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 my last Advisor, we examined some opportunities for applying agile principles to a "services in advance" (SIA) approach to SOA (see "How to Help Agile Get a Head Start," 23 July 2009).
In the first of this two-part Executive Update series,1 I took a swipe at the currently accepted approach to systems development. My argument was that if a system is to adequately support a business, the information it handles must be rigorously derived from the business itself.
This Executive Update touches on a solution for recording and maintaining the data lineage for decision support systems (DSSs). The aim is to increase the effectiveness and pace of impact analysis for enhancements and root-cause analysis of data issues. The solution explores the idea of connecting ETL and BI metadata via a custom-built metadata repository provisioning an end-to-end view of data from upstream to downstream.
Recently, looking at scaling issues for a couple of multinational organizations, the issue of feature teams (customer-oriented) versus component teams (technically oriented) arose again. There are some in the agile community who think that feature-oriented teams are the only correct way, but the issue is more complicated than a simple solution can handle. For software systems that run into millions of lines of code and large legacy systems for which the architecture can't be easily changed, a combined team strategy is often warranted.