|
|
Optimize with a SATA RAID Storage Solution
Range of capacities as low as $1250 per TB. Ideal if you currently rely on servers/disks/JBODs
Page 3 of 5
This usually produces cleaner, simpler code. While programmers can write convoluted code in any language, the newer stacks often require less extra glue code and version testing. Some of my code for smartphone apps goes through dozens of version tests to make sure it's doing the right thing for the right version. New stacks don't have this extra complexity.
There are dozens of new HTML5 projects that handle many of the basic details of creating a website or a mobile phone app. The code, which is often called a framework or a scaffolding, organizes the content in pages and offers a transition mechanism ruled by menus. Some of the most popular are jQuery Mobile, Sencha Touch, and Titanium, but a number of other tools are emerging. Many of the most popular CMS stacks like WordPress or Drupal sport themes that are tuned to the mobile environment and often use some of the same code.
While these new code stacks are clean, they often achieve this by tossing aside old platforms. It's easy for new tools to let people write simple, elegant code. They just ignore the older hardware and the older versions of the operating systems. Voilà! Of course they're simpler and faster because they only work with the pre-release code shipping at this moment.
The glitches with the HTML5 frameworks start appearing if you use an older browser or one that's not as standards-compliant. Suddenly, the menus start appearing in weird places and half of the text is off because the CSS instructions don't work. Sometimes the new needs to get along with the old, and it's a problem when the new code insists that it can only solve things one way.
Before you launch an experiment in this area, know where you can afford to support a subset of technologies out there.
Cutting-edge experiment No. 4: Chewing up data with R
From cleaner Web design to more sophisticated analysis of big data, the R language lies at the core of some of the most popular new tools designed to use math to solve problems and take care of customers.
The collection of tools around R is more than just a language with predefined functions for common statistical formulae; they're
entirely new ways of thinking about the problem and finding a solution.
The statistical models inside big data analysis packages, for instance, can suss out and flag complex patterns and take advantage of all the power a modern cluster of computers can deliver. They replace the old mechanisms that would simply sort or look for maxima. Working with cutting-edge statistical software means you can do deeper analysis and find signals when the old code just saw noise.
When these new insights appear, they can save businesses billions of dollars. They help stores detect local tastes and ensure that the shelves are better stocked with the colors, patterns, and sizes that are demanded by the people in the neighborhood. They offer marketing engineers the opportunity to do a better job at guessing how much advertising is enough. Anywhere there's data, there's a chance to find siginificant insights.