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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The primary goals of this Reining in Technical Debt webinar are to give you a preliminary understanding how quality can be assessed through technical debt techniques, to familiarize you with state of the art tools for measuring technical debt and to demonstrate how value delivery is affected when the technical debt is not "paid back" promptly. Israel and John will also introduce you to a governance framework that ensures you can rigorously manage your software development process from a business perspective.
In my last Advisor ("Understanding the Master Data Management Challenge," 4 August 2010), I discussed the demands of Master Data Management (MDM), particularly the difficulties of combining data from multiple sources.
In my last Advisor ("Understanding the Master Data Management Challenge," 4 August 2010), I discussed the demands of Master Data Management (MDM), particularly the difficulties of combining data from multiple sources.
Enterprise Data (Information) Architecture 101
Every large enterprise has what I call "one huge accidentally distributed database"; i.e., thousands of individual database tables, files, spreadsheets, and document stores with the same data elements stored redundantly all over the place and multiple copies of that same data stored over and over again. All of this complexity takes time to get your brain around if you're a new enterprise data architect.
Enterprise Data (Information) Architecture 101
Every large enterprise has what I call "one huge accidentally distributed database"; i.e., thousands of individual database tables, files, spreadsheets, and document stores with the same data elements stored redundantly all over the place and multiple copies of that same data stored over and over again.
There is one primary reason that legacy modernization projects fail, and one primary strategy that will guarantee success. Applying that strategy, however, almost always meets strong resistance from the technical staff, which management can overcome only rarely.