The Role of Big Data and Business Analytics in Decision Making

The Role of Big Data and Business Analytics in Decision Making

Pedro Caldeira Neves, Jorge Rodrigues Bernardino
DOI: 10.4018/978-1-7998-5849-2.ch010
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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 today 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 analytics (BA) represents a merger between data strategy and a collection of decision support technologies and mechanisms for enterprises aimed at enabling knowledge workers such as executives, managers, and analysts to make better and faster decisions. The authors review the concept of BA as an open innovation strategy and address the importance of BA in revolutionizing knowledge towards economics and business sustainability. Using big data with open source business analytics systems generates the greatest opportunities to increase competitiveness and differentiation in organizations. In this chapter, the authors describe and analyze business intelligence and analytics (BI&A) and four popular open source systems – BIRT, Jaspersoft, Pentaho, and SpagoBI.
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New advances of Information and Communication Technologies (ICT) continue to rapidly transform how business is done and change the role of information systems in business and our daily life. The amount of data in our world has been overwhelmingly exploding. Enterprises are flooded with ever-growing data of all types, easily amassing terabytes and even petabytes, of data. Analyzing such so-huge amounts of data is a keystone of competition, synonym for productivity growth, and innovation. With the emergence of new data collection technologies and analytical tools, Big Data offers a way to make businesses more agile, and to answer questions that were previously considered beyond reach. Increasing competition, demand for profits, contracting economy, and savvy customers all require companies and organizations to make the best possible decisions. With the fast advancement of both business techniques and technologies in recent years, knowledge has become an important and strategic asset that determines the success or failure of an organization (Wit & Meyer, 2010). Studies show that a competitive advantage in the business environment depends on the accessibility to adequate and reliable information in shortest time possible – sometimes even in real-time – and the high selectivity in the creation and use of information. An effective instrument to create, aggregate and share knowledge in an organization has therefore become a key target for management.

The need to implement decision support systems in organizations is not only an unavoidable reality but also a prerequisite for todays’ companies (Arsham, 2015). Currently, the majority of organizations have platform services, designed to record and store massive amounts of data resulting from the operational activity (Wang et al., 2019). This dataset is then transformed in information and all that information will lead to knowledge useful for the organizations.

The terms Business Intelligence (BI) and Business Analytics (BA) have been widely used in various contexts, but there seems to be no commonly accepted definition of what, at least BA is. Hindle et al., (2019) define BA in the same way that Davenport and Harris (2007) defines BI, which is “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions”.

On this study, we follow a terminology defended by a few researchers, who call this area BI&A which stands for Business Intelligence and Analytics and represents a merge of Business Intelligence techniques and systems with a Business Analytics strategy (Torres et al., 2018).

In addition, in a competitive environment, traditional decision-making approaches no longer meet the requirements of organizations for decision-making; organizations must make good use of information system tools such as BI&A systems to quickly acquire desirable information from huge volume of data to reduce the time and increase the efficiency of decision-making procedure. Different researchers have different definitions for business intelligence and analytics systems, for example Sharda et al., (2014) defined these as “an umbrella term that encompasses tools, architectures, databases, data warehouses, performance management, methodologies, and so forth, all of which are integrated into a unified software suite”.

Business Intelligence and Analytics is one of the few forms of sustainable competitive advantage left (Burstein & Holsapple, 2008). For example, any two well-funded competitors in a market have near real access to capital, technology, market research, customer data, and distribution. People and the quality of the decisions that they make are the primary competitive differentiators in the Information Age (Lin et al., 2009). The implementation of an effective BI&A strategy is the key to sustaining long-term competitive advantage as so, is normally driven by the top management as a whole instead of just the information technology department as usual.

Key Terms in this Chapter

BI&A Tools: Represents the tools and systems that play a key role in the strategic planning process of the organization. These systems allow a company to gather, store, access and analyze corporate data to aid in decision-making. Generally, these systems will illustrate business analytics in the areas of customer profiling, customer support, market research, market segmentation, product profitability, statistical analysis, and inventory and distribution analysis to name a few.

