Digital data from all the above sources and more contributes heavily to the massive influx of Big Data and is changing how businesses operate. The quantity and variety of data and the speed at which it is generated and processed each minute makes this phenomenon truly “big”. It is these variables that define Big Data and make it such a dominant factor in manufacturing, sales, marketing, operations, marketing research and business analysis to name a few of its applications. Big Data has led to significant developments in analytics of both text and video, detecting fraud, and predicting consumer trends. However, while solving several problems for both businesses and consumers, Big Data brings with it challenges of its own.
While methods of storing data and analyzing it have advanced considerably in the last 10 years, the fundamental systems based on Big Data have begun to create potential problems. As a result, businesses are left asking some pertinent questions that are relevant to the future of Big Data.
The volume of data out there is massive and what is needed is a system that can sift through it and make sense of it. While many Big Data systems are relatively new, they are becoming redundant or are overloaded, and are often incapable of responding to demands as they emerge and grow.
Currently, all processes relating to Big Data are executed and overseen by humans. However, imagine if complex processes like extricating relevant data and refining it could be delegated to an intelligent machine. Putting other Big Data processes on auto mode and delegating the machine to manage it could make business processes quicker and smarter. Sounds exciting? This day, however, might just arrive earlier than we think.