One of the most recent updates to the iPhone, and more specifically the operating system that is packaged with the iPhone, iOS, brought one of the most fantastic and phenomenal updates ever: an update to Maps. Maps has been used as an application that provides an easy way to find routes, and (obviously) maps about certain areas, businesses in the local vicinity, and also leaving pins on favorited locations, or pins where you have explored, and for many other reasons. However, although Maps has always been a great way to travel with, it has always been redundant to travel with, also. When you used Maps a while ago, you had to route your map, and then manually click each next button as you reached each turn or freeway exit, and the like. So, if you had to turn left on a certain street, you had to tell your phone you had done so, so it would give you the next directions. As a result, it could become very dangerous to always have your phone out, looking at it, while you are on a high-speed freeway. But, the newest update solved that, and brought a great amount of new features.

Using Maps GPS

Using Maps is as easy as it gets. Most of the time, when you are using Maps, you are using it to search for a location, and finding a way to get there. To start off, let’s search for the nearest mall, and routes to get there. Simply search a nearby mall you know about, or search the general word “mall” by tapping on the top text box, and typing in mall, and searching. Pins will drop down on the screen, and locating the mall by zooming into certain streets and locations will help you find the mall you want. Once you find the mall you desire to go to, click on the blue arrow, and scroll down, and tap on the button that says “Directions To Here.”

As a result of tapping on that particular button, a new window should show up asking where your starting location is. On default, this location is your current location; if it is anything else, simply type in the starting location into the top address bar, such as your house. Once you are ready to go, tap on route, and you should be ready to go. Well, not exactly. One of the best features that has been implemented in the new system is suggested routes, and alternative routes. If you don’t like to drive on certain streets, or roads, the system provides you with different methods to get to your destination, which may avoid a road you don’t feel like driving on that certain day, or time, or you simply don’t want to take the freeway. It’s all okay, as Maps provides you with many different routes to take. Once you find the route you want (by tapping on the certain route’s outline), click start, and you should be ready to go. Make sure you turn up your volume so you can hear the directions!

Maps for Alternative Transportation

Cloud computing is the recent rage in the IT industry. According to the report by Forbes, the estimated global market for cloud computing is expected to reach $35.6 billion in 2015, from the $12.1 billion market of 2010.

How it began

The idea of cloud computing was inspired by the concept of “utility computing” which introduced the idea of computing using the virtual servers. These virtual servers do not actually exist anywhere physically and can be moved anywhere without causing any disturbance to the end users. Thus it minimizes the cost involved on the devices to a great extent and provides innumerable benefits to the companies that adopt this system.

Cloud Computing Types

When making a strategic cloud decision, organizations can follow either one of two ideologies: open or closed.

In the past, major software technologies have been widely accepted because an emerging market leader simplified the initial adoption.  After a technology comes of age, the industry spawns open alternatives that provide choice and flexibility, and the result is an open alternative that quickly gains traction and most often outstrips the capabilities of its proprietary predecessor.

After an organization invests significantly in a technology, the complexity and effort required steering a given workload onto a new system or platform is, in most cases, significant. Switching outlays, shifting to updated or new software/hardware platforms, and the accompanying risks may lead to the ubiquitousness of large, monolithic and complex ERP systems – reason not being that they offer the best value for an organization, but rather because shifting to anything else is simply – unthinkable.

There’s no denying that these are critical considerations today since a substantial number of organizations are making their first jump into the cloud and making preparations for the upsetting shift in how IT is delivered to both internal and external clientele. Early adopters are aware of the fact that the innovation brought about by open technologies can bring dramatic change, and hence are realizing how crucial it is to be able to chart their own destiny.

The interpreted programming language Python has surged in popularity in recent years. Long beloved by system administrators and others who had good use for the way it made routine tasks easy to automate, it has gained traction in other sectors as well. In particular, it has become one of the most-used tools in the discipline of numerical computing and analysis. Being put to use for such heavy lifting has endowed the language with a great selection of powerful libraries and other tools that make it even more flexible. One upshot of this development has been that sophisticated business analysts have also come to see the language as a valuable tool for those own data analysis needs.

Greatly appreciated for its simplicity and elegance of syntax, Python makes an excellent first programming language for previously non-technical people. Many business analysts, in fact, have had success growing their skill sets in this way thanks to the language's tractability. Long beloved by specialized data scientists, the iPython interactive computing environment has also attracted great attention within the business analyst’s community. Its instant feedback and visualization options have made it easy for many analysts to become skilled Python programmers while doing valuable work along the way.

Using iPython and appropriate notebooks for it, for example, business analysts can easily make interactive use of such tools as cohort analysis and pivot tables. iPython makes it easy to benefit from real-time, interactive researches which produce immediately visible results, including charts and graphs suitable for use in other contexts. Through becoming familiar with this powerful interactive application, business analysts are also exposing themselves in a natural and productive way to the Python programming language itself.

Gaining proficiency with this language opens up further possibilities. While interactive analytic techniques are of great use to many business analysts, being able to create fully functioning, independent programs is of similar value. Becoming comfortable with Python allows analysts to tackle and plumb even larger data sets than would be possible through an interactive approach, as results can be allowed to accumulate over hours and days of processing time.

This ability can sometime allow business analysts to address the so-called "Big Data" questions that can otherwise seem the sole province of specialized data scientists. More important than this higher level of independence, perhaps, is the fact that this increased facility with data analysis and handling allows analysts to communicate more effectively with such stakeholders. Through learning a programming language which allows them to begin making independent inroads into such areas, business analysts gain a better perspective on these specialized domains, and this allows them to function as even more effective intermediaries.

Related:

Who Are the Main Players in Big Data?