MG-GY 6203 - Data Visualization for Business Intelligence
ASSIGNMENT-2
You are a Market Analyst for a Major Hotel Brand!
Perform. and present your exploratory data analysis on the “Reservations” data (available under Assignments).
As a lead analyst, you have to decide how to analyze the data and present the findings.
Prepare a slide-deck (not more than 15 slides) to share your insights with the hotel management – Be professional!
Prepare interactive Tableau sheets for the senior managers to explore further on their own.
In your slide-deck, provide appropriate instructions for them on how to use the interactive Tableau sheets, with appropriate references to the respective sheets.
Your presentation/Tableau sheets should incorporate visualization best practices (including Gestalt Psychology principles), a
of each of the following:
nd should demonstrate use
Dual axis charts
Combo charts
Highlighters
Table Calculations
Sets
Filters
Parameters
The extent to which you use each of the above features depends on your individual presentation, but there should be at least two good instances for each. You could combine more than one feature within the same visualization.
Submit your work on Brightspace as Tableau packaged workbook (.twbx) and PowerPoint slides by 11:59pm on Sunday, Oct’ 12.
You can save your work as Tableau packaged workbook via File->Save as->Tableau packaged workbook (.twbx).
You can export your Tableau visualizations to PowerPoint via File
communicate your analyses/insights well to the audience! ->Export as PowerPoint. You must refine the PowerPoint slides after this step to make it professional and communicate your analyses/insights well to the audience!
You will be penalized if you do not submit the files in the correct format.
Explanation of Selected Data Fields for the Reservations Dataset
• is_cancelend: Value indicating if the booking was canceled (1) or not (0).
• lead_time: Number of days that elapsed between the entering date of the booking into the PMS and the arrival date.
• stays_in_weekend_nights: Number of weekend nights (Saturday or Sunday) the guest stayed or booked to stay at the hotel.
• stays_in_week_nights: Number of week nights (Monday to Friday) the guest stayed or booked to stay at the hotel.
• country: Country of origin of the guest.
• market_segment: Market segment designation. The term “TA” means “Travel Agents” and “TO” means “Tour Operators”.
• is_repeated_guest: Value indicating if the booking name was from a repeated guest (1) or not (0)
• previous_cancellations: Number of previous bookings that were cancelled by the customer prior to the current booking.
• previous_bookings_not_canceled: Number of previous bookings not cancelled by the customer prior to the current booking.
• booking_changes: Number of changes/amendments made to the booking from the moment the booking was entered until check-in or cancellation.
• days_in_waiting_list: Number of days the booking was in the waiting list before it was confirmed to the customer
• customer_type: Group: When the booking is associated to a group; Transient – when the booking is not part of a group or contract, and is not associated to other transient booking; Transient-party – when the booking is transient, but is associated to at least other transient booking.
• adr: Average Daily Rate (Calculated by dividing the sum of all lodging transactions by the total number of staying nights)
• reservation_status: Check-Out – customer has checked in but already departed; No-Show – customer did not check-in and did inform. the hotel of the reason why.
• reservation_status_date: Date at which the last status was set. This variable can be used in conjunction with the ReservationStatus to understand when was the booking canceled or when did the customer checked-out of the hotel.