Cloud computing is rapidly evolving. From its original offerings of Infrastructure as a Service (IaaS) and Software as a Service(SaaS) have emerged a series of data management solutions, such as Database as a Service (DaaS). With so many offerings available, it doesn’t seem like another edition should warrant a lot of attention, but Big Data as a Service (BDaaS) such as provided by Qubole should have the attention of business leaders. BDaaS revolutionizes the big data services industry by making it more affordable, easier to use and more accessible than it was before.
What’s the Big Deal with Big Data?
Data is being created at a frantic pace, and much of this data is in an unstructured form, such as the abbreviated text of a tweet or a status update. This data is being created so quickly and in such huge amounts that traditional databases are unable to hold the surge in volume in an affordable manner. In addition, those traditional databases are unable to capture data unless it is converted to a structured form, making it impossible to store and analyze important sources such as social media messages, metadata or emails. To surmount this problem, Hadoop was created, which can not only scale to meet surging data volumes but can also capture data in any form.
With the ability to now capture and analyze big data, businesses, the healthcare industry, governments and many other organizations have started to gain insights and build new tools to boost profitability, productivity and customer satisfaction.
So Why BDaaS?
Hadoop was a major stepping stone for big data, but it still had its limitations, especially for SMBs that don’t have the resources to build up a Hadoop infrastructure in house. While Hadoop is more cost-effective than a traditional database, it is still expensive to buy up front and to maintain. In addition, expertise in how to use Hadoop is limited, making it essential for big data services to be enterprise-friendly, and in the case of small businesses, cost effective. Big Data as a Service addresses these issues by taking advantage of the flexibility of cloud computing.
1. Set-up in Minutes
Building Hadoop in-house would take several months by the time a company researched options, worked out a budget and then actually started building. With cloud computing, all a business has to do is select a provider and within minutes it has access to the entire infrastructure, software, and in many cases, applications that it needs to get started right away.
2. Affordable Pricing Model
Rather than paying for hardware that often sits empty and frequently needs maintenance and upgrades, cloud computing charges on a per-use basis. This means that small businesses can pay to analyze a set of data, and once the project is complete, no longer pay for that storage space. With such a flexible pricing model, the hefty price tag attached to Hadoop is no longer a barrier.
3. No Expertise Required
Finally, turning to a cloud database eliminates the need to find a data scientist or IT expert to help you implement a big data project. Instead, the provider offers tools that are easy to use and technical support for any issues you may run into.
It’s hard to say which big data solution the business world will finally settle on, but with most of the big data vendors now offering a version of their platform in the cloud, it is safe to say that the cloud will play a huge part in making big data an integrated part of the business world.