everyone. Don’t hoard job opportunities.
I’ve included some background on each of these, but to get the good discussion stories behind these, you’ll need to attend one of our future presentations of this. We have one story about the importance of your interviewers not needing to know the status of your underwear, too. It’s not all do’s and don’ts
Just a few of the resources I recommend for interviewing and being interviewed.
•…plus many more….
A couple of months ago I talked about Project Parabola – It’s Reorg Season. The project is basically concluded, and not surprisingly, resulted in a small number of layoffs. In a really sad situation an employee walked over to my cube and asked if I had a plastic bag or a box—at first I thought he was joking, but then quickly realized he wasn’t joking. I have to say: watching this was really painful, and frankly, his manager should had a box ready for all of his stuff. That was particularly crappy.
As part of Project Parabola, a small number of employees were let go—they got a basic severance package of a week of salary for each year they worked for the company, along with their vacation pay. Additionally, they get the use of an outplacement service, (I’ll talk more about this later). So how can you prepare for a layoff?
- Always be looking—never stop looking for jobs. Your company doesn’t care about you (seriously no box?) so why should you be loyal to them? I’m not implying you should job hop—but talk to
human traffickersrecruiters (I love the good ones, I really do), and see what’s going on. By all means, if you see something that looks interesting to you, wrangle your way into an interview for it.
- Keep your resume/CVs up to date and tailor them to the specific job description you are applying for. Notice that I have used plural forms there? Yes, it’s fine to have resumes tailored to specific types of jobs. In fact, it’s a good thing.
- Network with others NOW, not when you need a job. By networking, I don’t mean handing out business cards. I mean building relationships with people. You don’t have be BFFs, but you do need to know people well enough to ask them for a favour, later.
- Join user groups and participate in them. Attend some meetings. Most user group meetings are free. Take advantage of that. My mantra is NetworkToGetWork. Remember that.
- Participate in social media, even if you can do it only on a limited basis. Your reach is so much larger there. Still do local, in-person networking, but don’t ignore the virtual opportunities.
- Update LinkedIn—make sure your skills and profile are up to date. Don’t wait to do this when you need it. Do it now. In fact, in my presentations on Career Management for Data Professionals, I tell people to set a reminder to update their profile monthly. Not only does this keep your profile up to date, it notifies people in your network that something has changed. That gets your name in front of them on a regular basis. Regular updates also have the benefit of not signalling your boss that you might be looking for a job.
- Help people now, not when you need help. In addition to building a network you should have a reputation of helping others. I don’t mean just offering to help, but spending time to give others advice, write a helpful blog post, answer an email or to give someone a ride to a SQL Saturday or DAMA event. Note: I may have had assistance in writing this post. Thank you, anonymous helper. If you ever need a job, you are on my list of people to help.
- Read up on negotiation methods. Don’t wait until you need those skills. Get them now. Practice them. You’ll need them even during a layoff. In fact, you should know what to do when you get a lay off notice a head of time. Your rights and obligations vary by jurisdiction, but generally you don’t have to sign or agree to anything right then and there, even if they tell you that you do.
- Have two month’s salary in savings—severance and unemployment will help, but having a nice cushion is very good. I know this one is really difficult. But having a cushion allows you and your family to choose better options.
One other thing to remember—you are going to lose all computer access. This means your files and contacts will be gone. Make sure you keep copies of your contacts and any scripts or tools that you would like to retain, at least the ones you are allowed to take with you. Be sure you keep your personal files and contacts separate from your corporates ones.
The Good News
Depending on what your data source is the unemployment rate for database professionals is between 1-3%. The US Government defines full employment at 3%, so that means it won’t take you very long to find a new job. The one thing I recommend highly is leveraging the outplacement services you’ll get as part of your severance package. Those folks are professionals and can help you write a really good resume. Aside from that some other things you should do are:
- Leverage your network. Let folks in your user group and personal network know that you are looking for a new gig (I’m assuming you are in a user group if you are reading this—if you aren’t, you should be). The best jobs frequently never make it to a formal posting. This is where all that user grouping, social media
workfun, blogging, and generally being a great resource to others is going to pay off, in a big way.
