Role of Big Data in Business Intelligence and IBM Cognos

The report analyses the role of big data in BI and IBM Cognos. It describes the advantages, threats of BI system and how IBM Cognos can assist the managers in decision making.

Running head: Information system for managers
Information system for managers
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Executive summary
The aim of this report is to analyse the role of big data in BI and analyse IBM cognos. Big
data has been an integrated part of business analytics. Business intelligence driven by big
data is key factor of business growth today. IBM cognos is such a tool for the data analytics
which can help the managers to effectively carry out decision making process for the
company. The report describes the advantages, threats of BI system.

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Table of Contents
Introduction................................................................................................................................3
Discussion..................................................................................................................................4
Cost reduction........................................................................................................................4
Faster and effective decision making.....................................................................................4
New services and products.....................................................................................................4
OLAP(Online analytical processing).....................................................................................4
Corporate Performance Management (CPM)........................................................................5
Real time BI...........................................................................................................................5
Data Warehousing..................................................................................................................5
DataSources............................................................................................................................5
How IBM cognos can assist the managers.............................................................................6
Conclusion..................................................................................................................................6
References..................................................................................................................................7

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Introduction
Big data can be fundamentally described as huge amount of data which can be both
structured and unstructured. Big data is undoubtedly one of the most important factors to run
business. Big data is very important for the mangers in order to take decision regarding the
business as the analysis of big data gives in depth information which can lead to better
decision making and strategy determination by the managers. Business intelligence is a
method of analysing data by using various tools, procedures to help managers, executives to
create reports and take effective decisions.
Discussion
Big data has become an integrated part of modern techniques of decision making in
corporate world(John Walker, 2014). It helps to explore new opportunity for the companies
reducing cost, growing business and so on. The main benefits of using big data are
Cost reduction
Big data technologies, for example, Hadoop and cloud computing based analytics
bring a larger amount of cost benefits with regards to storage of a lot of information, in
addition to they can determine more effective process for business.
Faster and effective decision making.
With the speed of Hadoop and analysis of data along with the capacity to analyse
information(Provost & Fawcett, 2013), organizations can analyse data promptly and take
decision based on what information they have gathered.

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New services and products
With the capability to measure client needs and fulfilment through analysis comes the
ability to give clients the product or service demand. Companies with enormous information
analysis, are making new items to meet clients' demands.
The main components of business intelligence are
OLAP(Online analytical processing)
OLAP is a component which provides the managers to sort and select aggregates of
data to monitor strategically(Murdoch&Detsky, 2013). With the software like IBM cognosthe
companies can use data to make necessary modification to the business strategy.
Corporate Performance Management (CPM)
CPM is a tool that provides statistics to the managers about a product or a service
provided by the company to its clients.The data gathered by the CPM tool can also be
analysed to predict in which markets a new product may have demand and be successful.
Real time BI
The component has increasing demand as it can respond to real time messaging
system, digital displays using software. This helps mangers to analyse in real time and
announce decisions immediately like providing offers in restaurants depending on the
demand of the customers.
Data Warehousing
Data warehousing lets the managers to go through different components of data which
are interrelated and helps in driving the business effectively and provides growth. Data
warehousing also stores a significantly large amount of information in such procedure that it
becomes beneficial to different departments of the company.

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Data Sources
This component is related to how data is stored in various forms. It is related to taking
raw data and by using various software to convert it to meaningful source of data.
Business intelligence is legal because it a more scientific and research dependent
method of business analysis. It collects data and uses them for future decision making. Data
collection is done with the permission of the customers so it is legal.
The advantages of BI is that it provides capability to take fact based decisions,
improves the sales of the company and better negotiations(IşıK, Jones&Sidorova, 2013). It
reduces waste of money due to wrong decisions taken by managers and executives. BI can
help a company to assess its strengths, compare its market position against its rival
companies and identify new avenues.
The risks of BI are wrong choice of BI tool, which can be avoided by detailed product
evaluation of the tool before implementation(Wu, Chen & Olson, 2014). Rigidity of the
management to changethe existing system is another major problem. The threat can be
mitigated with effective communication and describing the benefits with proper proof. Poor
data quality is also a risk for BI. Lack of adequate data can lead to failure of BI and damage
the decision making process severely. The issue can be solved by putting strict data alteration
managementprocess.
How IBM cognos can assist the managers
The IBM cognos critically analyses data and provides managers well researched
information to decide the strategies for the company(Davis &Woratschek, 2015). As an
example owner of a restaurant can provide offers on food items which are preferred mostly
by customers to increase the sale. The strategy of giving offer on hot soups in a cold day can
attract more customers to the restaurants. Offering combo deals on the most demanded

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products can increase sell in a huge scale. Managers can reduce cost by taking faster
decisions like stopping production of an obsolete item which is not used by many customers
now a days.
Conclusion
BI is in every aspect useful because of its data driven approach and tools like IBM
cognos which is widely used for analytics can give a company edge over its rivals and
provide better products and service to its customers.

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References
Davis, G. A., &Woratschek, C. R. (2015). Evaluating business intelligence/business analytics
software for use in the information systems curriculum. Information Systems
Education Journal, 13(1), 23.
IşıK, Ö., Jones, M. C., &Sidorova, A. (2013). Business intelligence success: The roles of BI
capabilities and decision environments. Information & Management, 50(1), 13-23.
John Walker, S. (2014). Big data: A revolution that will transform how we live, work, and
think.
Murdoch, T. B., &Detsky, A. S. (2013). The inevitable application of big data to health
care. Jama, 309(13), 1351-1352.
Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-
driven decision making. Big data, 1(1), 51-59.
Wu, D. D., Chen, S. H., & Olson, D. L. (2014). Business intelligence in risk management:
Some recent progresses. Information Sciences, 256, 1-7.