by Victor Brown
As a recent article on Wikibon notes, the changes wrought by the cloud, Big Data, and the advent of technologies like MongoDB and Hadoop are hitting traditional database vendors hard.
While Oracle and its competitors are still forces to be reckoned with in the IT world, cloud storage and data processing technologies, with their open APIs, open source development models, and non-existent licensing costs, are a better fit with modern business operations, particularly when it comes to handling the data loads and processing requirements of companies that do most of their business online.
Big data is big, obviously, but volume is far from the only concern of companies that want to efficiently leverage the data goldmine. For business intelligence and analytics to live up to their potential, data velocity, scalability, and the costs associated with data storage and movement are of equal importance. There’s very little point in storing huge amounts of data if its use isn’t timely and the costs of managing it cut deeply into profit margins, both of which hinder business agility.
It’s hardly surprising that the dinosaurs of the data management industry are taking a hit; they value correctness over velocity and contractual and technological lock-in over openness and portability. There will always be applications where a data management model optimized for predictable structured data is absolutely necessary. The businesses with the expertise and technology meet those requirements aren’t going anywhere.
However, at least 80 percent of a modern corporation’s data assets are unstructured. Much of that data is ephemeral, and its major usefulness lies in the insights that can be gleaned from it in the short, and medium, term rather than for its long-term record keeping potential.
Cloud platforms and Big Data are intimately connected. The cloud empowers modern businesses to store vast amounts of data at relatively low costs, scale their storage in response to requirements, process and analyze data for actionable insights. They also integrate the results of analyses with ongoing business operations through SaaS applications that can tie Big Data insights into collaborative tools for handling logistics, enterprise resource management, customer relationship management, human resources, sales and marketing, and most other areas of modern business.
All of that would be difficult and expensive if companies were limited to fixed infrastructure costs, slow scaling cycles, long-term lock-in with vendors, a lack of vertical integration, and an inability to extract value from unstructured data.
The giants of old IT have not been slain and they will continue to grow, but as businesses accelerate their exploitation of Big Data’s benefits, cloud platforms will continue to dominate the landscape.