It’s not a huge revelation that the world of Cloud computing is rapidly evolving and taking on a wide range of shapes these days. The as-a-service nomenclature is expanding beyond Cloud-based platforms, infrastructures, and software solutions. It now includes a variety of Web and Data Management technologies that are almost becoming too many to name. For instance, over the past year or so we have witnessed the rise of Database-as-a-Service (DaaS) solutions shift an emphasis to NoSQL and other types of structured and non-structured Data Management tools.
It’s possible that the last thing we need is another as-a-service Cloud computing model to define, but just as you may have expected that’s exactly what we have to do. Now, as the world of Big Data seeps into every aspect of enterprise-class Data Management and decision-making, we’re experiencing another wave of Cloud computing models. Enter Big-Data-as-a-Service (BDaaS).
Why Cloud-based Big Data?
At the core of the looming BDaaS revolution is the reality that Big Data is everywhere. According to a recent Gartner report, 42% of all IT leaders have either already invested in Big Data technology, or will be in the very near future. The same report indicates that IT leaders are rapidly moving down the Big Data stream out of necessity. They are highly cognizant of the fact that Big Data does and will reveal business opportunities that are completely overlooked with archaic Data Management and visualization analytics tools.
However, there’s something beyond the simple fact that an increasing number of IT pros are gravitating towards Big Data technology. That is, businesses are increasingly aware of the power of Big Data to inform business decisions. As a result, from the top down organizations are pushing for Big Data-centric infrastructure to help integrate this new technology.
The big idea here is that the enterprise is virtually drowning in data. Without a powerful Cloud-based resource to manage that information, it can quickly verge on becoming unmanageable.
Understanding this new BDaaS Cloud computing model means having some sort of a grasp on the concept of Big Data itself. If you haven’t been following along, Big Data refers to massive volumes of data in new varieties moving through large-scale organizations in real time, or at least extremely close to real time, depending on the infrastructure. Naturally, at the core of BDaaS is this growing need to offload these Big Data processes to a Cloud-based, third party vendor.
Challenges for a Looming BDaaS Revolution
The key questions for many organizations considering a migration to a BDaaS provider are all related to rapid technological shifts currently taking place in the enterprise. According to Gartner Vice President, Frank Buytendik, business and IT leaders are increasingly worried about their ability to keep up with competitors. This is all due to – from an infrastructure perspective – a lack of preparation for this dramatic technological shift in the IT space.
The good news, according to Buytendik, is that there is no shortage of opportunity to expand and develop resources to meet the needs of this new era of BDaaS Data Management and computing solutions. In fact, despite these seemingly overwhelming challenges, Gartner still believes that Big Data technologies will see major growth in the years ahead. Gartner believes that by 2015, 20% of all global 1000 companies place a high emphasis on “information infrastructure,” or other types of Big Data technologies. Some analysts believe that this is merely setting the stage for BDaaS adoption on a much larger scale.
Five Key Benefits of BDaaS for the Enterprise
Beyond the clear BDaaS implementation challenges facing today’s enterprise organizations, there are hosts of benefits that are influencing IT leaders to move their Big Data management solutions to Cloud-based providers. Let’s take a look at five of these key benefits for the enterprise.
- Analytical Insights: This is where a lot of key business decision-making really shines. Big Data analytics in the Cloud offer insights that are geared towards improving how organizations respond to complex data sets. In most cases, the Big Data analytics environment gives you some leverage to customize the data you want to analyze. In other words, you can easily process and query information based on very specific search queries related to very specific business processes.
- Real-time Data Analysis: Perhaps one of the most attractive things about Big Data in the Cloud is the potential to access data in real time, or at least pretty darn close to it. Database indexing and response times are lightning fast, which gives you a great deal of power over a wide range of sophisticated Big Data analysis and processing tasks. The big idea is that your databases refresh in a matter of minutes, which gives you near-real-time results.
- Data Manageability: One of the major challenges for IT leaders attempting to manage both semi-structured and non-structured databases within an in-house Big Data infrastructure is the sheer volume of data that needs to processed and analyzed. BDaaS solutions are designed to simplify this process. Through the power of index compression, all data is dramatically reduced in size to make the data management process a lot more digestible. This goes a long way to improve accuracy, and keep overall costs down.
- Flexibility: Open source solutions for managing Big Data applications are becoming more and more prevalent, especially as the BDaaS conversation really starts to take shape. Through integrated open source platforms like Hadoop and Cassandra, you can have greater control over real-time analytics processes.
- Cost Effectiveness: Finally, one of the most valuable benefits of Big Data in the Cloud is inextricably tied to the overall nature of cloud computing. That is, you’re not locked into proprietary hardware, and by provisioning a host of virtual servers you only pay for what you need, and only as you need it.
At the end of the day, the big question facing all industry analysts, experts and IT leaders is if the world is ready for a BDaaS revolution. On one hand, according to Phillip Wik, DBA for RedFlex, BDaaS infrastructure isn’t inherently difficult to execute. It’s all about having the right components in place. Some key elements needed for successful BDaaS implementation include a highly functional service-oriented architecture, cloud virtualization capabilities, Hadoop, as well as a host of Business Intelligence tools that allow for deep and sophisticated data analytics.
RedFlex’s Phillip Wik has concerns beyond the mere mechanics of delivering Cloud-based Big Data solutions. He says there are some ethical concerns as well. The big concern is that having several massive databases gathering and processing data from cameras and sensors in real time could raise some privacy concerns in the big data management space.
The short answer to the question that this article poses is that beyond these ethical questions that are actually incredibly complex and difficult to answer, the world may actually be ready to embrace BDaaS in a meaningful way. It’s clear that the technology is in place, and organizations are, in increasing numbers, adopting Big Data solutions on a large scale. At this point, it’s not a matter of “if” in the BDaaS adoption conversation. It all comes down to timing, and whether or not BDaaS is right for your operational needs.