Mining Big Data: Its Current Status and Future

2017 ◽  
Vol 7 (7) ◽  
pp. 285
Author(s):  
Mayushi Chouhan ◽  
Rohit Singh Nain
Keyword(s):  
Big Data ◽  
Daily Basis ◽  
Unstructured Data ◽  
Current Status ◽  
Process Automation ◽  
Cognitive Technology ◽  
Business World ◽  
The World ◽  
Set Up ◽  
Extract Information

Organizations create 2.5 Quintilian bytes of data. So much that 90% of the data in the world today has been set up in the last two years alone. What is Big Data? Big Data is large volumes of structured and unstructured data. This data is what organizations collect on a daily basis. The amount of data is not the important part, but the information gathered from that data is the key. Collecting and analyzing Big Data gives organizations enhanced insight, decision making, and process automation. Approximately each one can agree that big data has taken the business world by storm, but what’s next?  Will data continue to grow?  What technologies will develop around it? Or will big data become a relic as quickly as the next trend — cognitive technology? Fast data? - appears on the horizon. I believe, am that big data is only going to get bigger and those companies that ignore it will be left further and further behind. This paper studies about what is big data, how does it helps organizations to extract information, its tools and technologies and its future.

scholarly journals The Big Data Era: What are the Implications for the World of Accounting?

2020 ◽  
Vol 17 (2) ◽  
pp. 248-254
Author(s):  
Rokhmat Taufiq Hidayat ◽  
Akhmad Khabibi
Keyword(s):  
Information Technology ◽  
Big Data ◽  
Financial Accounting ◽  
Unstructured Data ◽  
Added Value ◽  
Managerial Accounting ◽  
Business World ◽  
The World ◽  
Oxford Dictionary ◽  
Definition Of

In an era where information technology is developing so rapidly as it is now, contact with technology is inevitable. One that may often be heard is the use of big data. Although the development of big data has begun long before, its growth began rapidly since the Oxford Dictionary included the definition of big data in 2013. The use of big data is thought to have a big influence on the business world, and anything that influences the business world will certainly affect the world of accounting. Does the accountant anticipate these changes? In this article, the author tries to explore what allusions might occur between the world of accounting and big data. Big data will increase the complexity of the accounting world by adding unstructured data in the accounting cycle. This presents a challenge for accountants but can also provide far greater added value if accountants are able to use it well. The results of this study indicate that there are at least 3 areas in the field of accounting that are very likely to be exposed to the use of big data, namely in the process of financial accounting, managerial accounting, and auditing

How Phillips saw the light

2020 ◽  
Vol 36 (8) ◽  
pp. 29-31
Keyword(s):  
Design Methodology ◽  
Reading Time ◽  
Daily Basis ◽  
Business World ◽  
Content Type ◽  
Freak Show ◽  
The World ◽  
Pertinent Information ◽  
The One ◽  
Practical Implications

Purpose Reviews the latest management developments across the globe and pinpoints practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings The problem with developing a reputation of being something of an oracle in the business world is that all of a sudden, everyone expects you to pull off the trick of interpreting the future on a daily basis. Like a freak show circus act or one-hit wonder pop singer, people expect you to perform when they see you, and they expect you to perform the thing that made you famous, even if it is the one thing in the world you don’t want to do. And when you fail to deliver on these heightened expectations, you are dismissed as a one trick pony, however good that trick is in the first place. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Big Data: A Very Short Introduction

2017 ◽  
Author(s):  
Dawn E. Holmes
Keyword(s):  
Social Media ◽  
Big Data ◽  
Online Shopping ◽  
The Internet ◽  
Gps Data ◽  
Security Risks ◽  
Short Introduction ◽  
Business World ◽  
The World ◽  
Diverse Cultures

Since long before computers were even thought of, data has been collected and organized by diverse cultures across the world. Once access to the Internet became a reality for large swathes of the world’s population, the amount of data generated each day became huge, and continues to grow exponentially. It includes all our uploaded documents, videos, and photos; all our social media traffic; our online shopping; even the GPS data from our cars. Big Data: A Very Short Introduction explains how big data works and is changing the world around us, the effect it has on our everyday lives and in the business world, and it considers the attendant security risks.

scholarly journals Big Data and Business Analytics: Trends, Platforms, Success Factors and Applications

