Business Case Evaluation and Data Identification

Business Case Evaluation and Data Identification

Jignesh Patil, Sharmila Rathod
Copyright: © 2024 |Pages: 17
DOI: 10.4018/979-8-3693-0413-6.ch004
OnDemand:
(Individual Chapters)
Available
$33.75
List Price: $37.50
10% Discount:-$3.75
TOTAL SAVINGS: $3.75

Abstract

Businesses need all data to be controlled centralized, and most corporations utilize analysis to learn where their company stands in the market. Big data tools and approaches are being used by researchers and practitioners to compute performance utilizing various algorithms. It is obvious that organisations require strong understanding of their consumers, commodities, and laws; nevertheless, with the aid of big data, organisations may find new methods to compete with other organizations. This study will focus on big data techniques and algorithms to find patterns to apply on the business cases which are lagging. Technology is simply a tool used by the business elite to keep their clientele close by. It has successfully aided the organisation in achieving cost savings, making quicker, better decisions using business big data cycle and collaborative filtering.
Chapter Preview
Top

Introduction To Business Factor

Business need that all data be controlled centralized, and most corporations utilize analysis to learn where their company stands in the market. We recognize that big data tools and approaches are being used by researchers and practitioners to compute performance utilizing various algorithms. Organization’s typically have a large number of departments, and the risk analysis utilizes computations of the administrative flow and erroneous tests.

It is possible to link and dissociate distinct data assets from different big data sources using metadata. During the search process, metadata may be utilised to filter out irrelevant information, which helps search engines provide results with a high degree of confidence.

Despite the vast volume of content stored in these repositories, big data and analytics users may find the correct information fast by using metadata. Additionally, metadata establishes and preserves data consistency. Organisations can establish a uniform definition or business rule for a certain data attribute by using metadata. (Anuja Kulkarni, 2016).

Big data is the process of collecting and analyzing large data sets from traditional and digital sources to identify trends and patterns that can be used in decision-making. These large data sets are both structured (e.g. sales transactions from an online store) and unstructured (e.g. posts) on social media. Organizations are grappling with what big data is and how it effects their organizations and how it makes benefits to their organizations. A survey is conducted in which found that the only 12 percent organizations are implementing or executing the big data strategy and 71 percent organizations are going to begin the planning stage (“2013 Big

Data Survey Research Brief,” n.d.) It is clear that organizations need good knowledge of customers, goods and rules, with the help of big data organizations can find new ways to compete with other organizations. The organizations of the world are using the big data for their future decisions. Types of decisions that organizations can make from big data are smarter decisions, future decisions and decisions that make the difference (M. Schroeck et al,2012)

Organizations are making business decisions on the basis of the transactional data in past and in present but there is another kind of data which are nontraditional, less structured data for example weblogs, social media, Email and photographs that can be used for effective business decisions making. (J. P. Dijcks,2012).

So big data has imparted golden opportunity to the universal market, every part of industry is trying to evaluate the higher possibilities to gain and analyze information to take better decisions, much data means much more use-cases, more use-cases leads to more illustration of business evaluation which ultimately leads to best business decision making.

This scenario will lead to much profit, by changing the traditional approach of managing data into helpful new approaches.(Sosna, M., Trevino Rodríguez, R. N. &Velamuri, S.R., 2010).

Big data is the process of collecting and analyzing large data sets from traditional and digital sources to identify trends and patterns that can be used in decision-making. These large data sets are both structured (e.g. sales transactions from an online store) and unstructured (e.g. posts) on social media. Organizations are grappling with what big data is and how it effects their organizations and how it makes benefits to their organizations. A survey is conducted in which found that the only 12 percent organizations are implementing or executing the big data strategy and 71 percent organizations are going to begin the planning stage (“2013 Big

Data Survey Research Brief,” n.d.) It is clear that organizations need good knowledge of customers, goods and rules, with the help of big data organizations can find new ways to compete with other organizations. The organizations of the world are using the big data for their future decisions. Types of decisions that organizations can make from big data are smarter decisions, future decisions and decisions that make the difference (M. Schroeck et al,2012)

Organizations are making business decisions on the basis of the transactional data in past and in present but there is another kind of data which are nontraditional, less structured data for example weblogs, social media, Email and photographs that can be used for effective business decisions making. (J. P. Dijcks,2012).

Key Terms in this Chapter

Key Performance Indicators: ( KPIs ): These gauge how well your teams are working together to accomplish the overarching goals and objectives of the company. KPIs can be used to monitor the effectiveness of individual team members as well as the various departments that make up an organisation.

Data Transformation: A series of actions on data is what is referred to as a data transformation , which includes the discovery and removal of abnormalities.

Big Data Cycles: These plug in spaces in business or solve issues that contain bugs or faults by defining solutions to real-world situations.

Marketing Information System: A major company's top management invests a lot of time and money to realise that information management is just as important as managing people, materials, plants, and money. This process is known as the Marketing Information System .

User History: A term used to describe data that is used for user analysis or prediction. We are aware that historical data can be used to forecast actual statistical analysis, which in turn provides business solutions.

Big Data: The act of gathering and analyzing massive data sets from conventional and digital sources in order to uncover trends and patterns that may be utilized in decision-making is known as big data .

Collaborative Filtering: This describes the practise of matching individuals based on their shared interests.

Complete Chapter List

Search this Book:
Reset