Название: Rhythmic Advantages in Big Data and Machine Learning
Автор: Anirban Bandyopadhyay, Kanad Ray
Издательство: Springer
Год: 2022
Страниц: 270
Язык: английский
Формат: pdf (true)
Размер: 10.15 MB

The current book in the series of Systems in Rhythm Engineering, SRE, compiles rhythms from Big data in pure computation, astrophysics to basic biological structures. In today’s world, anything and everything is data and we generate voluminous data almost every passing second which actually gave birth to “Big Data”. The phrase “Big Data” which buzzes around us everywhere, is applied to a specific type of data that has certain traits. However, this phrase has been over used and often incorrectly, which is why itis difficult to gauge its true meaning. For commoners, it is very difficult to understand if Big Data is a tool or a technology or just a buzzword used by data scientists to scare us. Another concern is if Big Data really has the potential to usher in dramatic changes or will the hype fade away with time. In any case, over the past few years, Big Data has become an integral part of several industries and in many cases has shown the potential to be a game-changer.

To put it simply, big data describes the massive volume of both structured and unstructured data which is so enormous that processing this voluminous data requires special techniques. In short, big data is simply a whole lot of data. This concept is a relatively new one and it constitutes not only the increasing amount but also the diverse types of data that gets collected. As more and more information moves online and gets digitized, it paves way for the analysts to start using it as data. For instance, social media posts, online books, music, videos, along with their reviews, as well as the increased number of sensors have all added to the staggering increase in the amount of data that has become available for analysis. Everything we do now gets stored and tracked as data. Starting from online shopping to browsing movies generates data about our requirements, choices, and lifestyles. Our smartphone constantly uploads data about our location, movement as well as the apps we use.

So far, we have talked about Big Data from the perspective of its volume. However, Big Data isn’t just the volume of data we generate, it’s also about the different types of data, viz. text, video, search logs, sensor logs, customer transactions, etc. Formally, Big Data is the data that satisfies the following seven Vs:

1) Volume: In every sense, big data is really big! With the dramatic growth of the Internet, mobile devices, social media, and Internet of Things (IoT) technology, the amount of data generated from all these sources has grown accordingly.

2) Velocity: In addition to volume, the generation of data and the organizations’ ability to process it is accelerating.

3) Variety: In earlier times, most data types could be neatly captured in rows on a structured table. In the big data world, data often comes in unstructured formats like social media posts, server log data, lat-long geocoordinates, photos, audio, video, and free text.

4) Variability: The meaning of words in the text (unstructured data) can change based on the context.

5) Veracity: With many different data types and data sources, data quality issues invariably pop up in big data sets. Veracity deals with exploring a data set for data quality and systematically cleansing that data to be useful for analysis.

6) Visualization: Data visualization is a great tool for data analysis. Exploratory data analysis (EDA) can provide quick and in-depth insight to the end-users.

7) Value: Data must be combined with rigorous processing and analysis to be useful.