- Update LinkedIn. Yes, I said above to do this regularly. You still need to do that. But right now you need to let that network know you are looking for a job. Do not under any circumstances change your title to Unemployed or something weak like that. Change your title to the type of job you are looking for (and are qualified for). This is the time to leverage your networks, so your networking profiles need to reflect the fact that you are looking for a new project.
- Take the downtime to rest, exercise and learn new skills. Is there a new database feature you’ve been wanting to play with, but couldn’t implement at your old job? Now is the time to learn it.
More Advice on Job Hunting and Layoffs
I’ve blogged about this topic before; you might find these posts helpful, too:
Do you have a blog post with career advice? If you leave a comment here on my blog, you can choose that post to share it, too. Share the love.
My Lessons on Layoffs
I’ve been around a while (I’m not old; I’m experienced), and I know a lot of this stuff, but “Do you have a bag” was still a surprise to me. There weren’t many rumours of layoffs out of Parabola, so even though the total number was small, it was more eye opening. The number one thing I learned yesterday though, was to bring a bag, a plastic trash bag, and keep it in my desk, because MassiveMegaGlobalMegaCorpTM probably doesn’t care enough about you to give you a box to put your belongings in.
If you work in a large organization, you probably have been through a number of reorganizations. You know how this works: your management chain changes, people get new titles, and maybe, if you are lucky a few people get laid off. A good example are DBAs–they are a regular choice for reorganization, as they are frequently moved from Infrastructure to Applications groups or vice versa.
So how does this happen? It’s usually a several phase process, which starts with a new high level executive (usually the CIO or perhaps in larger organizations a Senior Vice President). He or she brings in a team of overpaid consultants (no, not consultants that fix problems—these tend to be big 5 organizational consultants who haven’t actually worked in IT). And the new CIO, if your karma is really dented, will bring along a new team of direct reports to help him get his quarterly bonuses.
Then, the project gets a really cool, exciting sounding name.
So The Parabola Project usually starts in late summer, just after vacation season. You may notice strange requests for information from your manager, also you may hear undercurrents about the latest hot methodologies (Agile, ITIL, Scrum). Around Thanksgiving, the rumors will really kick into overdrive. “The whole IT org is getting outsourced to Moldovia”, or “The reason why Senior Director X left for BjgReallyCoolNewTech, Inc. is that he was going to lose his job in the reorg”, are some examples of the types of rumors you will hear. Then eventually in early December, just before everyone leaves for Christmas, a new organization will be announced, there will be grumblings, and your IT organization will continue to have the same problems it had before. Only now the problems will be even more complex due to the recent organizational changes and for two months people will be way less productive because they don’t know what they are supposed to be doing.
So why do we do this? Companies lose a ton of productivity and pay consulting firms into the millions of dollars for what amounts to rotating the tires on your car. I feel like it’s a twofold process that relates to poor management.
- Managers/Directors/VPs get bored in their day to day roles and want to make change happen
- The same group of middle managers doesn’t want to address people problems, so they try to solve them using process
- Calling something new (Special Knowledge Efficiency Workgroup will somehow make ineffective people, processes or technologies work better.
- Reorg activity can take the focus of poorly performing projects as well as provide a great project slippage justification
Technology, Process and People
IT is a three-legged stool consist technology, process and people. You can mitigate some technology problems with people, and technology can be used to replace people (computers are more consistent than humans). Where it gets challenging is when companies try to fix people problems with process. Once in a while a reorg can help foster collaboration within an organization. I’ve been through one such reorg where functions were split into a global/regional/local model, which was really effective in fostering process standardization and opening communication channels. However, when people who or can’t do their jobs, changing the reporting structure won’t turn them into superstars. Instead, the constant cycle of reorgs annoys and drives away your good employees. The mediocre employees who are happy just to have jobs, will stay since they have fewer options. So what can you do when the inevitable reorg happens?
- Have a really solid internal network—it will let you know if you are being impacted well ahead of the reorg, which leads to…
- Always have your resume/CV up to date, if the reorg puts you in a less favorable position, it may be time to move
- Having a strong external network is also critical in helping plan your next moves
As long as there are companies there will be reorgs—middle managers need to keep themselves occupied. The best way to deal with this as an employee is to keep yourself extremely employable—keep your skills and network up to date, and you will always have a lot of employment options. If you have career options, you won’t need to sweat a reorg, and if the reorg really sucks, vote with your feet.
