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.
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I have often joked that data warehouses are as unfriendly to business users as physical warehouses are to shoppers. The reality is perhaps grimmer: data warehouse designs took no cognizance of the actual processes at work within human beings when making decisions. Data lakes, despite metaphors of recreational use and dipping in for data, actually pay as little attention to the mental processes involved in decision making as did data warehousing.
The habits of thought that we learn and practice as we conduct EA can influence our thinking and behavior in broad aspects of our lives. Indeed, wise use of EA can train us to be better thinkers; unwise use can reinforce our bad habits. This Executive Update explores how we should revisit the original intent of EA and bring the human element back into EA practice. Not because we failed in our attempt to automate enterprise architecture (thank goodness), but because it is the right thing to do.
I've been researching how banks and other financial institutions are using cognitive systems. The short story is that cognitive systems like IBM Watson, Expert System's Cogito, and Microsoft's Cognitive Services — as well as industry-specific commercial solutions built upon these and other providers' cognitive platforms — are increasingly being utilized in banking and finance.
In practice, content and information management systems today haven’t fulfilled their promise. They don’t understand unstructured data, and they can’t directly act upon it. They work well only when people follow defined information governance processes.
This article addresses the challenge of slicing data warehousing and business intelligence (DW/BI) user stories into small, business-valued deliverables to align with the Agile principle of "Deliver[ing] working software frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale."
The idea of a metaframework isn’t really anything new. It is simply a way of describing something that enterprise architects need to do.
Hex elementalization aims to create a platform — an architecture, an environment — encompassing end-to-end integration. The traditional way of thinking about data in 1s and 0s (bits) is unsuitable if we want to create a common “playground” for IoT. No matter how large or diverse the data is, it needs to be broken down into smaller chunks that will enable and ease interaction. These smaller chunks (i.e., hex elements) can be combined and related into meaningful information. Why “hex” elements? This article explains.
Traditionally, EA has focused on delivering a set of guiding principles, frameworks, reference models, blueprints, and roadmaps to support operational excellence as well as strategic business and IT alignment goals. Today this focus is shifting toward leveraging collaborative, agile, disruptive, and innovative approaches to executing EA practices for digital transformation. Like many thought leaders, I believe that in order to successfully implement a new change, a new EA must be proactive and customer-oriented. This new EA must be innovative enough to deliver tangible business results more consistently and more frequently to capitalize on the IoT opportunity. EA and IoT together help enterprises to leverage their capabilities (people, process, and technology) while establishing mechanisms or conduits for the digital transformation.