With the rise of the smart phone, many people who have long seen themselves as non-gamers have began to download and play to occupy themselves throughout the day. If you're a game developer who has a history of writing your code in C#, then perhaps this still emerging market is something you should consider taking advantage of. This, however, will require the familiarization with other programming languages.

One option for moving away from the C# language is to learn Java. Java is the programming used for apps on the android platform, billions of phones run on this programming language.

If you want to break into the android market, then learning Java is an absolute must.

There are both some pros and some cons to learning java. Firstly, if you already know C# or other languages and understand how they work, then java will be relatively easy to learn due to having similar, but quite simplified, syntax to C-based languages, the class library is large and standardized, but also very well written, and you might find that it will improve the performance and portability of your creations. Not to mention, learning java opens you up to the entirety of the android app and game market, a very large and still growing market that would otherwise stay closed off to you. That's too much ad and sale money to risk missing out on.

The few cons that come with learning the language is that, when coming from other languages, the syntax may take some getting used to. This is true for most languages. The other problem is that you must be careful with the specifics of how you write your code. While java can be written in a very streamlined fashion, it's also possible to write working, but bulky, code that will slow down your programs. Practice makes perfect, and the knowledge to avoid such pitfalls within the language.

If you wish to develop for the iOS on the other hand, knowledge of Objective C is required. The most compelling reason to learn Objective C is the market that it will open you up to. According to the website AndroidAuthority.com, in the article "Google play vs. Apple app store", users of iPhones and other iOS devices are much more likely to spend money on apps rather than downloading free ones.

Though learning Objective C might be a far jump from someone who currently writes in C#, it's certainly learn-able with a little bit of practice.

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In the ever changing landscape of software programming, it is not surprising that developers and employees have a different set of preferences for desired skills.  However the number one language that developers want to learn according to a survey of developers by technical recruiter, Hacker Rank is Python. This is not a surprise considering that Python has been in demand for several years and programmers tend to really enjoy this language for clear syntax, good OOP support and great shortcuts. Python, named “the language of the year” in 2007 and 2010 in the TIOBE Index and has climbed to #4 status in May of 2018.

According to the study, employers want developers who:

-  Have problem-solving skills, such as the ability to break down large, complex problems.
- Are proficient in their programming language and debugging.
- Can design systems.
- Can optimize performance.
- Have experience in reviewing and testing code.
- Are proficient in database design

Surprisingly, formal education is not the deciding factor when it comes to what companies care about the most. People with computer degrees or certifications on a resume are not necessarily a first choice for hiring managers. Others that have years of experience even if those individuals are partially self-taught in the field stand to be taken seriously in the field.   For those individuals with a passion to learn and master a skill, there are ample opportunities with smaller to mid-sized companies.

Some interesting FAQ’s from the study:

    On average, developers know 4 languages, and they aspire to learn 4 more.
    Younger developers between 18 and 24 plan to learn 6 languages.
    Folks older than 35 only plan to learn and additional 3 languages.
    The top languages developers said they will learn were, Go, Python, Scala, Kotlin, and Ruby.
    There is a large gap between employers seeking developers that know React than there are folks that can do it.

So, Why Learn Python?
It is now the most popular introductory teaching language in U.S. universities.  Python is easy to use, powerful, and versatile, making it a great choice for beginners and experts alike. It allows you to think like a programmer and not waste time understanding difficult syntax that other programming languages can command. And, because of its rapid growth, many developers contribute to the Python community and share Python libraries making creativity that much more a reality

Data has always been important to business. While it wasn't long ago that businesses kept minimal information on people who bought their products, nowadays companies keep vast amounts of data. In the late 20th century, marketers began to take demographics seriously. It was hard to keep track of so much information without the help of computers.

Only large companies in the '60s and '70s could afford the research necessary to deliver real marketing insight. The marketers of yesteryear relied upon focus groups and expensive experiments to gauge consumer behavior in a controlled environment. Today even the smallest of companies can have access to a rich array of real-world data about their consumers' behavior and their consumers. The amount of data that is stored today dwarfs the data of only a few years ago by several orders of magnitude.

So what kind of information are businesses storing for marketing purposes? Some examples include:

- Demographic information — age, gender, ethnicity, education, occupation and various other individual characteristics.

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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