Data seems to be the main actor in the digital revolution that has been going on for decades. After focusing on processing speed for years, organizations have realized that the most valuable asset in this digital age is user-generated data. The industry then started restructuring their models accordingly to benefit from every single piece of information generated by every individual user.
Organizations that are data-centric adopted the idea of big data. Three main obstacles, which prevented the data-centered ecosystem from emerging sooner were the high storage cost, the difficulty of processing large volumes of data, and insufficiency of the user-generated data that companies have immediate access to, were rapidly solved with the birth of purpose-specific data management techniques. Distributed memory-based processing followed suit, announced the start of the data-driven era. Big data is the only path for significant corporations to overcome continuous exponential drop of data-storage costs accompanied by a constant exponential rise of the amounts of data. The open-source Hadoop ecosystem had become a crowded space filled with aspiring startups and promising technologies working on big data products.
Small companies that work with data still rely on trusted SQL-centered software. Data is getting more valuable. Scalability is the first reason that generated the need for big data in the first place. After development and improvement open-source big data technologies offer much more than old-school servers on every level. With distributed computing, more work could be done in less time. With these advantages, not using big data technology becomes a pointless fight that prevents an organization from generating more value from your most valuable resource. With cloud-based services, adopting significant data architecture is easy with no hardware hurdles.