Advisors provide a continuous flow of information on the topics covered by each practice, including consultant insights and reports from the front lines, analyses of trends, and breaking new ideas. Advisors are delivered directly to your email inbox, and are also available in the resource library.
Gamification and Big Data
Gamification is a tech industry buzzword referring to the use of gaming techniques in non-game applications. Big Data refers to data having properties like huge volume, high velocity, variety, and variability. A lot of people are already talking about Big Data, but many people question what to do with this data and how to make actionable insights out of it.
Gamification and Big Data
Gamification is a tech industry buzzword referring to the use of gaming techniques in non-game applications. Big Data refers to data having properties like huge volume, high velocity, variety, and variability. A lot of people are already talking about Big Data, but many people question what to do with this data and how to make actionable insights out of it.
About Transparency and Its Limits
In his recent novel The Circle, Dave Eggers draws the picture of a fictitious Internet company called "The Circle" that has broken the anonymity of Internet communication and subsequently has bought Google, Twi
Improving Process Improvement
So Much Change, So What?
4 Tips for Setting Up and Operating Agile Groups
Many large organizations set up Agile focus or mentoring groups for driving Agile implementation across the organization. They entrust those Agile groups with improving IT delivery capabilities by applying suitable methods. In this Advisor, I share four practical tips to be aware of while operating Agile focus groups.
EA: Art or Science?
Disciplined Agile Delivery: The Foundation for Scaling Agile
[From the Editor: This week's Cutter IT Advisor is from Scott W. Ambler's introduction to the November 2013 issue of Cutter IT Journal, "Disciplined Agile Delivery: The Foundation for Scaling Agile" (Vol. 26, No. 11).
Data Curation
As we move into the era of Big Data analysis and extensive use of unstructured data, it is time to take a closer look at data-quality issues. While there have long been procedures in place for ensuring quality of transactional data, unstructured data has been less well served. Unstructured data and data sources outside of the firm can be relatively opaque. Processes should be developed to ensure that data is maintained for future use -- adequately stored, accurate, and secure.
Data Curation
General Failures of Notice and Consent
The concept of notice and consent pervades modern privacy law and regulations. The efforts are laudable, but our cognitive limits and the rapid pace of advancing technology are straining their usefulness.
Why Do We Need Real-Time Digital Data Streams?
The ability to analyze data in real time has enormous potential in significantly impacting business performance at both the departmental and strategic levels. Internal data sets spanning across multiple departments often hold massive amounts of valuable data. These data sets, coupled with carefully selected real-time digital data streams (DDS), are increasingly becoming critical in data-based decision making by departmental managers as well as strategic-level stakeholders.
Mapping Psychosociological Needs to Agile
Agile is well served by exploring the connections between knowledge, culture, psychology, and technology. As Cutter Fellow Vince Kellen states:
The Social Media Path to Value
Trust but Encrypt
Organizational Agility, Not Agile Projects
My Executive Report "Agile Business: The Final Frontier" outlined some key elements of how we can extend and expand the fundamental concepts of Agile project management (APM) and Agile development to an holistic organizational approach to organizational agility.
The Circle -- Privacy, Transparency, and Anonymity in a Hyper-Connected World
The Circle -- the new novel from Dave Eggers -- is being billed as sort of a modern 1984 meets A Brave New World.
What's Wrong with Targets?
I've written multiple articles and given numerous presentations on the problems with establishing targets for your measures of improvement. It's worth reiterating what's wrong with them, though, because if you haven't tried using targets, chances are you will.
Predictive Analytics, Hadoop, and Mahout
Hadoop is receiving a lot of attention from data mining and predictive analytics practitioners because it offers a scalable platform for building, training, and testing models that can be executed in parallel using massive volumes of data, as opposed to typical data mining practices involving the use of sample data sets for m