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data merging

Joining Food Orders to Bookings for Revenue Insights

Enriching Bookings with Movie Details

Stacking Filtered Bookings for Trend Analysis with Concatenate

Outer Joins for Comprehensive Booking Analysis with Joiner

Lab Multi-Table Join for Food Revenue per Movie with Joiner

SANIA TANWEER

RA2311003010872

CLASS: CLS 919

DATA MERGING LAB

Convert string show_datetimeto date time
String to Date&Time
Read movie.csv
CSV Reader
Fill Missing valuesas Mean
Missing Value
Convert string booking_datetimeto date time
String to Date&Time
Convert string booking_datetimeto date time
String to Date&Time
To associate each food order with its corresponding booking details
Joiner
Remove any duplicatebookings
Duplicate Row Filter
Convert Rating Data Type
String to Number
Readbooking.csv
CSV Reader
To enrich the data with show timing and movie linkage
Joiner
To attach movie information (title, genre) to every food order, enabling movie-level analysis
Joiner
To visualize which movies generate the highest food sales
Bar Chart
To aggregate total food sales per movie, identifying top food-revenue films
Column Resorter
Convert stringto date time
String to Date&Time
Removes duplicate keys
Duplicate Row Filter
Remove any duplicate bookings
Duplicate Row Filter
Remove Duplicate Movies
Duplicate Row Filter
Combines Booking and Show data while retaining all records
Joiner
shows only bookings that don’t have a matching show
Row Filter
Value Lookup
booking.csv
CSV Reader
show.csv
CSV Reader
Fill Missing valuesas Mean
Missing Value
Rename Columns
Column Renamer
Read movie.csv
CSV Reader
Read booking.csv
CSV Reader
Convert booking_datetime to Date&Time
String to Date&Time
Filter Recent Bookings (After 2025-03-01)
Rule-based Row Filter
Filter Older Bookings (Before 2025-03-01)
Rule-based Row Filter
To label all recent bookings as part of the "Recent" period
Constant Value Column Appender
To label all older bookings as part of the "Older" period
Constant Value Column Appender
Convert to Date&Time
String to Date&Time
Convert Rating Data Type
String to Number
Joiner
Convert to Date&Time
String to Date&Time
Convert to Date&Time
String to Date&Time
Remove any duplicatebookings
Duplicate Row Filter
Remove any duplicatebookings
Duplicate Row Filter
Remove Duplicate Movies
Duplicate Row Filter
booking.csv
CSV Reader
Read foodorder.csv
CSV Reader
Convert to Date&Time
String to Date&Time
Readshow.csv
CSV Reader
this output shows shows that have no bookings
Row Filter
Join booking &foodorder onbooking_id
Joiner
Calculate Total Revenue =total booking cost+total food order cost
Expression
combine both filtered datasets vertically
Concatenate
Readbooking.csv
CSV Reader
Convert string order_datetimeto date time
String to Date&Time
visualize revenue trends across booking periods
Pie Chart
Readfoodorder.csv
CSV Reader
Rename Columns
Column Renamer
Read show.csv
CSV Reader

Nodes

Extensions

Links

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: Shagun
Created at: 2026-06-09
On NodePit since: 2026-06-09
Last update: 2026-06-09
Created with KNIME version: v5.8.0

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