Category Archives: Business

A New Direction for Data at #EDW17

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

Levels of Trust in Data Governance: It’s Not All or Nothing

The term “trust” implies absolutes, and that’s a good thing for relationships and art. However, in the business of data management, framing trust in data in true or false terms puts data governance at odds with good practice. A more nuanced view that recognizes the usefulness of not-fully-trusted data can bring vitality and relevance to data governance, and help it drive rather than restrict business results.

The Wikipedia entry — for many a first introduction to data governance — cites Bob Seiner’s definition: “Data governance is the formal execution and enforcement of authority over the management of data and data related assets.” The entry is accurate and useful, but words like “trust”, “financial misstatement”, and “adverse event” lead the reader to focus on the risk management role of governance.

However, the other role of data governance is to help make data available, useful, and understood. That means sometimes making data that’s not fully trusted available and easy to use. Continue reading

Five Thoughts On Data Management Maturity

StaircaseRecently I’ve had the opportunity to dig deeply into the CMMI Data Management Maturity model. Since its release, the DMM model has emerged as the de facto standard data management maturity framework (I’ve listed other frameworks at the end of this post).

I’m deeply impressed by the completeness and polish of the DMM model as a comprehensive catalog of processes required for effective data management. Even after decades in the business the broad scope and business focus of the model changed the way I think about data management.

Here are my impressions collected under five distinct categories. Continue reading

Three things about “Interview with a Data Scientist”

Chemistry-labRecently, I posted “Interview with a Data Scientist” at my company’s blog site. In it, my friend and colleague Yan Li answers four questions about being a data scientist and what it takes to become one. In my view Yan’s responses provide a bracing reminder that data science is something truly new, but that it rests on universal principles of application development. Continue reading

How To Do Well in Your Next Job Interview

Recently I read an editorial about job interviews. It was breezy and funny, but not very helpful. Given that millions are out there looking for work, I want to help by giving my perspective on how to “win” the interview.

I do a lot of interviewing, from both sides of the desk. As a consultant I am interviewed by clients. As one of many technical and behavioral interviewers for my employer, I talk with candidates about their skills, goals, and fit with our business.

Of course, winning the interview may not get you the job. An interview is just one part of a many step process. Getting a job involves showing you have the skills, establishing mutual fit, coming to terms on salary, and standing out versus the competition. This post is only about how to do well in the interview.

Assuming you’re qualified for the job, you can set up a good interview experience by applying the right mental model, preparing well, and interacting effectively during the conversation. Continue reading

Data Governance Begins At the Spreadsheet

Data management professionals have long and sometimes rather Quixotically driven organizations to “get past the spreadsheet culture.” Maybe that’s misguided. The recent furor over a widely read social science paper may show how we can look to scientific peer review for a way to govern data, spreadsheets and all.Spreadsheet

Recently, it was found that a key study underpinning debt-reduction as a driver of economic growth based its conclusions on a flawed spreadsheet. As this ArsTechnica article describes, Carmen Reinhart and Kenneth Rogoff’s Growth in a Time of Debt seemingly proved a connection between “high levels of debt and negative average economic growth”. But, per a recent study by Thomas Herndon, Michael Ash, and Robert Pollin, it turns out that the study’s conclusions drew from a Microsoft Excel formula mistake, questionable data exclusions, and non-standard weightings of base data. The ArsTechnica piece finds those conclusions fade to a more ambiguous outcome with errors and apparent biases corrected. Continue reading

Followership IV: How to criticize your boss

ObamaAndMcChrystalThis is the latest entry in an occasional series on followership. The premise, as stated here, is that not everyone gets to be a leader, and most leaders are also followers in their own right. The project manager follows instructions from the project sponsor, the CEO from the board, the politicians from the polls, and so on. Whoever you are, you spend a lot more time following than leading. As Bob Dylan put it so well, “you gotta serve somebody.”

The good follower is not a “yes man“. In the professional world I inhabit those who move “up” the hierarchy tend to retire technical skills in favor of architecture, proposal writing, and management. The relationship of manager to employee becomes more like agent to actor or musician, where the supervised employee is the “talent”.

In these conditions the old concept of top-down decision making seems quaint. Important choices require information from all perspectives, and organizations shut out those with knowledge of the details at their peril. The best decision makers search out diverse ideas before choosing a direction. Continue reading

No silver business intelligence bullets, but still a bright upside

When Tom Petty sang, “Hey baby, there ain’t no easy way out” he wasn’t referring to business intelligence (BI) reporting but he might have been. Current generation reporting engines, AKA data visualization or data discovery tools, market their products with statements like these, emphasizing quick development and ease of use:

  • “The democratization of data is here. In minutes, create an interactive viz (sic) and embed it in your website. Anyone can do it— and it’s free.” (Tableau Products Page)
  • “Easy yet sophisticated report design empowers your employees to design professional and telling reports in minutes not days” (Windward)

I like these tools, and I do believe that they can provide a leaner, more productive, and more informative approach to BI reporting than some more mature products.  However, none is a silver bullet for all data integration and reporting woes. Continue reading

Learning to learn

“A child of five could understand this. Send someone to fetch a child of five!”

– Groucho Marx

Recently my colleague Sara Shelton posted an article listing non-technical things we IT specialists need to do to maintain our careers. Each of the nine items on Sara’s list is a key to IT professional success. One particularly worthy of a drill down was learning:

“It is critical for the technical professional to hold themselves accountable…to learn new languages, new tools, emerging technical trends, and best practices.  With technologies changing more than ever, technical professionals need to focus on their own learning to stay on par with or ahead of the curve.” Continue reading

Abstracting and recombining all the way to the bank

In the past I’ve never understood what people really mean they say “think outside the box” but Jim Harris, in a recent OCDQ blog post, helped me figure it out.

Mr. Harris ends with this provocative line: “the bottom line is Google and Facebook have socialized data in order to capitalize data as a true corporate asset.”  The post starts with a cold war analogy and proceeds to describe how Facebook and Google have made big money as “internet advertising agencies:” offering free services with which users (like us) serve up personal data in return for use of the service, then selling advertising space based on our data (hopefully anonymized).

Continue reading