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Technologies Revolutionizing The Big Data Industry

Published on 02 December 14
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More is more with Big Data: the more data collected, the more insight that can be gleaned from it. Based on this premise, the Big Data industry is one of constant growth and innovation that seeks to support and enhance the informational needs of organizational bodies everywhere, be they corporations, educational institutions or otherwise.

Accordingly, revolutionary technologies are at the forefront of Big Data both as standalone applications/services, and as refinements of pre-existing solutions. Below, weâve listed a sampling of Big Data technologies that are revolutionizing the industries leveraging them.

Cloud Computing

Without the cloud as the integral technology that it is today, the Big Data industry would be, at best, inaccessible to those without the deepest of pockets. Thanks to the cloud, weâre able to handle extremely complex types and amounts of data where we otherwise couldnât. Far beyond just storing/retrieving data, the cloud allows for efficient and cost-friendly computational power that gives superior analytical insight to vast data sets.

The cloud affords us mass collaboration and shared sets of data to allow for more expansive insights, as well as increased productivity with significantly less time spent on duplicate results and broken research models. Going forward, you can expect the cloud to remain perhaps the most integral technology of Big Data, controlling everything from in-house data to public-facing resources (Web applications, data sets, etc.).

Hadoop

Hadoop is a platform with which the future of cloud computing can really blossom. Itâs composed of several features, the two most important being its file system (HDFS, or Hadoop Distributed File System) and its operating system (YARN, or Yet Another Resource Negotiator). Hadoop allows for an abundance of new opportunities with analytics and data/resource management.

Data-Correlated Prediction

Predictive analysis is one of the most anticipated technologies for businesses and organizations with vast data sets. Imagine being able to have a product ready for a customer before they even order it, based solely on their prior purchasing habits from you as a merchant. Another example would be a hospital in a particular city being prepared to immediately treat certain illnesses based on correlational data from social media streams and shared patient databases in surrounding areas. Big Data allows for data-correlated prediction technologies to not only exist, but to quickly flourish over time.

Location Awareness

Having the ability to know exactly where a customer is the moment they interact with you and your offerings is another sought-after technology being refined in the Big Data industry. Social media has allowed for a key component of location awareness to take hold, but being able to take location data and apply it to always-ready data sets is a future staple of Big Data that will allow companies to create new opportunities with customers in a near-real-time context.

Online and Offline Data Convergence

One of the primary sources of information loss in the customer acquisition cycle is the transference from online to offline, i.e., a potential customer discovering you via the Web, researching the product theyâre interested in, then making the purchase offline by picking up the phone and calling a representative. Emerging technologies are allowing for cross-pollination of online and offline data to create one cohesive set of data from which to analyze and create future opportunities.

Conclusion

The aforementioned is but a minor subset of important technologies revolutionizing the Big Data industry. As you can see, these technologies allow us to do more with copious amounts of data than we ever could have dreamed of doing otherwise. Big Data is still a very young concept in the grand scheme of things, but with some of the worldâs most successful companies and institutions successfully leveraging Big Data, itâs clear that its potential reaches far into the future of computing, business and research.


More is more with Big Data: the more data collected, the more insight that can be gleaned from it. Based on this premise, the Big Data industry is one of constant growth and innovation that seeks to support and enhance the informational needs of organizational bodies everywhere, be they corporations, educational institutions or otherwise.

Accordingly, revolutionary technologies are at the forefront of Big Data both as standalone applications/services, and as refinements of pre-existing solutions. Below, weâve listed a sampling of Big Data technologies that are revolutionizing the industries leveraging them.

Cloud Computing

Without the cloud as the integral technology that it is today, the Big Data industry would be, at best, inaccessible to those without the deepest of pockets. Thanks to the cloud, weâre able to handle extremely complex types and amounts of data where we otherwise couldnât. Far beyond just storing/retrieving data, the cloud allows for efficient and cost-friendly computational power that gives superior analytical insight to vast data sets.

The cloud affords us mass collaboration and shared sets of data to allow for more expansive insights, as well as increased productivity with significantly less time spent on duplicate results and broken research models. Going forward, you can expect the cloud to remain perhaps the most integral technology of Big Data, controlling everything from in-house data to public-facing resources (Web applications, data sets, etc.).

Hadoop

Hadoop is a platform with which the future of cloud computing can really blossom. Itâs composed of several features, the two most important being its file system (HDFS, or Hadoop Distributed File System) and its operating system (YARN, or Yet Another Resource Negotiator). Hadoop allows for an abundance of new opportunities with analytics and data/resource management.

Data-Correlated Prediction

Predictive analysis is one of the most anticipated technologies for businesses and organizations with vast data sets. Imagine being able to have a product ready for a customer before they even order it, based solely on their prior purchasing habits from you as a merchant. Another example would be a hospital in a particular city being prepared to immediately treat certain illnesses based on correlational data from social media streams and shared patient databases in surrounding areas. Big Data allows for data-correlated prediction technologies to not only exist, but to quickly flourish over time.

Location Awareness

Having the ability to know exactly where a customer is the moment they interact with you and your offerings is another sought-after technology being refined in the Big Data industry. Social media has allowed for a key component of location awareness to take hold, but being able to take location data and apply it to always-ready data sets is a future staple of Big Data that will allow companies to create new opportunities with customers in a near-real-time context.

Online and Offline Data Convergence

One of the primary sources of information loss in the customer acquisition cycle is the transference from online to offline, i.e., a potential customer discovering you via the Web, researching the product theyâre interested in, then making the purchase offline by picking up the phone and calling a representative. Emerging technologies are allowing for cross-pollination of online and offline data to create one cohesive set of data from which to analyze and create future opportunities.

Conclusion

The aforementioned is but a minor subset of important technologies revolutionizing the Big Data industry. As you can see, these technologies allow us to do more with copious amounts of data than we ever could have dreamed of doing otherwise. Big Data is still a very young concept in the grand scheme of things, but with some of the worldâs most successful companies and institutions successfully leveraging Big Data, itâs clear that its potential reaches far into the future of computing, business and research.




Research references/sources used:

https://www.youtube.com/watch?v=qsvIKgn_CxE

http://www-01.ibm.com/software/data/infosphere/hadoop/

http://www.gartner.com/technology/topics/big-data.jsp

http://www.informationweek.com/strategic-cio/executive-insights-and-innovation/big-data-in-2014-top-technologies-trends/d/d-id/1113092

http://blogs.wsj.com/digits/2014/01/17/amazon-wants-to-ship-your-package-before-you-buy-it/

http://www.zdnet.com/blog/big-data/why-is-big-data-revolutionary/281

This blog is listed under Cloud Computing and Data & Information Management Community

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