scholarly journals IMPLEMENTASI BUSINESS INTELLIGENCE UNTUK MENENTUKAN TINGKAT KEPOPULERAN JURUSAN PADA UNIVERSITAS

2017 ◽  
Vol 2 (2) ◽  
pp. 135-138
Author(s):  
Ricky Akbar ◽  
Ria Oktaviani ◽  
Shabrina Tamimi ◽  
Syifa Shavira ◽  
Tri Winda Rahmadani
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Big Data ◽  
Business Intelligence ◽  
Research Application ◽  
Important Thing ◽  
Processing Data ◽  
Almost All ◽  
Information And Technology

In this globalization era that we face nowadays, information technology is the most important thing to be learnt or just to be known. Because in this all-sophisticated era, almost all the live's aspects are related with information and technology. It's not exception to determine the level of major popularized in on of University. In it's implementation, for sure it's difficult to determine which major is being the most popular, because there are so many data, so the process of decision making run slowly if it is done with standard query on database. Here is the used of Business Intelligence is really needed. By implemented Business Intelligence, the big data can be processed without any difficulties. On this research, application that we use is TABLEAU. TABLEAU is chosen because of its ease and its velocity on processing data. So that, it's hoped can ease in decision making for determining the most popular major at Andalas University.

scholarly journals Characterizing Big Data Management

10.28945/2192 ◽  
2015 ◽  
Author(s):  
Rogério Rossi ◽  
Kechi Hirama
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Big Data ◽  
Data Management ◽  
Process Management ◽  
Three Dimensions ◽  
Storage And Retrieval ◽  
Human Aspects ◽  
Business Approach ◽  
Support Decision Making

[The final form of this paper was published in the journal Issues in Informing Science and Information Technology.] Considering that big data is a reality for an increasing number of organizations in many areas, its management represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial dimensions to facilitate the management of big data in any organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management must be supported by technology, people and processes; hence, this article discusses these three dimensions: the technologies for storage, analysis and visualization of big data; the human aspects of big data; and, in addition, the process management involved in a technological and business approach for big data management.

Decision-Making with Big Data Using Open Source Business Intelligence Systems

2016 ◽  
pp. 120-147 ◽  
Author(s):  
Jorge Bernardino ◽  
Pedro Caldeira Neves
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Open Source ◽  
Business Intelligence ◽  
Business Performance ◽  
Specific Area ◽  
Enterprise Management ◽  
Business Decision ◽  
Business Intelligence Systems ◽  
Fundamental Shift

The importance of supporting decision making for improving business performance is a crucial, yet challenging task in enterprise management. The amount of data in our world has been exploding and Big Data represents a fundamental shift in business decision-making. Analyzing such so-called Big Data is becoming a keystone of competition and the success of organizations depends on fast and well-founded decisions taken by relevant people in their specific area of responsibility. Business Intelligence (BI) is a collection of decision support technologies for enterprises aimed at enabling knowledge workers such as executives, managers, and analysts to make better and faster decisions. We review the concept of BI as an open innovation strategy and address the importance of BI in revolutionizing knowledge towards economics and business sustainability. Using Big Data with Open Source Business Intelligence Systems will generate the biggest opportunities to increase competitiveness and differentiation in organizations. In this chapter, we describe and analyze four popular open source BI systems - Jaspersoft, Jedox, Pentaho and Actuate/BIRT.

Decision-Making With Big Data Using Open Source Business Intelligence Systems

Web Services ◽  
2019 ◽  
pp. 431-458 ◽  
Author(s):  
Jorge Bernardino ◽  
Pedro Caldeira Neves
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Open Source ◽  
Business Intelligence ◽  
Business Performance ◽  
Specific Area ◽  
Enterprise Management ◽  
Business Decision ◽  
Business Intelligence Systems ◽  
Fundamental Shift

The importance of supporting decision making for improving business performance is a crucial, yet challenging task in enterprise management. The amount of data in our world has been exploding and Big Data represents a fundamental shift in business decision-making. Analyzing such so-called Big Data is becoming a keystone of competition and the success of organizations depends on fast and well-founded decisions taken by relevant people in their specific area of responsibility. Business Intelligence (BI) is a collection of decision support technologies for enterprises aimed at enabling knowledge workers such as executives, managers, and analysts to make better and faster decisions. We review the concept of BI as an open innovation strategy and address the importance of BI in revolutionizing knowledge towards economics and business sustainability. Using Big Data with Open Source Business Intelligence Systems will generate the biggest opportunities to increase competitiveness and differentiation in organizations. In this chapter, we describe and analyze four popular open source BI systems - Jaspersoft, Jedox, Pentaho and Actuate/BIRT.

