April 04, 2014

How Do You Evaluate a Data Scientist?
Good data scientists will not just address business problems; they will pick the right problems that offer the most value to the organisation. It is essential for a data scientist to understand the domains of programming, machine learning, data mining, statistics, and hacking--in the positive sense. These are keys to getting in and grabbing the data one needs.  A good data scientist needs to understand his domain, whether it’s science, engineering or business. He needs to be able to cut through the myths associated with big data.


Seven Steps to Create an Unbeatable Enterprise Mobility Strategy
An enterprise mobility strategy is less about managing mobile devices and more about being an advocate for the business—enabling the business to integrate and deliver new and innovative business services more quickly. It is more about enabling and accelerating new windows of opportunity and efficiencies and less about restricting access and choices, which can have the unintended consequence of slowing business down. Even so, security remains fundamental to making these new and innovative business services possible.


Key Considerations in Establishing a Chief Data Office
Many organizations are setting up centralized data management departments. These departments may be called Enterprise Data Management, Enterprise Information Management or the Chief Data Office. Whatever they are called, these departments are accountable for getting their organizations to treat data as an enterprise asset, they share some common characteristics and they increasingly report into the business rather than IT.


Yorgen Edholm of Accellion, on the Motivation of Passion
You can’t have people who are afraid of making mistakes. In high-tech, there are no templates. And when you have no templates, you can’t think that with the right time and resources, you’ll have a 95 percent chance of success. We can’t have people who approach problems by thinking, “If I can’t guarantee success, it’s going to hurt me.” The idea is not to celebrate mistakes, but to be somewhat tolerant of them. Whenever something unexpected happens in a big company, that’s not a good thing.


Competition from FinTech startups keeps big suppliers on their toes
The large suppliers are even asking Barclays for advice on how to become more agile after the bank launched it mobile service PingIt in just seven months. “We have articulated the model as to how we acted as a startup internally to disrupt ourselves and we’re starting to industrialise that,” said White. “I can count five large technology companies all of the names you would imagine have come to Barclays and have asked how we are doing it,” he said. Alistair Grant, EMEA CIO at Citi has also noticed how startups are keeping the big suppliers on their toes.


Financial firms and social media remain top Phishing targets
Social networks were the top Phishing target in 2013, with nearly 36 percent of the overall volume, which makes sense given that those attacks often have a goal of propagation. If a person's social presence is compromised, then their friends and any associated accounts (especially if they recycle passwords), such as email, are likely to fall too. On the other hand, financially-based Phishing attacks were also popular last year. Kaspersky says that nearly 23 percent of the year's Phishing attacks targeted the financial sector globally.


API testing ensures smooth sailing for SOA enterprises
API testing at the integration level is where the application consuming the service is examined. Various scenarios should be investigated to ensure caching or interpretation issues, for example, don't arise. While manual testing is encouraged, Dan said it's not always a viable method for service and API testing, particularly at the service function level. "A service is something more than a way to process information," Dang said. "A way to process that information is always by some kind of data going in and some sort of response coming back."


Twitter uses code refactoring to reduce risk and improve testing
One risk comes from overly large files. Large files should be broken up into multiple smaller ones when possible. Modifying these smaller files is less risky, said Ornelas, because there is less for a developer to keep in his head when working on them. Other risks relate to the separation of the groups working on the same file. Ornelas said other research has shown that as code is touched by a larger number of groups, the risks can go up. "The more cohesive your organization is with the code base, the better the quality of code," he said. If a lot of different teams are modifying a single file, it probably means something is wrong.


How to keep the rush to cloud from clouding enterprise judgement
In many ways, cloud represents a step backwards from a decade of work to bring applications and systems together within a common, standardized framework. The authors point out that architecture -- service-oriented architecture -- is taking on an even greater urgency as enterprises latch onto "legacy clouds." While not mentioned specifically in the article, many cloud services are now criss-crossing enterprises in spaghetti-like fashion, used and paid for by lines of business outside of IT. There is no doubt plenty of money being spent on services that are either duplicated or going virtually unused.


Interview with Tobias Mayer about the People’s Scrum and AgileLib
The people’s Scrum by Tobias Mayer is a collection of essays based on material written by him between 2005 and 2012. The essays describe agile ideas and practices, examples of the topics covered are self-organizing, team working, craftsmanship, technical debt, estimation, retrospectives, culture and Scrum adoption. InfoQ interviewed Tobias about the importance of people, teams and self organization with Scrum and about AgileLib.net, a new initiative for sharing agile resources.



Quote for the day:

"There is a difference between knowing the path & walking the path." -- Morpheus