Task This task requires you to use exploratory data analytics skills to derive key insights from a given dataset. You ar

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Task This task requires you to use exploratory data analytics
skills to derive key insights from a given dataset. You are free to
use any pre-processing operation(s) on the data such as
aggregations, calculated items, etc. and use (appropriate) chart
types to tell a compelling story from the data. Make sure you
present at least 5 key insights visually using charts and explain
in writing the key insights your charts are communicating. Try and
present your insights in a logical order (a cohesive narrative)
where possible. Dataset
Dataset BANK_DIRECT_MARKETING - This dataset is pre-loaded into
SAS Viya or can be downloaded from course level Moodle site
Background The dataset relates to a direct marketing campaign of a
Portuguese banking institution. The marketing campaign was based on
phone calls and aimed to promote a specific product (a term
deposit). Often, more than one contact to the same client was
required to determine if the customer would subscribe to the
promoted product. The data dictionary is provided in the appendix.
Primary variable of interest is ‘y’, which identifies if a customer
subscribed to the product. Assume you work as a Business Analytics
expert in this bank. Your Marketing Manager hands this dataset to
you and asks you to uncover useful insights that may be hidden in
the dataset. Apply your exploratory data analysis skills to derive
some insights from this dataset. Present your findings in a written
report. Report Requirements Your report should contain: 1. A brief
introduction – your interpretation of the background and the
problem. 2. A description of the dataset (Example: what the dataset
is about, number of categorical variables, number of measures,
descriptive statistics of key variables, etc.) 3. Overall aim of
your analysis 4. At least five key questions/hypotheses you want to
answer/test by interrogating the dataset (in a logical order) 5.
Methods: a. any data pre-processing you carried out b. what chart
types were used to answer each question (justification of your
selection) 6. Results and Discussion: images of charts and
interpretation of the charts you generated. In this section,
attempt to tell a story driven by your analytical insights. 7.
Conclusion (A short summary of the background and aim. What are the
key insights? How do they relate to your overall aim?
Recommendation, etc.) Marking Criteria Following areas of your
written report will be looked at when awarding marks. Item Marks
Introduction 4 Describing the dataset & setting an overall aim
for the analysis 6 Stating relevant questions/hypotheses to be
answered through exploratory analysis 5 Appropriateness of the
chart types/visualisation and accuracy of the generated charts 10
Interpretation of the charts (discussion of results) 15 Language,
logical flow of the data story (narrative) and conclusion 10 Total
50 Appendix: Data Dictionary 1- age 2- job: type of job 3- marital:
marital status 4 - education 5 - default: has credit in default? 6
- housing: has housing loan? 7- loan: has personal loan? 8 -
contact: contact communication type 9 - month: last contact month
of year 10 - day: contact day of month 11 - duration: last contact
duration, in seconds 12 - campaign: number of contacts performed
during this campaign and for this client (numeric, includes last
contact) 13 - pdays: number of days that passed by after the client
was last contacted from a previous campaign (numeric; -1 means
client was not previously contacted) 14 - previous: number of
contacts performed before this campaign and for this client
(numeric) 15 - poutcome: outcome of the previous marketing campaign
16 - Balance: available bank balance in existing accounts Primary
variable of interest: 17 - y - has the client subscribed a term
deposit? (Binary: ‘yes’, ‘no’)