Have you ever waited until the last minute to complete a critical project, only to find out that you have to process significantly more information than you can actually handle? You watch the clock count the hours and then minutes down to your deadline, but there is still so much material in front of you that you still have left to analyze that you want to just pull out your hair. If you answered yes, you have experienced the concept of big data first hand.
The term “big data” refers to data sets that are so incomprehensively large and complex that they are practically impossible to process, even when using database management tools or other traditional data processing applications.
Scientists in many fields—including genomics, physics and biological research, to name a few—continuously encounter obstacles in their research due to having to handle extremely large sets of data. These obstacles result in budget and time management setbacks and can be incredibly frustrating.
There is positive news, though: as of 2012, limits on the size of data sets that are feasible to process in a moderate amount of time were as high as a few exabytes of data. If you are unfamiliar with the concept of the exabyte, it is the equivalent to one quintillion bytes. That’s pretty massive!
Big data is growing exponentially larger every day. This is partly due to the fact that data is being collected on mobile devices, remote sensors, software logs, cameras, microphones and wireless networks, to name a few. And the number of devices collecting data continues to increase at an impressive pace. Consider how much information you collect on a daily basis; you call coworkers, text friends, take pictures of your dog and check Facebook before you go to bed.
Amazingly, the world’s technological ability to store information has practically doubled every forty months since the 1980s. In 2012, 2.5 quintillion bytes of data were created every day!
What is considered to be big data varies greatly depending upon the capabilities of the organization in question that is managing the set and on the capabilities of the applications that will be used to process and analyze the data set.
An example of the concept of big data in science is the Large Hadron Collider. This collider is famous for being the world’s largest and highest-energy particle accelerator; 150 million sensors deliver data 40 million times per second, and there are approximately 600 million collisions per second. That’s a lot of data!
Researchers filter out 99.999% of the unnecessary collected data, but this still creates 100 collisions of interest per second. If all data were to be collected for analysis, it would exceed 500 exabytes per day. To put this number into perspective, this is equivalent to 500 quintillion bytes per day—almost 300 times higher than all other sources in the world combined.
We are currently living in an age where having a title such as “Data Scientist” is not far from reality. The convergence of two groundbreaking technologies—big data and cloud computing—are creating far-reaching implications that will soon change the world.
Big data is extremely important in allowing organizations to better anticipate and react to consumer demands. But when unprocessed data accounts for at least 80% of the world’s information, many companies are making critical decisions with just 20% of the data they have analyzed. This certainly is not ideal.
The cloud hosting computing model provides a perfect match for big data since cloud computing provides absolutely unlimited resources on demand. Cloud-based solutions purchased from providers give companies the capability to access processing applications on remote networks that were not previously available and allow them to access these applications via web browsers or even mobile applications.
The Cloud helps corporations to save money by providing a means to store massive quantities of data without a massive cost. In the Cloud, hardware and software do not need to be purchased or even stored in-house, improving both the company budget and available office space. Cloud solutions reduce the energy consumption of servers, thus lowering overhead and reducing carbon footprints.
Also, storing data within the cloud allows the information to be accessed across a wide spectrum of devices—desktops, tablets, mobile phones and more, all while being strongly protected against natural disasters and malicious attacks.
When cloud computing and big data are combined to create a convenient, versatile and automated solution, profit generation opportunities are sky-high.
Since 1994, Atlantic.Net has been providing premiere hosting services to corporations, small businesses and personal clients. We have always been one step ahead of the latest trends in technology, and we have taken advantage of this stronghold by offering scalable, secure and budget-friendly cloud servers. To learn more about how you can try a cloud server with absolutely no commitment, contact us today at 800-521-5881.