Tag: Business Analysis
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Reengineered Processes Need Business-Defined Data
“Business process reengineering is the act of recreating a core business process with the goal of improving product output, quality, or reducing costs.”* Recently I’ve perused articles on business process reengineering and have been surprised to find that they share a lack of emphasis on data definition. By establishing a shared business vocabulary, identifying and…
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Data Architecture for Improved Dashboard Performance
Sometimes success seems like a data analytics team’s worst enemy. A few successful visualizations packaged up into a dashboard by a small skunkworks team can generate interest such that a year later the team has published scores of mission critical dashboards. As their use spreads throughout the organization, and as features expand to meet the…
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How to be a good client
I recently listened to Brian O’Neill’s excellent interview with Tom Davenport, headlined “Why on a scale of 1-10, the field of analytics has only gone from a one to about a two in ten years time.” The conversation covered a lot of ground as Mr O’Neill and Mr Davenport explored the reasons why. Highlights included…
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Data Governance Meets Procurement
Why pay good money for bad data? Of course no one would do that on purpose, but I as a consultant over many years I’ve often seen it. A vendor fulfills a contract to the letter, which unfortunately allows them to deliver required reports in various, sometimes changing, formats with suspect data quality. The customer…
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Anonymize Data for Better Executive Analytics
Reading articles about data anonymization makes it clear that it is not an entirely effective security measure (here and here), but still part of a robust security capability, and required if your organization is affected by GDPR. (I use “anonymization” as a general term encompassing techniques that de-identify personal data within a given data set.) But there’s a positive…
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Meaningful Requirements Start Successful Data Projects
To me, development projects fail or succeed in the first few weeks. Once a project starts off in the wrong direction, momentum and expectations tend to prevent a return to the proper path. With today’s wealth of database options each addressing exciting new possibilities, the right choice for the application’s data foundation plays a large…
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The PDDQ Framework: Lean Data Quality for Patient Records
For most of us it may have slipped under the radar, but in December a groundbreaking Patient Demographic Data Quality framework was jointly released by a US government agency and the CMMI Institute. In response to findings that many “safety-related events were caused by or related to incorrect patient identification”, the Office of the National Coordinator…
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The Practical Metadata Business Case
Even now the business case for a metadata tool seems unclear and difficult to quantify, but it isn’t impossible. We in the data management business tend to devalue solutions that don’t clearly derive from a coherent top-level view. We seek applications defined from an enterprise architecture, database designs from an enterprise data model, and data…
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Analytics Requirements: Avoid a Y2.xK Crisis
Even though it happens annually, teams building new visualizations often forget to think about the effects of turning over from one year to another. In today’s fast paced, Agile world, requirements for even the most critical dashboards and visualizations tend to evolve, and development often proceeds iteratively from a scratchpad sketch through successively more detailed…
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Assumptions: A Key to Technical Leadership
There’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…