Running head: LITERATURE REVIEW
Literature Review
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LITERATURE REVIEW
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Literature Review
Tableau software is Business Intelligence (B) software which is both utilized in
transforming raw data into a more meaningful and useful information which is critical in the
process of business analysis functions and operations. Tableau software enables the users to
develop intuitive graphics, dashboards, and reports in a simpler faster way which is a drag and
drop techniques. The tableau software has maintained its competitive advantage through its
innovative technologies and its ease of use features which has made it successful in the
competitive market. Business Intelligence entails the tools and systems that play a critical role in
the strategic planning process within any business organization. The business intelligence will
enable the company to gather, store, access and analyze the required and relevant information or
data which will help in the process of decision making. This paper is aimed to discuss the role of
Tableau Software in Business Intelligence (BI) and analytics, which will in turn lead to a
strategic and practical decision within an organization.
Typically, the literature review will discuss the various elements of the tableau software
and the business intelligence which are essential for the successful operation of the firm. The
measured variables included the Business intelligence systems, use of the tableau software and
the process of decision-making within an organization (Power, 2007). The various theories and
theoretical frameworks are also elaborated to provide more insight to the discussed topic. The
use of the tableau software is indeed a valuable tool to help the organizations in their business
intelligence efforts and decision making.
Business Intelligence (BI) Structure
Various scholars and studies have differently defined the term business intelligence.
Therefore, there are multiple explanations concerning Business Intelligence either from the
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literature world or in the business environment. Business Intelligence can be defined as an
organized and systematic procedure through which the organizations acquire, analyze, and
distribute information from both the internal and external information sources which are essential
for their business operations and the process of decision making (Lonnqvist & Pirttimaki 2006).
The term business intelligence has also been concerned as a particular reason for data-driven
decision support system (DSS). A business intelligence system is a data motivated decision
support system that majorly helps in querying of an old database and the creation of periodic
report summary. By enhancing the business’s capability to structure given information and
making it accessible, the business intelligence systems have the capacity to maximize the
utilization of information, hence developing a competitive advantage in the industry.
Business intelligence was also considered as the process through which data coming from
both the internal and external sources can be gathered and analyzed to generate relevant
information. Some of the benefits a company can derive from the use of Business Intelligence
are multifaceted, and they include the following: The identification of the profitable clients,
discovery of the best-soled products and services, which service is highly profitable, what type of
customer is least millennial and loyal, detects the deceiving behavior and actions and forecast the
market environments on the trends among other benefits (Ranjan, 2009). However, the business
intelligence systems can be broadly defined as the broad category of technologies, software,
applications and processes for collecting, storing, accessing and analyzing various data that can
help the users to make crucial decisions.
The business intelligence cannot be singly applied, but it can efficiently work with
interlocking elements that must always work together seemly to deliver a business value.
Notably, there are is a variety of Business Intelligence (BI) solutions that serves different
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purposes in the organization. Specifically, the generalized structure of the business intelligence
consists of the elements such as the data source, ETL, data warehouse, and the analytical and
visualization tools (Watson, 2009).
As stated by Watson & Wixom (2007), the portrayed components frequently reflect the
four primary stages of the data processing cycle. For instance, pre-processing which involves the
data cleaning, data selection and data transformation and the integration that is responsible for
data merging, data mining and pattern evaluation within the application layer and the
presentation of data within the display layer.
Tableau Software Structure and its role in Business Intelligence and Analytics
Tableau software is a drag and drop business intelligence tool that allows the regular
users to quickly manipulate data and develop easy-to-publish reports or information and
dashboards (Watson, 2009). Tableau helps individuals and organizations to see and understand
the various data. Tableau will assist anyone to quickly analyze, visualize and share a vast amount
of information to different people or agencies. However, Tableau is not applicable to non-profit
organizations as most of the business intelligence tools; it can connect to and create performance
metrics for any tabular data. Tableau software structure is quite logical and straight forwards.
The application’s layout is very simple for the non-IT professional to understand.
Data Integration Capabilities
Tableau software will assist the business in its process of business intelligence by its
capacity to integrate data. This is because the secure information is derived from data and it’s
always perceived as a valuable asset to the productivity of any business (Roekel et al., 2009).
With the tableau software enterprises having a complex data which are spread over multiple
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databases including the text field, spreadsheets, access and the public services will achieve its
benefit through the business intelligence. It is very critical for the goo business analytical
software such as Tableau to provide linkages to various data sources to facilitate the business
analysis or business discovery on data existing in a different location. In Tableau software
environment, the international data can be done through the use of the interface. The interface
usually needs no scripting skills. Besides, Tableau facilitates ease of use for any level of users of
the business intelligence system in the process of making critical decisions. The capability to
integrate multiple data sources into one particular platform can save the company a lot of time
and also enhance convenience and value for the users.
Tableau ability to Connect to Multiple Sources of Data
Tableau software has native connectors to several common databases, including
Microsoft SQL Server, My SQL, Oracle, and Teradata among others. If in any case, the native
connectors are not available, the users can have access to data through the use of ODBC which
stands for open database connectivity that uses the Open Database Connectivity standard. The
multiple lines of evidence which can be supported by the tableau software are significant in
enhancing sustainability and effectiveness in the business management through business
intelligence (Negash, 2004). Tableau software integrates a technology which is traditional querybased technology that operates from a disk, and it typically requires that the database remains in
the hard drive, while the software is actively querying it.
Theoretical Framework: Decision Making Process
Review of Existing Research methodology
References
Lukevich, M., Vitt, & Misner, S. (2002) ‘Business Intelligence,' Microsoft Press.
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Negash, S. (2004). Business Intelligence. Online, 13(Accessed:10/06/2016). Retrieved from
http://redient.com/business-intelligence/
Power, D., (2007, May 27th). "Tom Davenport Interview: Competing on Analytics,"
DSSResources.COM. Read 7.12.2016, available at
http://dssresources.com/interviews/davenport/davenport05272007.htm l
Ranjan, J. (2009). Business Intelligence: Concepts, Components, Techniques, and Benefits.
Journal of Theoretical and Applied Information Technology, 9(1), 60.
https://doi.org/10.2139/ssrn.2150581
Roekel, H. V., Linders, J., Raja, K., Reboullet, T., & Ommerborn, G. (2009). The BI framework:
How to turn information into a competitive asset.Reading: Logica.
Wasmann, M., & Spruit, M. (2012). Performance management within social network sites: the
social network intelligence process method.International Journal of Business Intelligence
Research (IJBIR), 3(2), 49-63.
Watson, H. J. (2009). Tutorial: Business Intelligence – Past, Present, and Future.
Communications of the Association for Information Systems, 25.
Watson, H. J., & Wixom, B. H. (2007). The current state of Business Intelligence. Computer,
9(40), 96–99
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