07 Time Series Analysis
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May 5, 2024
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Time Series Analysis - Sales Forecast
Authors:
Nitin Kalé, University of Southern California
Nancy Jones, San Diego State University
Revised:
Liz Simmons and Audrey Zhao, February 2023
OBJECTIVE
The objective of this exercise is to use Time Series analysis to forecast Global Bike U.S. sales and interpret the reliability of the forecasting model.
ACTIVITIES
Import and prepare data.
Configure forecasting models.
Analyze and interpret output from models.
SOFTWARE PREREQUISITES
Access to SAP Analytics Cloud with Predictive Scenarios
DATA SET
GBSales_transactions.xlsx
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Scenario
Nina and other managers at Global Bike are getting ready to develop strategic plans and budgets for the upcoming year. Therefore, Nina is interested in forecasting Sales Revenue for at least one year from the date for which data are available. She will use Time Series Analysis for forecasting.
Time Series Analysis
Time Series Analysis
is a technique that analysts use to (a) uncover any implicit structure (patterns or trends) in the data and (b) model that structure to make forecasts. The assumption is that the future, at least in the short term, will continue the structure of the past. This technique is useful wherever forecasting values such as sales quantities, airline passenger volume, economic metrics, and traffic volume are needed.
1.
Acquire and Aggregate the Data
The data set given to Nina includes sales transactions from 2008 through 2020. To create a forecast, you will want to consolidate/aggregate the details into one-month time periods. You can do this easily in a private model in SAC. a.
Select Stories
from the menu on the left side of the screen. b.
Select Create New Canvas
.
c.
Select Add data.
i.
Select Data uploaded from a File
Source File
.
(1)Find and open the Excel sheet GBSales_transactions.xlsx
.
ii.
Import
. iii.
On the Data tab of the Story do the following:
(1)
Change Year and Month to Dimensions
(2)Change Year and Month Details. (Click the column, then click the Details icon to the right of the Builder pane title.)
(i) Change Data Type to String
.
(ii)Check to be sure Statistical Type is set to Continuous
.
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(3)
Concatenate Month and Year
(select using the CTRL key in this order) using the Concatenate using “,”
transformation function. The
name of the column will default to Month_Year. Figure 1: Concatenate Month and Year
iv.
Go to the Story view; create a Table
.
(1)Include Revenue
as the Measure and Currency and Month_Year
, in
that order, as Rows. Your results should look similar to those in
Figure 2.
Figure 2: Create the Table
d.
Export
the results of the table using the Export function under the table’s More Actions. The parameters for the Export function are shown in .
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