Voice recordings are useful at any point in time. If you want to save a lecture (or presentation) that you are attending, or record a voiceover for a project, the iPhone can be your solution. You don’t have to use an old tape recorder, or a standalone recorder. The iPhone’s fantastic technology records high quality voice recordings on demand, whenever you need it.

To get started, look for an application named “Voice Memos.” Most likely, this particular application is found in your Utilities category by default. Once you open it up, you are greeted by a large microphone, indicating you are in the correct application. When you want to start recording, simply tap on the large red button in the bottom left, and you are on your way to begin recording. What is important about recording voices on this application to the highest degree of quality, ensure that your meter in the bottom is within the middle range; with the pointer in the red zone, your recording will be awfully loud, while otherwise, it will be too quiet. Finished recording? Simply tap on the square button, and you have your recording.

What can you do with these recordings? Once you have finished recording, you are able to now share this recording through email or even in a text message; email it to yourself so you can save it on your computer, and listen to it later, or start editing it to put into a movie production, or text it to a friend for their needs.

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?

Applications are becoming more and more sophisticated as languages such as Python open the doors to the world of programming for people who have the creative vision but always felt actually writing code was beyond their grasp.

A large part of any programs success is based on how well it can react to the events which it has been programmed to understand and listen for.

A good example of an event would be when the user clicks a button on the applications window. What happens when that button is clicked?

Well, the first thing that happens is the operating system sends out a message to let any listening software know that the button was clicked. Next, your application needs to do something in response to that event.

In Python, we can create three types of methods in a class:  instance or regular method, classmethod and staticmethod.  Instance methods are associated, as the name infers, with an instance or object of the class and take self as the first parameter.  Classmethods take a reference to the class, cls, as the first parameter of the class.  Staticmethods, for the most part, are convenience methods that could be declared as functions since they really do not have much to do with the class itself.  They were probably added at some time after the advent of Python in order to make the language more object oriented i.e. minimize the number of free floating functions. 

Refer the our article static, class and regular methods in Python for a detailed explanation on this subject.