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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For many people, one of the most exciting and challenging career choices is computer programming. There are several ways that people can enter the computer programming profession; however, the most popular method has traditionally been the educational route through an educational institution of higher learning such as a college or technical school.

Even though many people think of computer programmers as individuals with a technical background, some programmers enter the computer programming profession without a structured technical background. In addition, after further investigation several interesting facts are uncovered when a profile of the best computer programmers is analyzed.

When observing how the top programmers in the profession work, there are four characteristics that tend to separate the top programmers from the average programmers. These four characteristics are:

1.Creativity.
2.Attention To Detail.
3.Learns New Things Quickly.
4.Works Well With Others.

Creativity.

Being a top computer programmer requires a combination of several unique qualities. One of these qualities is creativity. In its very essence, computer programming is about creating programs to accomplish specific tasks in the most efficient manner. The ability to develop computer code to accomplish tasks takes a certain level of creativity. The top computer programmers tend to have a great deal of creativity, and they have the desire to try things in a variety of ways to produce the best results for a particular situation.

Attention To Detail.

While creativity is important for top programmers an almost opposite quality is needed to produce great computer programs on a consistent basis, this quality is attention to detail. The very nature of computer programming requires the need to enter thousands of lines of computer programming code. What separates many top programmers from average programmers is the ability to enter these lines of code with a minimum amount of errors and just as importantly test the code to catch any unseen errors. Top computer programmers have the necessary attention to detail to successfully create and enter the necessary computer code project after project.

Learns New Things Quickly.

The technology field is constantly changing. Almost daily new technology innovations are being developed that require computer programmers to learn new technology or enhancements to current technology on a regular basis. The top computer programmers are able to learn new technology or enhancements quickly, and then they are able to apply what has been learned to their current and future programming projects in a seamless manner.

Works Well With Others.

There are several differences between top computer programmers and other programmers. However, one of the biggest differences is the ability to work well with others. By its very nature, computer programming requires programmers to spend a lot of time alone developing computer code, but the top computer programmers are able to excel at this aspect of computer programming along with being able to work well with other people.

Regarding computer programmers, the top programmers approach and handle their jobs differently than other programmers, and these differences set them apart from the other programmers. For any average programmers who have the desire to excel as a computer programmer, they must understand and embrace the characteristics of top programmers.

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Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”