The Zen of Python, by Tim Peters has been adopted by many as a model summary manual of python's philosophy.  Though these statements should be considered more as guideline and not mandatory rules, developers worldwide find the poem to be on a solid guiding ground.

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!

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/

Related:

How does Google use Python?

Top Innovative Open Source Projects Making Waves in The Technology World

Is the U.S. the Leading Software Development Country?

How to Keep On Top Of the Latest Trends in Information Technology

The field of information technology is in many ways perfectly suited for entrepreneurship. Many highly successful enterprises started with a lone IT professional venturing out on their own and starting up their own company. If you have computer science skills and want to explore alternative options outside the corporate arena you should seriously consider going into business for yourself. Businesses may be more willing to hire you as a contractor rather than as a full-time worker. There are certain IT jobs that are perfect for individuals who want to be self-employed, they include:

• Working as a Consultant
Large IT departments are not as necessary for corporations as they were at the start of the internet era; this is partly due to the trend towards cloud computing. Consultants are often brought in to handle the need for tech expertise when companies downsize or eliminate their IT departments. A consultant may work for several different clients at the same time, be on call for various disciplines or be commissioned for specific projects.

• Web Entrepreneurship
The ease of building a website and the fact that web hosting is relatively affordable means that it does not take a lot of know-how to start your own online empire. You can sell products or services, or start your own online community. Another option is to start selling goods via auction sites or on sites that sell advertising space. You will need an understanding of marketing and of search engine optimization so that you can draw visitors to your site.

• Programming Apps for Mobile Devices
The future of the Internet is in mobile devices. Statistics show that much of the world will be using mobile devices and smart phones to handle their surfing needs in the near future. If you have the skills to program the apps used on these devices, you could be among those riding the wave of this trend.

It is not impossible to start an Information Technology company with very little startup capital. Getting it off the ground in terms of online visibility will require focus to detail, knowing your target market, a consistent campaign to build a client list and a solid reputation.