Organizational business intelligence and decision making using big data analytics

2021 ◽  
Vol 58 (6) ◽  
pp. 102725
Author(s):  
Yanfang Niu ◽  
Limeng Ying ◽  
Jie Yang ◽  
Mengqi Bao ◽  
C.B. Sivaparthipan
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Business Intelligence ◽  
Data Analytics ◽  
Big Data Analytics

Information Technology Usage: The Indian Experience

2004 ◽  
Vol 29 (1) ◽  
pp. 83-92 ◽  
Author(s):  
M P Gupta ◽  
Sanjay
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Supply Chain ◽  
Inventory Control ◽  
Business Intelligence ◽  
Business Strategy ◽  
Information Needs ◽  
Market Place ◽  
Business Executives ◽  
Strategy Transformation

This paper attempts to understand the current state of Information Technology (IT) usage in select Indian organizations based on a questionnaire survey of business executives and IS staff of select IT-savvy organizations. In recent years, rapid changes and developments in the IT domain have created new leaders in the market place. Corporates, the world over, are leveraging on these developments through efficient supply chain, inventory control, and business intelligence applications for gaining an edge over their competitors. The Information System (IS) developed by these organizations is non-replicable thus providing the differentiation. Though Indian companies are aware of concepts such as supply chain, inventory control, etc., the actual implementation of such concepts is not that widespread. Also, the IS function in India is yet to establish itself as a mainstream business function. It is in this context that this paper makes an effort to understand the importance of IT as a key driver for business strategy and recommend to the industry to adopt some of the best practices prevailing in organizations worldwide. The analysis of the responses indicates that there is a discrepancy between the opinions of business executives and IS staff regarding the adequacy of the current IT systems. This situation can be remedied by implementing some of the suggestions which are as follows: The business executives and the IS staff should be located in the same place to integrate IT into the mainstream of business. Business intelligence application needs to be included in the portfolio of applications for business use. The Indian industry needs to be stepped up to the ‘informate’ stage as it is still in the ‘automate’ stage. CIOs have to play an important role by linking IT to business strategy. Information needs of the executives are increasing and necessary steps for imple- menting data warehousing and OLAP solutions need to be taken. Supporting IS should be put in place to facilitate decision-making. Key performance indicators (KPIs) should be clearly identified and incorporated into the IS to monitor the health of the organization. These initiatives are expected to have the following implications: tighter integration of IT with business strategy transformation from the ‘informate mode’ to the ‘transformate’ mode implementation of newer business intelligence tools development of information-based decision-making culture better understanding of organization's KPIs by the IS staff.

Business Intelligence

2019 ◽  
pp. 578-588
Author(s):  
Richard T. Herschel
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Common Sense ◽  
Business Intelligence ◽  
Productivity Growth ◽  
Unstructured Data ◽  
Quality Data ◽  
Data Governance ◽  
Location Data ◽  
Multiple Dimensions

Big data is driving new forms of competition, new waves of productivity growth, innovation, and providing unique ways to interact with customers. Big data is comprised of a wealth of unstructured data that is being transmitted and captured by organizations to enhance business intelligence efforts. The forms that big data takes include text, video, voice, location data, social media, and its growth is exponential. Big data encompasses multiple dimensions, including volume, variety, velocity, veracity, variability, and complexity. Despite the opportunities that big data presents, organizations are having difficulty managing it, especially in the areas of data management and data governance. Executive involvement is critical to ensuring quality data for business intelligence as well as to ensure that their firms will be able to attract the necessary talent to effectively engage in BI analytics. It is recommended that management take a common-sense approach to dealing with big data to ensure that data-driven decision making is not compromised.

Commercial and Open Source Business Intelligence Platforms for Big Data Warehousing

2019 ◽  
pp. 158-181 ◽  
Author(s):  
Jorge Bernardino ◽  
Joaquim Lapa ◽  
Ana Almeida
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Decision Support ◽  
Comparative Analysis ◽  
Open Source ◽  
Data Warehouse ◽  
Business Intelligence ◽  
Selection Process ◽  
Decision Making Processes ◽  
Big Data Warehouse

A big data warehouse enables the analysis of large amounts of information that typically comes from the organization's transactional systems (OLTP). However, today's data warehouse systems do not have the capacity to handle the massive amount of data that is currently produced. Business intelligence (BI) is a collection of decision support technologies that enable executives, managers, and analysts to make better and faster decisions. Organizations must make good use of business intelligence platforms to quickly acquire desirable information from the huge volume of data to reduce the time and increase the efficiency of decision-making processes. In this chapter, the authors present a comparative analysis of commercial and open source BI tools capabilities, in order to aid organizations in the selection process of the most suitable BI platform. They also evaluated and compared six major open source BI platforms: Actuate, Jaspersoft, Jedox/Palo, Pentaho, SpagoBI, and Vanilla; and six major commercial BI platforms: IBM Cognos, Microsoft BI, MicroStrategy, Oracle BI, SAP BI, and SAS BI & Analytics.

Business Intelligence

2018 ◽  
pp. 951-960
Author(s):  
Richard T. Herschel
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Common Sense ◽  
Business Intelligence ◽  
Productivity Growth ◽  
Unstructured Data ◽  
Quality Data ◽  
Data Governance ◽  
Location Data ◽  
Multiple Dimensions

Big data is driving new forms of competition, new waves of productivity growth, innovation, and providing unique ways to interact with customers. Big data is comprised of a wealth of unstructured data that is being transmitted and captured by organizations to enhance business intelligence efforts. The forms that big data takes include text, video, voice, location data, social media, and its growth is exponential. Big data encompasses multiple dimensions, including volume, variety, velocity, veracity, variability, and complexity. Despite the opportunities that big data presents, organizations are having difficulty managing it, especially in the areas of data management and data governance. Executive involvement is critical to insuring quality data for business intelligence as well as to insure that their firms will be able to attract the necessary talent to effectively engage in BI analytics. It is recommended that management take a common sense approach to dealing with big data to insure that data-driven decision-making is not compromised.

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