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

When businesses are trying to expand and require professionals to lead teams, terminology may get in the way of who performs what roles. When it comes to information technology (IT), new and vital professionals may seem hard to differentiate between one another. However, there are key differences between specific professionals needed with IT departments. Here are the responsibilities that differentiate between an IT manager and an IT project manager.

IT Managers

IT managers are the leaders of the entire IT infrastructure a business has to function properly. The IT manager must lead the entire IT department to regulate and maintain the IT network for the business. As a manager, this IT professional corresponds with other departments in the business about how the IT department is implementing the goals the business is aiming toward. In addition, the manager must be fiscally responsible and answer to executives and financial officers in the business the reasons behind certain costs and investments. Because of the dual computer technology and business acumen this profession requires, many IT managers have a Master of Business Administration (MBA) related to information technology.

IT Project Managers

I’ll get straight to the point.  Why should companies invest more in management training?  Here are 10 simple reasons.

1) An employee’s relationship with his or her direct manager is the most important single factor in employee engagement.

2) Engaged employees are happier and more productive.  Disengaged employees are frustrated and more disruptive.

3) Because there’s no widely agreed-on skillset for management (good managers come in all shapes and sizes), there’s an assumption everyone knows how to do it.  This is akin to someone who’s never driven before being given keys to a car and told: “Drive.”  (Many many years ago, this is how I first learned to manage.  I blundered my way through it.  Trial and error.  It wasn’t pretty.)