2019 ◽  
Vol 3 (2) ◽  
pp. 32 ◽  
Author(s):  
Ifeyinwa Angela Ajah ◽  
Henry Friday Nweke
Keyword(s):  
Big Data ◽  
Success Factors ◽  
Database Management System ◽  
Unstructured Data ◽  
Digital Data ◽  
Business Strategies ◽  
Modern World ◽  
Successful Implementation ◽  
Business Analytics ◽  
Business World

Big data and business analytics are trends that are positively impacting the business world. Past researches show that data generated in the modern world is huge and growing exponentially. These include structured and unstructured data that flood organizations daily. Unstructured data constitute the majority of the world’s digital data and these include text files, web, and social media posts, emails, images, audio, movies, etc. The unstructured data cannot be managed in the traditional relational database management system (RDBMS). Therefore, data proliferation requires a rethinking of techniques for capturing, storing, and processing the data. This is the role big data has come to play. This paper, therefore, is aimed at increasing the attention of organizations and researchers to various applications and benefits of big data technology. The paper reviews and discusses, the recent trends, opportunities and pitfalls of big data and how it has enabled organizations to create successful business strategies and remain competitive, based on available literature. Furthermore, the review presents the various applications of big data and business analytics, data sources generated in these applications and their key characteristics. Finally, the review not only outlines the challenges for successful implementation of big data projects but also highlights the current open research directions of big data analytics that require further consideration. The reviewed areas of big data suggest that good management and manipulation of the large data sets using the techniques and tools of big data can deliver actionable insights that create business values.

scholarly journals A Scalable Business Intelligence Decision-Making System in the Era of Big Data

2019 ◽  
Vol 8 (12) ◽  
pp. 2034-2042
Keyword(s):  
Big Data ◽  
Data Warehouse ◽  
Data Storage ◽  
Business Intelligence ◽  
Unstructured Data ◽  
Data Sources ◽  
Second Step ◽  
Decision Making System ◽  
Set Up

Transformation presents the second step in the ETL process that is responsible for extracting, transforming and loading data into a data warehouse. The role of transformation is to set up several operations to clean, to format and to unify types and data coming from multiple and different data sources. The goal is to get data to conform to the schema of the data warehouse to avoid any ambiguity problems during the data storage and analytical operations. Transforming data coming from structured, semi-structured and unstructured data sources need two levels of treatments: the first one is transformation schema to schema to get a unified schema for all selected data sources and the second treatment is transformation data to data to unify all types and data gathered. To ensure the setting up of these steps we propose in this paper a process switch from one database schema to another as a part of transformation schema to schema, and a meta-model based on MDA approach to describe the main operations of transformation data to data. The results of our transformations propose a data loading in one of the four schemas of NoSQL to best meet the constraints and requirements of Big Data.

scholarly journals Playing with data and its consequences

First Monday ◽  
2019 ◽  
Author(s):  
Miren Gutiérrez ◽  
Stefania Milan
Keyword(s):  
Big Data ◽  
Paradigm Shift ◽  
Daily Basis ◽  
Social Contexts ◽  
Communicative Practices ◽  
Data Infrastructure ◽  
Critical Data ◽  
Data Practices ◽  
The Social ◽  
The World

The fundamental paradigm shift brought about by datafication alters how people participate as citizens on a daily basis. “Big data” has come to constitute a new terrain of engagement, which brings organized collective action, communicative practices and data infrastructure into a fruitful dialogue. While scholarship is progressively acknowledging the emergence of bottom-up data practices, to date no research has explored the influence of these practices on the activists themselves. Leveraging the disciplines of critical data and social movement studies, this paper explores “proactive data activism”, using, producing and/or appropriating data for social change, and examines its biographical, political, tactical and epistemological consequences. Approaching engagement with data as practice, this study focuses on the social contexts in which data are produced, consumed and circulated, and analyzes how tactics, skills and emotions of individuals evolve in interplay with data. Through content and co-occurrence analysis of semi-structured practitioner interviews (N=20), the article shows how the employment of data and data infrastructure in activism fundamentally transforms the way activists go about changing the world.

