Data quality improvements follow specific, clear leadership from the top. Project leaders count data quality among project goals when senior management encourages them to do so with unequivocal incentives, a common business vocabulary, shared understanding of data quality principles, and general agreement on the objects of interest to the business and their key characteristics.
Poor data quality costs businesses about “$15 million per year in losses, according to Gartner.” AsTendü Yoğurtçuputs it, “artificial intelligence (AI) and machine learning algorithms are only as effective as the data they use.” Data scientistsunderstandthe difficulties well, as they spend over 70% of their time in data prep.
Recent studies report that data entry typos are the largest source of poor data quality (here and here). My experience says otherwise. From what I’ve seen, operational data is generally good, and data errors only appear when data changes context. In this post I’ll detail why data quality is management’s responsibility, and why data quality will remain poor until leadership makes it a priority.Continue reading →
It’s been a truism that data is a resource, but to prove it you just have to follow the money. As the illustration shows, the vast majority of corporate market value draws from intangible assets. Just as money is an abstraction that represents wealth, data is an abstraction that represents these intangible assets.
It’s year three after initial rollout of the Leader’s Data Manifesto (LDM). Since then, many widely publicized events have highlighted the value of data and metadata, and the importance of sound data management (here, here, and here). Recently at Enterprise Data World, John Ladley, Danette McGilvray, James Price, and Tom Redman presented this year’s LDM update. They reintroduced the Manifesto, recounted events of the past year, discussed strategy for the coming year, and issued a call to action for data professionals. Continue reading →
In data management and analytics, we often focus on correcting apparent inability and unwillingness on the part of business leaders to effectively gather and capitalize on data resources. With that perspective, we often see ethics as a side issue difficult to prioritize given the scale and persistence of our other challenges.
At least that was my perspective, and my initial response when confronted recently by a family member on this topic. Her view from outside the field was that ethics should be a primary concern. As I’ve reflected on this conversation, I’ve come around to her point.
In recent years we’ve seen many examples of data misuse due to ethical lapses. Here’s a post that gives five examples, including police officers looking up data on individuals not related to any police business, an employee passing personal data including SSNs to a text sharing site, and Uber’s “god view”, available at the corporate level, which an employee used in 2014 to track a journalist’s location. Continue reading →
What is Data Quality anyway? If you are a data professional, I’m sure someone from outside our field has asked you that question, and if you’re like me you’ve fallen into the trap of answering in data-speak.
To my listener, I’d guess that the experience was similar to having a customer service rep who has just turned down his simple request justify it by describing byzantine company policies.
There’s a ton of great writing available on data quality, and I in no way mean to disparage it or its value in the field. But in that writing I’ve yet to find a concise and compelling definition that’s useful to non-data professionals. I’ll review one or two prevailing definitions and then offer one that could help us unlock real data quality improvements. Continue reading →
Modern data architectures, by enabling data analytics insights, promise to drive order of magnitude value gains across many business sectors (here, here, and here). Not so long ago, big data presented a daunting challenge. Although tools were plentiful, we struggled to conceptualize the architecture and organization within which to capitalize on those tools. Now solid frameworks have emerged. This post reviews two promising models for modern data architecture, and discusses two key cultural values critical to their successful adoption: drive to solve business challenges and drive for universal data correctness. Continue reading →
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.
Obviously, data management is important. Unfortunately, it is not prioritized in most organizations. Those that effectively manage data perform far better than organizations that don’t. Everyone who needs data to do his/her job must drive change to improve data management.
That was the theme of the recent Enterprise Data World (EDWorld) conference this week. This year’s EDWorld event might be the start of a new vitality and influence for the field, marked by introduction of a Leader’s Data Manifesto.
Over the years, data practitioners struggled for recognition and resources within their organizations. In reaction, they often focused on data “train wrecks” that this neglect causes. This year’s conference was no exception. For example: Continue reading →
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 →
It’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 →
I’ve written about groupthink-related quality challenges on Agile projects, and the architect’s role in preventing groupthink from degrading quality. I’ve seen other risks related to the cohesion and potential insularity of successful Agile teams, and the architect is also well positioned to help prevent these: a tendency to neglect setting up and documenting repeatable processes, and a similar tendency not to share of knowledge and lessons learned outside the Agile team. Continue reading →