required in the file
first mate
Business Intelligence (BI) Tools: Business Intelligence tools are essential for decision
support. They encompass a range of software applications and solutions that enable
organizations to collect, analyze, and present data to facilitate decision-making. BI tools often
include features like data querying, reporting, and dashboards, making it easier for users to
access insights from their data. They play a pivotal role in transforming raw data into
actionable information, aiding executives and managers in making informed decisions.
Natural Language Processing (NLP): Natural Language Processing is another critical
technology for decision support, particularly in the context of unstructured text data. NLP
algorithms can extract valuable insights from sources such as social media, customer reviews,
and news articles. This technology not only helps in sentiment analysis but also in
categorizing and summarizing large volumes of text data, providing decision-makers with a
better understanding of public sentiment, market trends, or customer feedback.
Blockchain Technology: Blockchain has gained prominence in decision support, primarily
in industries where data security and transparency are paramount, such as finance and supply
chain management. It offers a decentralized and immutable ledger that ensures the integrity
and traceability of data. Decision-makers can rely on blockchain to verify the authenticity of
transactions, contracts, or records, reducing the risk of fraud and errors. This technology
enhances trust in decision-making processes, especially in complex, multi-party scenarios.
A variety of technologies contribute to decision support by providing tools for data analysis,
predictive insights, and enhanced data security. Business Intelligence tools simplify data
visualization and reporting, while Natural Language Processing aids in understanding
unstructured data sources. Blockchain technology ensures data integrity and trustworthiness,
particularly in industries where these aspects are critical for sound decision-making. These
technologies collectively empower organizations to make informed choices in an increasingly
data-driven world.
Reference
Liang, Y., Liu, X., Zhang, J., & Wang, Z. (2020). A decision support system for sustainable
supplier selection based on a novel hybrid MCDM method combining QFD and VIKOR
under fuzzy environment. Sustainability, 12(2), 589. [6]
The second
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The increasing availability of data. The amount of data that is being generated and collected
is growing exponentially. This data can be used to gain insights into customer behavior,
market trends, and other factors that can help organizations make better decisions.
The decreasing cost of data storage and processing. The cost of storing and processing data
has been decreasing, making it more feasible for organizations to collect and analyze large
datasets.
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The advancement of analytical tools and techniques. There are a wide range of analytical
tools and techniques available that can be used to make sense of data. These tools are
becoming more powerful and easier to use, making it possible for more people to participate
in the decision-making process.
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The need for real-time decision making. In many cases, organizations need to make decisions
quickly in order to stay ahead of the competition. Analytics can help organizations to make
better, faster decisions by providing them with insights into current events and trends.
The need for collaboration. In today’s globalized economy, organizations need to be able to
collaborate with partners and suppliers in order to make decisions. Analytics can help to
facilitate collaboration by providing a common platform for sharing data and insights.
Here are three technologies that have been used for decision support:
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Data warehouses: Data warehouses are centralized repositories of data that can be used for
analysis. They allow organizations to collect and store data from a variety of sources, such as
operational systems, customer relationship management (CRM) systems, and marketing
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automation systems.
Business intelligence (BI) tools: BI tools are used to analyze data and generate reports. They
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can be used to identify trends, patterns, and anomalies in data.
Predictive analytics: Predictive analytics is a type of analytics that uses data to predict future
events. It can be used to forecast demand, identify risks, and make other predictions that can
help organizations make better decisions.
These are just a few of the factors that influence the evolving needs for analytics and decision
support. As the world becomes increasingly data-driven, the demand for these technologies
will continue to grow.
Ref: Kranth, S., & Kumar, P. (2018). Plant disease prediction using machine learning algorithms.
International Journal of Computer Applications, 182(25), 1-5. 2
College of Computing and Informatics
Discussion Board
Deadline: Tuesday 19/09/2023 @ 23:59
[Total Mark for this Assessment is 4]
Pg. 01
Purpose
In this discussion board, you will post your answer to the question to make you aware of
the changing business environments that lead to the need for computerized support of
managerial decision-making. You will also read and respond to 2 other classmate’s
postings. This is an excellent way for you to interact with your colleagues and share your
thoughts about their answers in a critical way.
Topic of the Discussion (100 – 200 words)
Action Item
Numerous factors from the external and internal environments are influencing the
process of decision-making. In your opinion, what are the most critical factors that
influence the evolving needs for Analytics and Decision Support? Also, list three
technologies that have been used for decision support.
Submission Instructions
• Access the discussion forum for this Discussion Board by clicking on the discussion
forum title.
• Click on “Create Thread.”
• Enter a title for your response in the “Subject” line.
• Type your answer into the message field to answer the question.
Submission Requirements
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Assure uniqueness and other qualities of academic writing when posting your
discussion.
Respond to two other classmates’ postings by critically reviewing your classmate’s
answer and stating with reasons which point you agree or disagree with.
Short responses such as “I agree”, “I disagree”, “You are right”, “Very good
answer”, etc., are NOT acceptable. You need to be critical with some substance.
Submission Due Date
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Post your answer and your 2 comments on your classmates’ answers
before Tuesday 19/09/2023 @ 11:59 PM.
Grading Criteria (4 Marks)
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3 marks for posting your answer, and
0.5 marks for each response to your classmate’s posting (2 x 0.5 = 1 mark)
Note that merely a copy/paste from the Internet will lead to a ZERO mark.
