The buzz around data and artificial intelligence (AI) often overshadows a fundamental truth: the core of any successful endeavor remains distinctly human. As businesses navigate the complexities of the digital age, the importance of human insight, empathy, and value-driven strategies becomes increasingly evident.
Read MoreTaxonomy v Folksonomy
The concepts of taxonomy and folksonomy hold significant implications, especially in the context of emerging technologies like OpenAI. While traditional taxonomies offer structured hierarchies of knowledge, allowing for a systematic approach to information organization, folksonomies represent a more fluid and emergent way of categorizing information based on user-generated tags and metadata.
However, the challenge arises when technological advancements fail to incorporate divergent thinking and promote groupthink through convergent taxonomies. This phenomenon is particularly evident in language models, where developers' linguistic and cultural biases can influence the interpretation and representation of (the dominant) language.
Read More6 Myths and Misconceptions about Data Projects
As I considered how to promote my new book on driving data projects, I wanted to include myths and misconceptions that reinforce their value. I have experienced many of these in teams I’ve worked on or with. Data projects are not a static set of routines. It's a constantly evolving, open-to-innovation process.
Only 54 percent of organizations fully understand the value of project management, according to PMI's Pulse of the Profession™ report. That might explain, in part, why project success rates are so low: Less than two-thirds meet their original business intents.
Read MoreData Projects: Tips and Challenges
As we continue to drive data projects, familiar challenges begin to present themselves. By observing, we can become better diagnosticians of systemic issues. Learn what to avoid and how to navigate them better.
Read MoreResistance mitigation strategies
Change management wouldn’t be so hard if it weren’t for…the people. Open issues or objections left unresolved today cost time down the road. Suppose work starts before these concerns are mitigated. Stakeholders might get frustrated or begin to hold back their participation. Work produced might have difficulty getting implemented. Buy-in realizes impact.
Read MoreCountdown: Book Excerpt Chapter 2
Book Excerpt: While a fully funded budget that supports data as a service is an integral part of a data transformation’s financial picture, few are fully staffed or funded. Three-quarters of executives confirm their organization now has some form of data strategy (however rudimentary), but a paltry 16% say they have the skills and capabilities necessary to deliver it.[1] Even though the average staffing budget is growing yearly, finding the skills and capabilities to execute data projects is becoming harder and harder.
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