Word limit: 3500 words
(This assignment consists of two parts. The word limits for parts 1 and 2
are 1500 words and 2000 words, respectively.)

Weighting: 100%
(This assignment consists of two parts. The weightings for parts 1 and 2
are 40% and 60%, respectively.)

Requirements for part 1:
In part 1, you need to select and discuss one analytic technique we learnt
from the lectures (i.e., classification, regression, clustering, association
rules). When preparing your answers, include: What is the technique, why
it is important, and provide case examples to explain how it can be used
in business to support decision making.

Requirements forpart 2:
In part 2, you need to provide a critical analysis of a specific tool or
technique for big data analytics. You can choose any big data tool or
technique taught in the seminars or based on your private study (e.g.,
MapReduce, HDFS, HBase, Pig, Hive, Qlik, Minitab, EViews, etc.).

The following information provides some guidelines about what should be
included in this part.
 Explain why this tool or technique is suitable for big data analytics.
 Explain, demonstrate, and document how to use this tool or technique
(e.g., installation, data processing/analysis, output results, etc.)

You should show your own (not others’) steps of using this tool or technique. A direct copy of others’ steps without any modification will be given zero marks for this part.
 Provide and explain a real world case about how this tool or technique
is used in business.
 Benchmark this tool or technique in terms of application and
contribution in business.