I agree with this:
The intellectual equipment needed for the job of the future is an ability to define problems, quickly assimilate relevant data, conceptualize and reorganize the information, make deductive and inductive leaps with it, ask hard questions about it, discuss findings with colleagues, work collaboratively to find solutions and then convince others.
Do you think this we are educating our future generations for this sort of job of the future? Are we creating the type of learning and living environments that encourage our kids to tackle these kinds of tasks?
I blogged over on Dataversity about Hiring Data Professionals: Mason Dixon Lines and Zombies in Your Job Postings . In that rant, I talk about organizations that want to hire people who can do everything in the data column of the Zachman Framework.
I call these people "wonder candidates" and write about how they don’t exist in sufficient numbers to supply all the organizations in the world:
It would seem to make sense that if you were hiring a data professional you’d design a position that fills in the Data column, right? No? It turns out, though, that most people don’t think and work along a column. In my experience, people aren’t passionate about tasks that span columns from top to bottom. They normally aren’t skilled along the whole column, either. Referring to the Zachman Framework, what sorts of skills and passions would this candidate need: planning, architecting, designing, building systems, building parts, keeping the systems up and running.
I thought about my rant in this area while reading a job posting on Dataversity for a Data Architect. I’m sure the people at Miami Children’s Hospital do amazing things, probably with very limited budgets. That’s why these hiring organizations tell me they have to fill their positions with Architect Designer Developer Implementer Operational Support Wonder Candidates. I’m going to pick on this posting, so apologies to the hospital for using them as an anti-pattern for finding good data architects. I’m sure they are nice people there and really want to get to successful database and data warehouse solutions. You might even want to apply for that job.
“Designs and constructs very large relational databases for data warehousing. Develops data models and is responsible for data acquisition, access analysis and design, and archive/recovery/load design and implementation. Integrates new data with existing data data warehouses in design and planning.”
Right there we have the keywords design, constructs, develops, implementation. These activities are done in different rows in the data column of the Zachman Framework. There’s also this:
performance tuning, data retention policies, data classification, data security, and data acquisition….Data modeling experience. Database and application object management, including DDL, table constraints and triggers, clusters, object storage allocation and tuning, indexing options and tradeoffs, partitioning, etc., experience.”
Those activities are clearly down in the lower half of the Framework. Yet data modeling, which exists along the entire data column, is not typically a strong skill set for people who work so far down in the Framework. So my guess is that professional data architects and modelers will not be qualified to do the clustering/partitioning/indexing/performance tuning part of the job and that implementers who can won’t be qualified to prepare and maintain the data models they also want out of this role.
If I were interviewing for this type of position, I’d focus on why this organization wants data models but doesn’t seem to want to fund a data architect. It’s sounds crazy, but I recommend that organizations not incur the costs of preparing and maintaining data models when they don’t want to work with professional data modelers. They won’t see many of the benefits of having an active data model but will incur all the costs and the risks associated with preparing incorrect ones.
I realize that there are many successful IT professionals who can work along many rows and columns. I’ve worked with these amazing people. But staffing a team of these amazing people is costly: they are difficult to find, expensive to hire, and tough to keep around because:
There may be people who can do a lot of those things, but in my experience they aren’t passionate about all of them. New hires won’t be happy and the organization will not realize the economies that they think they will.
I recommend that if organizations want to combine responsibilities that they do so across the columns in the same range of rows. Combining positions where thought processes are similar (business and data analysts, DBAs and developers, etc.). Analysts in general make for good analysts in other columns. Operational people tend to think operationally, builders tend to think mostly of building, not planning well. Let’s not drag people up or down the rows.
Go now and check your job postings. Do they reflect the true nature of the job? Or are they actually full of zombies ready to drag someone to an assignment that they don’t really want?
Do you work with any of these Zombies? People who have been hired to fill several jobs, but don’t have the passion or skills to do all of them? How is that working?
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