Strategic advice to leverage new technologies
Technology is at the heart of nearly every enterprise, enabling new business models and strategies, and serving as the catalyst to industry convergence. Leveraging the right technology can improve business outcomes, providing intelligence and insights that help you make more informed and accurate decisions. From finding patterns in data through data science, to curating relevant insights with data analytics, to the predictive abilities and innumerable applications of AI, to solving challenging business problems with ML, NLP, and knowledge graphs, technology has brought decision-making to a more intelligent level. Keep pace with the technology trends, opportunities, applications, and real-world use cases that will move your organization closer to its transformation and business goals.
Insight
In The Art of Agile Practice, I discuss why organizations should embed the values and practices of Agile within their existing planned and formal approaches and how they can go about doing so.
For the purpose of Cutter Consortium's latest CBR survey, we define Agile data analytics as "the application of Agile methods to data analytics initiatives in order to increase flexibility, provide faster 'time to value,' and support collaborative relationships between business users and IT developers." Further still, as described by Agile data analytics expert Ken Collier, Agile methods are built on a "simple set of sensible values and principles but require a high degree of discipline and rigor to properly execute" and as a process Agile falls somewhere in the "middle betwe
Based on my professional experience in both the large enterprise and startup worlds, I believe that business intelligence (BI) and the general category of analytics for business can benefit greatly from the application of Agile development methodologies.
I hope this issue of Cutter Benchmark Review gave you food for thought and some useful guidance as you consider your current and future Agile data analytics efforts. I'll wrap up the issue by pointing out a few things that really stood out for me -- both in the data and our two articles -- and which point the way to specific actions: