Social, Agile and Transformation
JANUARY 21, 2020
As more organizations have embarked on agile software development over the last five years as part of digital transformation programs, the term technical debt is more widely understood. Teams that develop code leave artifacts behind that require improvements, reengineering, refactoring, or wholesale rewriting.
Social, Agile and Transformation
JANUARY 24, 2013
Social, Agile, and Transformation. I cover topics for Technologists from CIOs to Developers - agile development, agile portfolio management, leadership, business intelligence, big data, startups, social networking, SaaS, content management, media, enterprise 2.0 Three Steps to Big Data Discovery.
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Social, Agile and Transformation
APRIL 28, 2014
Better late then never, and hopefully this will help some of you that are starting out looking at solutions to better store, search, and data mine text documents. . . So here are some things not to do (or avoid doing) with unstructured text Big Data: Develop home grown scripts to.
CTOvision
SEPTEMBER 21, 2015
Here’s something to think about when you're planning a big data project: are you planning a project or a program ? Relatively self-contained big data projects may be tied to an ongoing process or program that is already developing or delivering a product or service. Discussion.
CTOvision
DECEMBER 21, 2013
By Bob Gourley If you are an analyst or executive or architect engaged in the analysis of big data, this is a “must attend” event. Registration is now open for the third annual Federal Big Data Apache Hadoop Forum! 6, as leaders from government and industry convene to share Big Data best practices.
Social, Agile and Transformation
SEPTEMBER 28, 2012
Social, Agile, and Transformation. I cover topics for Technologists from CIOs to Developers - agile development, agile portfolio management, leadership, business intelligence, big data, startups, social networking, SaaS, content management, media, enterprise 2.0 Big Data Needs to Scale.
CTOvision
SEPTEMBER 17, 2014
SOCIAL IMPACT. Successfully deploying Hadoop as a core component or enterprise data hub within a symbiotic and interconnected big data ecosystem; integrating with existing relational data warehouse(s), data mart(s), and analytic systems, and supporting a wide range of user groups with different needs, skill sets, and workloads.
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