Open Source Software (OSS): Open source software refers to software that is developed, tested, or improved through public collaboration and distributed with the idea that the must be shared with others, ensuring an open future collaboration. The collaborative experience of many developers, especially those in the academic environment, in developing various versions of the UNIX operating system, Richard Stallman's idea of Free Software Foundation, and the desire of users to freely choose among a number of products - all of these led to the Open Source movement and the approach to developing and distributing programs as open source software.

Cloud: Cloud consist in a distributed environment that uses resource virtualization to unify and abstract resource management and provide several high performance, available and redundant services in a pay-as-you-go model that allows cloud service provider’s clients not to worry about IT concerns and focus mainly in their business needs. Among the services provided in the cloud are the Infrastructure as a Service (IaaS), which allow clients to purchase resources on demand; Platform as a Service (PaaS) where platform instances are hired as a service, trusting the cloud provider to maintain servers; Software as a Service (SaaS), which is used to deploy software in a scalable and available way; Big Data as a Service – a specification of PaaS – that provides cloud’s customers a way to store, manage and process big volumes of data; Analytics and Business analytics as a Service (AaaS and BAaaS) enables users to mine data to find interesting patterns, correlations and trends.

Decision Support Systems (DSS): Decision support systems are a specific class of computerized information system that supports business and organizational decision-making activities. A properly designed DSS is an interactive software-based system intended to help decision makers compile useful information from raw data, documents, personal knowledge, and/or business models to identify and solve problems and make decisions.

Data Warehousing: Analytical databases focused on providing decision support information and deriving business analytics for enterprises. According to Kimball definition, “a data warehouse is a copy of transaction data specifically structured for query and analysis”. This is a functional view of a data warehouse. Typically, a data warehouse is a massive database (housed on a cluster of servers, or a mini or mainframe computer) serving as a centralized repository of all data generated by all departments and units of a large organization. Advanced data mining software is required to extract meaningful information from a data warehouse.

Business Intelligence and Analytics: Business intelligence and analytics is a broad category of strategies, applications, and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI&A applications include the activities of decision support systems, query and reporting, statistical analysis, forecasting, and data mining. BI&A refers to a management philosophy and tool that help organizations to manage and refine business information to make effective decisions.

Information technology (IT): Set of tools, processes, and methodologies (such as coding/programming, data communications, data conversion, storage and retrieval, systems analysis and design, systems control) and associated equipment employed to collect, process, and present information. In broad terms, IT also includes office automation, multimedia, and telecommunications. It refers to anything related to computing technology, such as networking, hardware, software, the Internet, or the people that work with these technologies. Many companies now have IT departments for managing the computers, networks, and other technical areas of their businesses. IT jobs include computer programming, network administration, computer engineering, Web development, technical support, and many other related occupations. Since we live in the “information age,” information technology has become a part of our everyday lives.

Open Source: Open source doesn’t just mean access to the source code. The distribution terms of open-source software must comply with the following criteria: 1. Free Redistribution; 2. Source Code; 3. Derived Works; 4. Integrity of The Author's Source Code; 5. No Discrimination Against Persons or Groups; 6. No Discrimination Against Fields of Endeavor; 7. Distribution of License; 8. License Must Not Be Specific to a Product; 9. License Must Not Restrict Other Software; 10. License Must Be Technology-Neutral. For the complete definition see .

Information and Communications Technology (ICT): ICT refers to technologies that provide access to information through telecommunications. It is similar to Information Technology (IT), but focuses primarily on communication technologies. This includes the Internet, wireless networks, cell phones, and other communication mediums. In the past few decades, information and communication technologies have provided society with a vast array of new communication capabilities. For example, people can communicate in real-time with others in different countries using technologies such as instant messaging, voice over IP (VoIP), and video-conferencing.

Big Data: Big data has four distinct characteristics (so called 4V features): the data volume is huge (volume); the data type is diverse meaning a mixture of structured data, semi-structured data and unstructured data (variety); the streaming data is very high (velocity); and uncertain or imprecise data (veracity).

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