Tag Archives: Professional Development

Values and Behaviors of the Successful Agilist

Of course, any discussion of Agile values starts with the Agile Manifesto. The first sentence declares that Agile development is about seeking better ways and helping others. Then, as if espousing self-evident truths, the founders present four relative value statements. Finally, they emphasize appropriate balance, saying that the relatively less valued items aren’t worthless: implying that they are to be maintained inasmuch as they support the relatively more valued items.

While there is value in the four relative value statements, I believe most successful Agilists value the first and last statements more. So to me, the core Agile values are continuous improvement, helping others, and balance.

There’s a lot written about Agile behaviors, but as I read most is geared toward scrummasters or managers, and most is about transitioning from the waterfall world. Starting from the premise that Agile methods are established, focusing on participants rather than managers, and based on the assumption that behaviors are grounded in values, this post details the values and behaviors I’ve observed of those who succeed as Agile team members.

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Escaping Teradata Purgatory (Select Failed. [2646] No more spool space)

Also see the related post More on “Select Failed. [2646] No more spool space”

If you are a SQL developer or data analyst working with Teradata, it is likely you’ve gotten this error message: “Select Failed. [2646] No more spool space”. Roughly speaking, Teradata “spool” is the space DBAs assign to each user account as work space for queries. So, for example, if your query needs to build an intermediate table behind the scenes to sort or otherwise process before it hands over your result set, that happens in spool space. It is limited, in part, to keep your potentially runaway query from using up too much space and clogging up the system.

After briefly setting the stage, this post presents the top three tactics I use to avoid or overcome spool space errors. For the second two tactics I’ll show working code. At the end of the post you’ll find volatile DDL that you can use to get the queries to run. Continue reading

The Faith of Tolerance

Yes this is a post about religion, so at the outset let me assure you that I won’t try to talk you into or out of any religion or otherwise. Nor will I reveal my beliefs. Instead, I will make the case that the beliefs of others are to be celebrated.

To those thinking this is off-topic, the “about” page says that this site deals in “motivated professionals working together to solve problems.” In order to cooperate closely and harmoniously, co-workers must share values that foster mutual trust. IT teams tend to be diverse. In this time when some of our elected officials sow distrust it is important to remember the last of the agile team values listed by Scrum Alliance: “As we work together, sharing successes and failures, we come to respect each other and to help each other become worthy of respect.”

I was motivated to write this after accidentally finding Landon Fowler’s 2016 article called The Faith of Atheism. To briefly summarize the argument (Landon correct me if I mischaracterize): Continue reading

Protect Your Culture: Screening for authoritarian project leaders

Bugs BunnyIt’s fashionable today to talk about the risks of authoritarianism in the political sphere. I’m not going to speculate on that, but such talk got me thinking about the same tendencies among IT project leaders. What is an authoritarian personality? (Yes, that’s actually a thing.) Is it truly antithetical to a healthy project? If so, how can you screen for it in hiring?

Recently, ArsTechnica ran an article that offers a survey of research on authoritarian personalities conducted since the 1940s. The bottom line for us is that those with authoritarian tendencies more often Continue reading

Tableau Startup: First Lessons Learned

XAs I mentioned in the February post, I’m new to Tableau, and as the tone of that post implied,enjoying it very much. Tableau is a robust and flexible solution for data delivery. Like Qlikview, which I worked with a while ago, it is supported by outstanding, and free, introductory training and a very active user community.

As I’ve made my first steps in Tableau I’ve been a frequent user community visitor, and generally have gotten the answers I’ve been looking for. However, like any tool there still have been a few surprises. I’ll run down the top few in this post:

  • Measures can have complex logic
  • Big extracts are tricky
  • Changing data sources is really tricky
  • Sorry, there are some things you just can’t do

Hopefully this post helps other novices negotiate those first few steps a bit more easily. Continue reading

No Silver BI Bullet: Tableau Edition (It’s a good thing!)

