Tag: Strategy
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Tableau Rollout Across Five Dimensions
Standing up any new analytics tool in an organization is complex, and early on, new adopters of Tableau often struggle to include all the complexities in their plan. This post proposes a mental model in the form of a story of how Tableau might have rolled out in one hypothetical installation to uncover common challenges for…
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More on the Agile Architect: Process and Knowledge Transfer
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…
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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…
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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…
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Five Thoughts On Data Management Maturity
Recently 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…
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No More Enterprise Data Sinks – An Agile Data Warehousing Manifesto
Over the past year I’ve reviewed what seem like countless plans for enterprise data warehouses. The plans address real problems in the organizations involved: the organization needs better data to recognize trends and react faster to opportunities and challenges; business measures and analyses are unavailable because data in source systems is inconsistent, incomplete, erroneous, or…
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Manage DATA, People, Process, and Technology
A quick Google search seems to reveal if you manage People, Process, and Technology you’ve got everything covered. That’s simply not the case. Data is separate and distinct from the things it describes — namely people, processes, and technologies — and organizations must separately and intentionally manage it. The data management message seems a tough…
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What is Big Data Creativity and How Do You Get It?
In 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…
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Requirements Half-Life
I had pondered writing a post called “Requirements Decay” about how requirements don’t last forever. In my research I found that such a post, complete with “my” words “requirements decay” and “requirements half-life”, had already been done comprehensively here. In a compact argument underpinned by half-life mathematics, the anonymous author proposes that a requirement isn’t likely…
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To SQL or to NoSQL?
Recently there was a great post at Dzone recounting how one “tech savvy startup” moved away from its NoSQL database management system to a relational one. The writer, Matt Butcher, plays out the reasons under these main points: Our data is relational We need better querying We have access to better resources Summing up: “The bottom…