It is no secret that the world of business is evolving at what can only be called a blistering pace. What worked yesterday may not function today and it could very well be outdated tomorrow. There is perhaps no better example of this modernization than in the world of evolving digital strategies. Of course, implementing a successful digital strategy to meet the core needs of any business can be easier said than done. This is the primary reason why the task is generally outsourced to professionals in the industry; they appreciate the bespoke needs and infrastructure of unique companies.
At the very first TDWI Conference, Duane Hufford described a phenomenon he called "embedded data", now more commonly called "overloaded data", where two or more concepts are stuffed into a single data field (“Metadata Repositories,” TDWI Conference 1995). He described and portrayed in graphics three types of overloaded data. Almost 20 years later, overloaded data remains rampant but Mr. Hufford's ideas, presented below with updated examples, are unfortunately not widely discussed.
It is no secret that the digital marketplace is expanding at what can only be called a breakneck pace. So, the expectations of the customer are rising dramatically. Meeting these needs can make all of the difference in the world between a failed business and one which is destined for success. Unfortunately, I have seen many enterprises that continue to struggle with adapting to such technologies. Not only are potential clients increasingly critical of how a product or service is presented, but the inclusion of mobile platforms such as smartphones and tablets also needs to be addressed.
I had pondered writing a post called "Requirements Decay" about how requirements don't last forever. In my research I found that such a post, complete with "my" words "requirements decay" and "requirements half-life", had already been done comprehensively here. In a compact argument underpinned by half-life mathematics, the anonymous author proposes that a requirement isn't likely to stand forever and explores the implications.
“Why can’t I just say, ‘do this because I said so?!!’ Shouldn’t that be enough?!!’” This is what my friend Jonah and fellow parent of a three-year-old said to me recently, as we were swapping stories about the trials and tribulations of raising kids. Or more specifically, the trials and tribulations of getting them to behave the way we want. As Jonah noted with some exasperation, everything—from putting on their shoes, to eating their carrots, to, for goodness sake, stopping the endless bickering with their siblings—seems to be a series of negotiations.
Should you use Robolectric with Gradle for your Android builds, you may find your tests failing when the first test using the RobolectricTestRunner is attempted to be used if you sit behind a strict firewall or proxy.
My current client has these policies in addition to its own Nexus repository that proxies most other public repositories such as OSS and repo1. We configured our Gradle scripts to leverage this repository:
"Poka-Yoke", a Japanese term that means "mistake-proofing," can be used to increase the quality of your software systems. Learn about different strengths of poka-yoke systems, and tips to be more effective in using poka-yoke systems in your code.
You are looking to adopt Swift as your language for developing iOS but you already have a great project written in Objective-C that works great and has been thoroughly tested. That is where interoperability comes in. You can start adding Swift classes to your code now. This tutorial will get you started in connecting your Swift and Objective-C code to each other.
An android programmer is an android programmer. The role is the skill set. But what skill sets are useful for a Data Scientist or a Data Analyst? Does this make staffing and executing projects in the analytics space more difficult? Is data analysis a science, or is the science in exploring data to prepare it for further analysis?