Big Data Mining

2016 ◽  
pp. 53-59 ◽  
Author(s):  
N. G. Bhuvaneswari Amma
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Social Networking ◽  
Unstructured Data ◽  
Science And Engineering ◽  
Business World ◽  
Volume Velocity ◽  
Big Data Mining ◽  
Traditional Processing ◽  
Processing Techniques

Big data is a term used to describe very large amount of structured, semi-structured and unstructured data that is difficult to process using the traditional processing techniques. It is now expanding in all science and engineering domains. The key attributes of big data are volume, velocity, variety, validity, veracity, value, and visibility. In today's world, everyone is using social networking applications like Facebook, Twitter, YouTube, etc. These applications allow the users to create the contents for free of cost and it becomes huge volume of web data. These data are important in the competitive business world for making decisions. In this context, big data mining plays a major role which is different from the traditional data mining. The process of extracting useful information from large datasets or streams of data, due to its volume, velocity, variety, validity, veracity, value and visibility is termed as Big Data Mining.

Driving Big Data with Hadoop Technologies

2014 ◽  
pp. 232-262 ◽  
Author(s):  
Siddesh G. M. ◽  
Srinidhi Hiriyannaiah ◽  
K. G. Srinivasa
Keyword(s):  
Big Data ◽  
Information Needs ◽  
Unstructured Data ◽  
On Demand ◽  
Data Formats ◽  
The World

The world of Internet has driven the computing world from a few gigabytes of information to terabytes, petabytes of information turning into a huge volume of information. These volumes of information come from a variety of sources that span over from structured to unstructured data formats. The information needs to update in a quick span of time and be available on demand with the cheaper infrastructures. The information or the data that spans over three Vs, namely Volume, Variety, and Velocity, is called Big Data. The challenge is to store and process this Big Data, running analytics on the stored Big Data, making critical decisions on the results of processing, and obtaining the best outcomes. In this chapter, the authors discuss the capabilities of Big Data, its uses, and processing of Big Data using Hadoop technologies and tools by Apache foundation.

A Framework for Evaluating Design Methodologies for Big Data Warehouses

2018 ◽  
Vol 14 (1) ◽  
pp. 15-39 ◽  
Author(s):  
Francesco Di Tria ◽  
Ezio Lefons ◽  
Filippo Tangorra
Keyword(s):  
Big Data ◽  
Unstructured Data ◽  
Data Warehouses ◽  
Qualitative Information ◽  
Design Specifications ◽  
Set Up ◽  
Definition Of ◽  
Data Context

This article describes how the evaluation of modern data warehouses considers new solutions adopted for facing the radical changes caused by the necessity of reducing the storage volume, while increasing the velocity in multidimensional design and data elaboration, even in presence of unstructured data that are useful for providing qualitative information. The aim is to set up a framework for the evaluation of the physical and methodological characteristics of a data warehouse, realized by considering the factors that affect the data warehouse's lifecycle when taking into account the Big Data issues (Volume, Velocity, Variety, Value, and Veracity). The contribution is the definition of a set of criteria for classifying Big Data Warehouses on the basis of their methodological characteristics. Based on these criteria, the authors defined a set of metrics for measuring the quality of Big Data Warehouses in reference to the design specifications. They show through a case study how the proposed metrics are able to check the eligibility of methodologies falling in different classes in the Big Data context.

Big Data

2015 ◽  
Vol 6 (2) ◽  
pp. 1-17 ◽  
Author(s):  
Ashok Kumar Wahi ◽  
Yajulu Medury ◽  
Rajnish Kumar Misra
Keyword(s):  
Big Data ◽  
Unstructured Data ◽  
Data Driven ◽  
Enterprise 2.0 ◽  
Huge Amount ◽  
The World ◽  
Data Driven Decisions ◽  
The Impact

Big data has taken the world by storm. Everyone from every industry is not only talking about the impact of big data but is looking for ways to effectively leverage the power of big data. This challenge has heightened with the huge amount of unstructured data flowing from every direction, bringing along with it the increasing pressure to make data driven decisions rather than the gut-driven decisions. This article sheds light on how big data can be an enabler for smart enterprises if the organization is able to address the challenges posed by big data. Enterprises need to equip themselves with relevant technology, desired skills and a supporting managerial attitude to swim through the challenges of big data. It also highlights the need for all enterprises making the journey from 1.0 stage to Enterprise 2.0 to master the art of Big Data if they have to make the transition successful.

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