For complex work, a very simple app requires a very smart user. That point was driven home to me in Tableau Fundamentals class this week. I don’t see that as bad news at all.

Not so long ago I wrote a piece that attempted to inject a bit of reality into the claims then made by some data visualization tool vendors. I cited unexpected challenges that those adopting such tools for their obvious and compelling data presentation abilities might face. The challenges included unexpectedly complex data integration, establishing solid reporting standards and practices, scaling report distribution as demand for the visualizations expands, and the conversion work that can result from version upgrades.

Although a Fundamentals class, the experienced and enthusiastic instructor and the small, intelligent student group combined to make the two days immensely valuable, going far beyond the basics on the program (more on specific lessons learned will appear in an upcoming post). The instructor’s focus on principles rather than recipes drove home this point: in order to effectively use Tableau you have to understand not only how to operate Tableau itself but also the underlying data management, usability, and statistics principles.

Could it be that adopting easy-to-use Tableau in place of, say, SSRS, Cognos, or SAS requires an upgrade in staff knowledge and expertise? Continue reading

Assumptions: A Key to Technical Leadership

DonkeyThere’s an unfortunate and rather rude saying about assumptions that I’ve found popular among IT folks I’ve worked with. I say unfortunate because, to me, assumptions that are recognized early and handled the right way are a key to successful projects. Technical players who use assumptions well can help set projects on the right path long before they go astray.

Sometimes on waterfall and hybrid projects technical players are asked to estimate work early, before requirements are complete. My instinctive reaction is not to provide an ungrounded estimate, but that’s not helpful. The way to handle this uncomfortable uncertainty is to fill out the unknowns with assumptions: detailed, realistic statements that provide grounding for your estimate. Continue reading

A Short List of Accessible Big Data Training Options

As you’ve read on this site and many others, the database world is well into a transition from a relational focus to a focus on non-relational tools. While the relational approach underpins most organizations’ data management cycles, I’d venture to say that all have a big chunk of big data, NoSQL, unstructured data, and more in their five-year plans, and that chunk is what’s getting most of the executive “mind share”, to use the vernacular.

Some are well along the way in their big data learning adventure, but others haven’t started yet. One thing about this IT revolution is that there’s no shortage of highly accessible training options. But several people have complained to me about the sheer quantity of options, not to mention the sheer number of new words the novice needs to learn in order to figure out what the heck big data is.

So here’s a very short list of training options accessible to the IT professional who is a rank big data beginner, starting with a very brief classification of the tools that I hope provides a some context. Continue reading

What is Big Data Creativity and How Do You Get It?

Thomas EdisonIn a recent Smart Data Collective post, Bernard Marr cites creativity as a top big data skill, but what is creativity?

His point is, since big data applications are often off the beaten IT path, big data professionals must solve “problems that companies don’t even know they have – as their insights highlight bottlenecks or inefficiencies in the production, marketing or delivery processes,” often with “data which does not fit comfortably into tables and charts, such as human speech and writing.” Continue reading

Technical Interviewers: Seek Opinions Not Facts

Asking fact questions in technical interviews is like eating a donut, feels great at the time but not so satisfying later.

Let’s say the interview consists of facts like this “softball question”: “What is the default port number for SQL Server?” The linked list of questions is a really good high level study guide for a SQL Server student. If a SQL Server developer candidate answers all correctly, then the interviewer can be confident that the candidate knows a lot about SQL Server. 

However, few development jobs require only technical fact knowledge. Typically, developers must apply creativity when working with unclear or poorly expressed requirements under tight schedules. They must be versatile so that they can take on unforeseen roles in case of resignations or transfers of team members. If you make an investment in an individual by hiring her or him, you’ll look for a return in the form of professional development as the individual grows their skills.

So how do you test creativity, versatility, and ability to learn, while still gauging raw technical talent? My method is to ask opinion rather than fact questions.  Continue reading