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Fundamentals
of Big Data & Business Analytics
1. The emerging technological
development of big data is recognized as one of the most important areas of
future information technology and is evolving at a rapid speed, driven in part
by social media and the Internet of Things (IoT) phenomenon. The technological
developments in big data infrastructure, analytics, and services allow firms to
transform themselves into data-driven organizations. IDC (2015) forecasted that
the big data technology and services market will grow at a compound annual
growth rate of 23.1% over the 2014—2019 period, with annual spending reaching
$48.6 billion in 2019. While structured data is an essential part of big data,
more and more data are created in unstructured video and image forms, which
traditional data management technologies are inadequate to process. A large
portion of data worldwide have been generated by billions of IoT devices such
as smart home appliances, wearable devices, and environmental sensors.
To meet the ever-increasing storage
and processing needs of big data, several new big data platforms are emerging,
including NoSQL databases as an alternative to traditional relational databases
and Hadoop as an open-source framework for inexpensive distributed clusters of
commodity hardware. *
Source: *https://e-tarjome.com/storage/panel/fileuploads/2019-02-27/1551256718_E10700-
e-tarjome.pdf
a) Mention at least 2 possible
business applications which are enabled by the existence of big data platforms
and how do these leverage big data?
Answer:
Introduction:
Big Data is a
collection of information that is tremendous in volume yet developing
exponentially with time. It is data with such a large size and complexity that
none of the traditional data management tools can store it or process it
efficiently. Big Data is additional information but with enormous size.
2. State 3 use-cases of business
analytics within the retail industry, highlighting usage of descriptive,
predictive, and prescriptive analytics (2 each). Give an example of how mobile
analytics has been implemented in the industry and the resultant impact. (10 Marks)
Answer:
Introduction:
Organizations use analytics to investigate and inspect their
information and afterward change their discoveries into bits of knowledge that
eventually help chiefs, administrators and operational workers improve, more
educated business choices. Three key sorts of investigation organizations use
are descriptive examination, what has occurred in a business; prescient
examination, what could occur; and prescriptive examination, what ought to
occur. While every
3. “HURRICANE FRANCES was on its
way, barreling across the Caribbean, threatening a direct hit on Florida’s
Atlantic coast. Residents made for higher ground, but far away, in Bentonville,
Ark., executives at Wal-Mart Stores decided that the situation offered a great
opportunity for one of their newest data-driven weapons, something that the
company calls predictive technology. A week ahead of the storm’s landfall,
Linda M. Dillman, Wal-Mart’s chief information officer, pressed her staff to
come up with forecasts based on what had happened when Hurricane Charley struck
several weeks earlier.”
a. Which type of analytics will be
best suited to solve this problem and which technique will you apply in this
case? Explain the data needed to solve this problem. (5 Marks)
Answer:
Introduction:
Hurricane storm Frances was on its way, barreling across the
Caribbean, undermining an immediate hit on Florida's Atlantic coast.
Inhabitants made for higher ground. In any case, far away, in Bentonville,
Ark., chiefs at Wal-Mart Stores concluded that the circumstance offered an
extraordinary chance for one of their most up to date information driven
weapons - predictive
3 b. Explain the difference between
BI and BA as to how can they help optimize supply chain in this case?
Illustrate the possible outcome achieved in each case (BI vs. BA) and how they
enable business objectives. You can make certain assumptions but highlight them
clearly. (5 Marks)
Answer:
Introduction:
Supply
Chain Agility is essential for organizations to stay competitive in today's
dynamic business environment. There is increasing interest in deploying
Business Intelligence (BI) in the Supply Chain Management (SCM) context to
improve Supply Chain (SC) Agility. However, there is limited research exploring
BI contributions to SC Agility.
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