The Big data trend is now slowly stabilizing, in these past 10 years many companies in their digitization attempt have encountered issues and setbacks, which they tried to tackle with these emerging digital technologies. Here, is a countdown of different stages of data development that enterprises go through.
Stage one is the big data talk, not all companies truly have a dataset that big and elusive that it can be called big data. Only few companies all around the globe actually own data resources that fall under the big data category and means to harness those data resources.
Stage two, is the accumulation or gathering of data. In this age of internet and smartphones, companies have the means to gather and collect data, based on user inputs, then there are social media feeds and webpages, which literally are data gold mines fetching demographics, like & dislike count, upvote & downvote count, follower count, and what not. All this data after processing fetches metadata, which is interpreted by means of advanced data analytics tools and machine learning techniques to gather behavior data about an individual. This stage of processing which includes video processing and language recognition, with the help of machine learning and deep learning techniques comprises the stage three in data development.
Stage four deals with data security and privacy concerns, with enterprises collecting hundreds of petabytes to tens of exabytes of data on a daily basis from different resources, concerns about safe data governance arises. Enterprises must bring in safe industry best practices to safeguard and regularly update this data, to keep its business vale intact.
And finally the stage five, which basically deals with negative impacts this big data set may have, as with advancements in big data and artificial intelligence technologies, issues like job scarcity, unemployment, and unfair competition are arising. Companies need to keep a firm check on these key concerns.