When folks refer to “Big Data” these days, what is everyone really talking about? For several years now, Big Data has been THE buzzword used in conjunction with just about every technology issue imaginable. The reality, however, is that Big Data isn’t an abstract concept. Whether you like it or not, you’re already inundated with Big Data. How you source it, what insights you derive from it, and how quickly you act on it will play a major role in determining the course—and success—of your company. Let’s talk specifics…
Handling the increased volume, variety and velocity (the “3V/s”) of data requires a fundamental shift in the makeup of the platform required to capture, store, and analyze the data. A platform that’s capable of handling and capitalizing on Big Data successfully requires a mix of structured data-handling relational databases, unstructured data-handling NoSQL databases, caching solutions, and map reducing Hadoop-style tools.
As the need for new technologies to handle the “3V/s” of Big Data has grown, open source solutions have become the catalysts for innovation, generating a steady launch of new, relevant products to tackle Big Data challenges. Thanks to the skyrocketing pace of innovation in specialized databases and applications, businesses can now choose from a variety of proprietary and open source solutions, depending on the database type and their specific database requirements.
Given the wide variety of new and complex solutions, however, it’s no surprise that a recent survey of IT professionals showed that more than 55% of Big Data projects fail to achieve their goals. The most significant challenge cited was a lack of understanding of and the ability to pilot the range of technologies on the market. This challenge systematically pushes companies toward a limited set of proprietary platforms that often reduce the choice down to a single technology. Perpetuating the tendency to seek one cure-all technology solution is no longer a realistic strategy. No single technology such as a database can solve every problem, especially when it comes to Big Data. Even if such a unique solution could serve multiple needs, successful companies are always trialing new solutions in the quest to perpetually innovate and thereby achieve (or maintain) a competitive edge.
Open Data Services and Big Data go hand-in-hand
Big Data success requires companies to ditch the one-size-fits-all approach in favor of evaluating and running the right set of technologies to tackle each part of their Big Data strategy. To support this need, Open Data Services (ODS) has emerged to enable the evaluation and running of multiple on-demand Big Data solutions on a single platform. ODS characteristics include interoperability, robust community support, and non-proprietary, best-of-breed application technologies that fuel the continuous cycle of innovation.
GoGrid launches the first cloud platform dedicated to Big Data
Keeping up with, selecting, and using the plethora of open source Big Data products currently available can be daunting to even the most dedicated technologist. That’s why GoGrid’s ODS features 1-Button Deploy™ of multiple purpose-built Big Data solutions that allows businesses to easily evaluate and run the right technology on a reliable, cost-effective, on-demand platform. Unlike proprietary cloud platforms, GoGrid’s ODS provides the freedom to self-select the optimal products that will equip companies to execute on their specific Big Data strategies—from delivering ads at warp speed to the right recipients at the right time to pushing appropriate recommendations to buyers evaluating certain types of products.
The decision of which Big Data solution—or solutions—to choose is still up to each company to decide. ODS, especially as implemented by our new 1-Button Deploy™ technology, is the framework that will make the process of easily evaluating and then running those technologies successful.
Latest posts by Andy Nester (see all)
- Deploying Cassandra with the Push of a Button on GoGrid - April 3, 2014
- What do P-Diddy & NoSQL have in common? - March 20, 2014
- Big Data = Big Confusion? Hint: The Key is Open Data Services - November 6, 2013