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. Some technical debt is done purposefully to deliver applications faster, while.
Social, Agile and Transformation
AUGUST 24, 2020
Data science requires questions, hypotheses, discovery, analysis, and recalibration. While the words I'm using to describe a data science are different than software development, the process and mindset are very applicable to agile methodologies. . And just like software development, data science requires a.
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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.
Data Center Knowledge
DECEMBER 21, 2016
There are a few critical processes that companies can employ to take full advantage of delivering more relevant applications faster, while still adapting to the necessary privacy processes to work in this world of big data sets. Read More.
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. A program is something ongoing and relatively permanent.
CTOvision
JULY 31, 2013
By Ryan Kamauff Peter Schlampp, the Vice President of Products and Business Development at Platfora, explains what the Hadoop Big Data reservoir is and is not in this webinar that I watched today. Platfora arrived at these conclusions from interviews of over 200 enteprise IT professionals who are working in the big data space.
Social, Agile and Transformation
MARCH 4, 2019
Designing and developing data-driven applications has to go through a modified agile planning, discovery, and user experience design compared to traditional applications. Because the data is an input to the design and development process! They have to review the underlying data, work with customers to.
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