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Wednesday 19 December 2018
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What are the Next Steps for Big Data?

What are the Next Steps for Big Data?

As business leaders we always ask ourselves.. what are my next steps? 

So, we ask the same of Big Data, what are the next steps in regards to technology, strategy, and requirements.

 

The world has careened, kicking and screaming, into the bright, new dawn of the computer age. Now more than ever, businesses and governments have a need to collect, analyze, and use data collected by computers and algorithms. But why do they need big data in the first place? The reasons are endless. Take, for example, the need for government security.

The U.S. Army Intelligence and Security Command has a need to track national security threats in real-time. The CDC tracks national influenza infection rates using big data systems and software. Private businesses want to aggregate big data regarding consumer activity and purchasing decisions. But with all of this information available, how can it be quantified and analyzed efficiently? What is the future of technology, and the next steps for big data databases?

Databases are the key to solving the challenges to Big Data! 

Data has been around for decades but was ‘analog’; put into spreadsheets and analyzed by hand. Since the 1990s, the need for data, the availability of data, and the problems surrounding its storage and organization has become much bigger. Instead of Lake Erie, businesses and governments are dealing with data the size of the Pacific Ocean. The scaling requirements have gotten more complex.

Let’s go back several years to 2009, when U.S. Army Intelligence and Security Command wanted to track threats to national security in real-time. The programs to handle this type of scale didn’t exist in 2009. NoSQL and classical relational systems wouldn’t work regarding the need for real-time tracking. In response, a new big data database was built, and it was based around the idea of a Graphic Processing Unit, or GPU.

A GPU gives the user the ability to track present data in real-time. GPUs use something called parallel structure that makes them more efficient than a general CPU.

In addition to the ability to track data in real-time, GPUs, as a ‘next generation’ big data database, have much better storage capabilities than previously designed databases. With more and more information pouring into the data ocean, GPUs will be utilized in the coming years since they can scale much better than earlier technology.

With modern technology, aggregating and collecting the data isn’t much of an issue. The problems are storage (which GPUs can handle) and analysis and organization. Analysis and organization is where new blockchain technology will become a major player in the growing use of big data databases.

What can Blockchain do for Big Data.. in short, A lot! 

Blockchain technology is a list of records, linked together, and secured with cryptography. The interesting thing about blockchain regarding organization and security of big data is that an incorrect block at the beginning of the chain will never reach the following blocks.

This type of technology would have massive implications in certain fields, such as healthcare. If a patient has incorrect information on one block, it will never make it to any subsequent blocks, thus keeping the entire chain of data incorruptible and organized.

In the digital age, governments and businesses are finding new needs for storing, analyzing and organizing the rising tide of data. To accurately sift through all of this information and bring clarity and efficiency to government and business processes, the next step for big data is utilizing new and emerging technology.

GPUs and blockchain technology will be at the forefront of emerging big data databases. As computers and algorithms begin to play bigger roles in day-to-day functions, this will mean consumers and citizens will benefit from reliable, accurate information with the potential to save lives and bring streamlined systems to everyday living.



Tracy is responsible for the marketing of Telliant Systems. Always looking for ways to increase Telliant Systems' brand. She loves finding ways to show how software development can make our daily lives better and more productive.


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