The process of collecting and saving considerable amounts of information, in the final analysis, is ages old. However, a new term but with an almost similar usage has come about, Big Data.
The term can be explained by what its name implies, the considerable amount of information, that can be structured or unstructured. The ability to decipher and decode the key insights which one extract from it is critical. To be able to remove practical intelligence from the big data has still been a difficulty for various industries. One needs apt tools to obtain information out of the data lake. The extraction isn’t the only significant problem they face, and it includes analysis, storage, sharing, data curation, transfer, searching, information privacy and even visualization.
If one can reach high precision and accuracy in interpreting the big data, then lower input costs and higher profits would become a mere matter.
Wong Hwee Lim, head of group business solutions & systems of CapitaLand, coined Big Data the “new currency,” “which allows real estate stakeholders to understand the business further to drive revenue forward.”
SAS considers two additional dimensions to Big Data:
Complexity. Today’s data comes from various sources, which makes it hard to transform, cleanse, match, and link data beyond systems. Still, it’s necessary to correlate and connect relationships, hierarchies and multiple data linkages or your data may immediately get out of control.
Variability. In addition to the increasing varieties and velocities of data, data flows can be highly variable with periodic peaks. Is there something trending in social media? Seasonal, daily, and event-triggered peak data loads can be hard to handle. Even more so with unstructured data.
Big Data is not just an alternative or option anymore, but a requirement to every business in every industry. Digital content is now at the peak with loads of updated and critical information which makes it essential for every company to be ahead. Big data requires superior technologies to process vast amounts of data in supportable elapsed times efficiently.
Big data has increased the need for information organization specialist in each industry. Big data is used to improve several aspects of our countries and cities. For instance, it enables cities to optimize traffic flows based on real-time traffic information as well as weather data and social media. Many cities are currently piloting big data analytics with the goal of turning themselves into Smart Cities, where the utility processes and transport infrastructure are all linked up. Where a bus would wait for a delayed train and where traffic signals predict traffic volumes and operate to lessen jams. Big data is utilized heavily in empowering law enforcement and enhancing security.
We are sure you are familiar with the admissions that the National Security Agency (NSA) in the U.S. utilizes big data analytics to prevent terrorist plots (and maybe spy on us). Others apply big data techniques to identify and counter cyber-attacks. Police forces employ big data tools to apprehend criminals and even predict criminal activity, and credit card corporations utilize Big Data and use it to discover fraudulent transactions.
We hope this article is helpful. All the best, and as we always say, happy learning!