Not too long ago, Apple added something phenomenal to the iPhone OS: a dashboard screen. If you have a Macintosh computer, you may be familiar with the dashboard that is available (regularly) by pressing F4. Otherwise, you can draw similarities to your Windows 7 Dashboard on the right hand side of your desktop, that shows you updates on your applications and widgets you add to it. Finding your dashboard on your iPhone is just as easy: just put your finger on the top of your iPhone screen, and drag down.

Here, in your dashboard, you will see all of the updates that has been pushed into such by your applications that desire to send you messages: things like new text messages, new updates to your subscribed magazines, your messages on payment applications. If you have reviewed a message set by an application by tapping on it, that message will automatically become deleted. However, if you don’t desire to go into the application to delete it, simply tap in the top right on the bar that categorizes that particular application, and tap again to clear all of the messages set by that application, and clear up your dashboard.

But, your dashboard isn’t all about your application. You not only get your messages, but you get important information set by default applications, such as the weather. If you don’t feel like scouting out your weather application amidst all your applications you have downloaded, simply go into your dashboard, and find out the forecast for the whole week, just by a simple swipe. Not only that, tickers for your stocks are displayed near the bottom of the dashboard.

This section of our beginning python training class always stumps students.  Firstly, because they need to know the difference between a function and a method.  Secondly, they need to understand object oriented programming concepts.  Thirdly, they need to realize that python has three types of methods.  Then they need to know how to use each method, which means they need to know the purpose of each method type.  Then they have to understand mutable versus non-mutable types.  The list goes on.  As part of our python tutorial, I hope to shed some light on this confusing topic.

To begin, the difference between a function and a method in python is that a method is defined within a class.  Here is an illustration:

#function

	def greeting():
	                print "Hello, I hope you're having a great day!"

	class HSGPrinter(object):
	                #method
	                def greeting(self): 
	                                print "Hello, I hope you're having a great day!"

As should be obvious, the second definition of greeting is encapsulated within the HSGPrinter class and is , therefore, refered to as a method.

The astute reader will notice that the greeting method contains one parameter named self.  For those who know C++ , Java or C#, self is equivalent to this i.e. it is a reference to the invoking object:

The world of technology moves faster than the speed of light it seems. Devices are updated and software upgraded annually and sometimes more frequent than that.  Society wants to be able to function and be as productive as they can be as well as be entertained “now”.

Software companies must be ready to meet the demands of their loyal customers while increasing their market share among new customers. These companies are always looking to the ingenuity and creativity of their colleagues to keep them in the consumer’s focus. But, who are these “colleagues”? Are they required to be young, twenty-somethings that are fresh out of college with a host of ideas and energy about software and hardware that the consumer may enjoy? Or can they be more mature with a little more experience in the working world and may know a bit more about the consumer’s needs and some knowledge of today’s devices?

Older candidates for IT positions face many challenges when competing with their younger counterparts. The primary challenge that most will face is the ability to prove their knowledge of current hardware and the development and application of software used by consumers. Candidates will have to prove that although they may be older, their knowledge and experience is very current. They will have to make more of an effort to show that they are on pace with the younger candidates.

Another challenge will be marketing what should be considered prized assets; maturity and work experience. More mature candidates bring along a history of work experience and a level of maturity that can be utilized as a resource for most companies. They are more experienced with time management, organization and communication skills as well as balancing home and work. They can quickly become role models for younger colleagues within the company.

Unfortunately, some mature candidates can be seen as a threat to existing leadership, especially if that leadership is younger. Younger members of a leadership team may be concerned that the older candidate may be able to move them out of their position. If the candidate has a considerably robust technological background this will be a special concern and could cause the candidate to lose the opportunity.

Demonstrating that their knowledge or training is current, marketing their experience and maturity, and not being seen as a threat to existing leadership make job hunting an even more daunting task for the mature candidate. There are often times that they are overlooked for positions for these very reasons. But, software companies who know what they need and how to utilize talent will not pass up the opportunity to hire these jewels.

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Big data is now in an incredibly important part of how many major businesses function. Data analysis, or the finding of facts from large volumes of data, helps businesses make many of their important decisions. Companies that conduct business on a national or international scale rely on big data in order to plot the general direction of their business. The concept of big data can be very confusing due to the sheer scale of information involved.  By following a few simple guidelines, even the layman can understand big data and its impacts on everyday life.

What Exactly is Big Data?

Just about everyone can understand the concept of data. Data is information, and information is everywhere in the modern world. Anytime you use any piece of technology you are making use of data. Anytime you read a book, skim the newspaper or listen to music you are also making use of data. Your brain interprets and organizes data constantly from your senses and your thoughts.

Big data, much like its name infers, simply describes this same data on a large sale. The internet allowed the streaming, sharing and collecting of data on a scale never before imaginable and storage technology has allowed ever increasing hoards of data to be accumulated. In order for something to be considered “big data” it must be at least 10 terabytes or more of information. To put that in perspective, consider that 10 terabytes represents the entire printed collection of material in the Library of Congress. What’s even more remarkable is that many businesses work with far more than the minimum 10 terabytes of data. UPS stores over 16 petabytes of data about its packages and customers. That’s 16,000 terabytes or the equivalent to 1,600 printed libraries of congress. The sheer amount of that data is nearly impossible for a human to comprehend, and analysis of this data is only possible with computers.

How do Big Data Companies Emerge?

All of this information comes from everywhere on the internet. The majority of the useful data includes customer information, search engine logs, and entries on social media networks to name a few. This data is constantly generated by the internet at insane rates. Specified computers and software programs are created and operated by big data companies that collect and sort this information. These programs and hardware are so sophisticated and so specialized that entire companies can be dedicated to analyzing this data and then selling it to other companies. The raw data is distilled down into manageable reports that company executives can make use of when handling business decisions.

The Top Five:

These are the five biggest companies, according to Forbes, in the business of selling either raw data reports or analytics programs that help companies to compile their own reports.

1. Splunk
Splunk is currently valued at $186 million.  It is essentially a program service that allows companies to turn their own raw data collections into usable information.

2. Opera Solutions
Opera Solutions is valued at $118 million. It serves as a data science service that helps other companies to manage the raw data that pertains to them. They can offer either direct consultation or cloud-based service.

3. Mu Sigma
Mu Sigma is valued at $114 million.  It is a slightly smaller version of Opera Solutions, offering essentially the same types of services.

4. Palantir
Palantir is valued at $78 million.  It offers data analysis software to companies so they can manage their own raw data analysis.

5. Cloudera
Cloudera is valued at $61 million.  It offers services, software and training specifically related to the Apahce Hadoop-based programs.

The software and services provided by these companies impact nearly all major businesses, industries and products. They impact what business offer, where they offer them and how they advertise them to consumers. Every advertisement, new store opening or creation of a new product is at least somewhat related to big data analysis. It is the directional force of modern business.

Sources:
http://www.sas.com/en_us/insights/big-data/what-is-big-data.html

http://www.forbes.com/sites/gilpress/2013/02/22/top-ten-big-data-pure-plays/

http://www.whatsabyte.com/

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