March 24, 2015

The data breach quiz: What have we learned?
Data breaches from Target to Sony to Anthem have been getting a lot of attention as millions of personal records are violated, and there’s lessons to be learned about data security from all these events. Here’s a short quiz about some of these and cyber security in general that will gauge how well you are prepared to deal with these threats. Keep score as you go and find out how well you did at the end.


Microsoft Apps Coming To Android Smartphones, Tablets
Through business-to-business sales channels, companies have access to the Business, Business Premium, and Enterprise versions of Office 365, which will be coupled with Knox. Microsoft's cloud-based Microsoft Office 365 offers access to the company's suite of Office applications, which include email, calendar, videoconferencing, and documents. The applications are optimized to provide a seamless experience across a variety of Internet-connected devices, including PCs, smartphones, and tablets. As part of the agreement, Samsung will include a setup service and provide ongoing support. The Galaxy S6 and Galaxy S6 edge will also come with 100 GB of additional free cloud storage for two years through Microsoft OneDrive


Data science done well looks easy, which is a big problem
In most cases, if the data scientist has done her job right the statistical models don't need to be incredibly complicated to identify the important relationships the project is trying to find. In fact, if a complicated statistical model seems necessary, it often means that you don't have the right data to answer the question you really want to answer. One option is to spend a huge amount of time trying to tune a statistical model to try to answer the question but serious data scientist's usually instead try to go back and get the right data. ... The really tricky twist is that bad data science looks easy too. You can scrape a data set off the web and slap a machine learning algorithm on it no problem. So how do you judge whether a data science project is really "hard" and whether the data scientist is an expert?


Good Design is About Process, not Product
When you study another designer’s trash, you will uncover the processes that drive her work. How many iterations of an unused idea were made before that idea was finally thrown away? How much variety can you find in the attempts at solving a particular problem? What common traits kept popping up between revisions? ... The tangible results of all creative acts are just the ash left behind by the way we work. What makes a design process healthy? I have some practical answers to this question. What I have to share comes from a variety of sources. These are in no particular order:


Google Play adds humans to the app review process
The manual checks are performed by a team of experts who will check for malware. An additional process will require developers to answer questionnaires that will help assign age-based ratings. "The move by Google is a good sign ­ the more eyes on the unsafe mobile app problem the better. In addition to the increasing threat of mobile malware, is the increasing exfiltration of sensitive data by seemingly legitimate apps. While other apps have been specifically designed to perform malicious actions other apps unknowingly access insecure third-party libraries and frameworks," Veracode's VP of Mobile, Theodora Titonis, told Salted Hash.


Awesome Analytics: Are We There Yet?
A hot topic of Gartner BI research in the late 1990s was the increasingly large ‘fact gap,’ whereby the amount of data available for decisions was rapidly outstripping the available analytic resources. With some minor modifications, such as changing ‘Terabytes’ to ‘Petabyes’ and ‘Analytic Personnel’ to ‘Data Scientists,’ the picture looks remarkably similar twenty years later. ... The top three problems remain data quality, ease of use, and the difficulty of integrating different systems. ... The top three barriers to business intelligence have remained largely unchanged for over a decade The reality is that today’s technology is much more powerful and widely used than in the past — but what was hard then remains hard today.


CFOs and the Many Flavors of Cloud
The emergence of Infrastructure-as-a-Service (IaaS) public cloud providers and hundreds of other SaaS applications have indeed brought innovation and time to market benefits, yet without oversight, adoption of these technologies can backfire quickly. Pretty soon, a company is overspending, using multiple services for the same purpose and exposing a company to data loss, security breaches and integration issues. This is where the CFO comes into the game. Beyond business applications, CFOs need to understand the quickly changing world of IT infrastructure and outsourcing. The more CFOs know about cloud computing and hosting options, the more they can influence IT decisions and help the CIO avoid a scenario of integration chaos and waste.


The data science ecosystem
Because data science is growing so rapidly, we now have a massive ecosystem of useful tools. I've spent the past month or so trying to organize this ecosystem into a coherent portrait and, over the next few days, I'm going to roll it out and explain what I think it all means. Since data science is so inherently cross-functional, many of these companies and tools are hard to categorize. But at the very highest level, they break down into the three main parts of a data scientist's work flow. Namely: getting data, wrangling data and analyzing data. I'll be covering them in that real-world order, starting first with getting data, or data sources.


Why the CIO must become the Chameleon In Chief
"The IT professional's longstanding focus on governance, strategy, and information means many technology executives have more in common with the finance chief than some of their more entrepreneurial executive peers, especially those in the marketing and sales departments," says Hand. But an insular style of leadership is simply not an option. As businesses look to gain a competitive advantage from digital transformation, engagement seems to be the watchword for IT leaders, who must continue to spend less time in the data centre and more time facing internal and external customers.


Tech-savvy NYPD cop allegedly hacked NYPD computer and FBI database to run a con
Although federal investigators don’t spell out how the cop was profiting from the scheme in the press release, the New York Daily News reported the “rogue” cop would collect information about traffic accidents and then pose as “an ambulance-chasing lawyer” when he contacted victims. “Numerous calls on his cellphone were associated with medical clinics, law firms and chiropractors, suggesting he was getting kickbacks for referrals.” After Katz accessed and gathered information from NYPD computer and law enforcement databases, he allegedly “contacted individuals who had been involved in traffic accidents and falsely claimed to be, among others, an attorney with the fictitious ‘Katz and Katz law firm’ who could assist them with potential legal claims.”



Quote for the day:

"A goal should scare you a little, and excite you a lot." -- Joe Vitale