Sales Analysis A Business Scenario

Suppose that you are a sales manager, who is responsible for planning and implementing sales strategy. Your tasks include the following:

Suppose also that you have the data in Tables 1.1 through 1.3 available about your firm's materials, customers, and sales organization.

Table 1.1. MATERIALS

Material Number Material Name Material Description
MAT001 TEA Ice tea
MAT002 COFFEE Hot coffee
MAT003 COOKIE Fortune cookie
MAT004 DESK Computer desk
MAT005 TABLE Dining table
MAT006 CHAIR Leather chair
MAT007 BENCH Wood bench
MAT008 PEN Black pen
MAT009 PAPER White paper
MAT010 CORN America corn
MAT011 RICE Asia rice
MAT012 APPLE New York apple
MAT013 GRAPEFRUIT Florida grapefruit
MAT014 PEACH Washington peach
MAT015 ORANGE California orange

Table 1.2. CUSTOMERS

Customer ID Customer Name Customer Address
CUST001 Reliable Transportation Company 1 Transport Drive, Atlanta, GA 23002
CUST002 Finance One Corp 2 Finance Avenue, New York, NY, 10001
CUST003 Cool Book Publishers 3 Book Street, Boston, MA 02110
CUST004 However Forever Energy, Inc. 4 Energy Park, Houston, TX 35004
CUST005 Easy Computing Company 5 Computer Way, Dallas, TX 36543
CUST006 United Suppliers, Inc. 6 Suppliers Street, Chicago, IL 61114
CUST007 Mobile Communications, Inc. 7 Electronics District, Chicago, IL 62643
CUST008 Sports Motor Company 8 Motor Drive, Detroit, MI 55953
CUST009 Swan Stores 9 Riverside Road, Denver, CO 45692
CUST010 Hollywood Studio 10 Media Drive, Los Angeles, CA 78543
CUST011 One Source Technologies, Inc. 11 Technology Way, San Francisco, CA 73285
CUST012 Airspace Industries, Inc. 12 Air Lane, Seattle, WA 83476

Table 1.3. SALES ORGANIZATION

Sales Region Sales Office Sales Representative Sales Representative ID
EAST ATLANTA John SREP01
NEW YORK Steve SREP02
  Mary SREP03
MIDWEST DALLAS Michael SREP04
  Lisa SREP05
CHICAGO Kevin SREP06
  Chris SREP07
WEST DENVER[*] Sam SREP08
LOS ANGELES Eugene SREP09
SEATTLE Mark SREP10

[*] Prior to January 1, 2000, the Denver office was in the Midwest region.

You also have three years of sales data, as shown in Table 1.4.

Table 1.4. SALES DATA

Customer ID Sales Representative ID Material Number Per Unit Sales Price Unit of Measure Quantity Sold Transaction Date
CUST001 SREP01 MAT001 2 Case 1 19980304
CUST002 SREP02 MAT002 2 Case 2 19990526
CUST002 SREP02 MAT003 5 Case 3 19990730
CUST003 SREP03 MAT003 5 Case 4 20000101
CUST004 SREP04 MAT004 50 Each 5 19991023
CUST004 SREP04 MAT005 100 Each 6 19980904
CUST004 SREP04 MAT005 100 Each 7 19980529
CUST005 SREP05 MAT006 200 Each 8 19991108
CUST006 SREP06 MAT007 20 Each 9 20000408
CUST007 SREP07 MAT008 3 Dozen 10 20000901
CUST007 SREP07 MAT008 3 Dozen 1 19990424
CUST008 SREP08 MAT008 3 Dozen 2 19980328
CUST008 SREP08 MAT009 2 Case 3 19980203
CUST008 SREP08 MAT010 1 U.S. pound 4 19991104
CUST009 SREP09 MAT011 1.5 U.S. pound 5 20000407
CUST010 SREP10 MAT011 1.5 U.S. pound 6 20000701
CUST010 SREP10 MAT011 1.5 U.S. pound 7 19990924
CUST010 SREP10 MAT012 2 U.S. pound 8 19991224
CUST010 SREP10 MAT013 3 Case 9 20000308
CUST011 SREP10 MAT014 1 U.S. pound 10 19980627
CUST012 SREP11 MAT014 2 U.S. pound 1 19991209
CUST012 SREP11 MAT015 3 Case 2 19980221
CUST012 SREP11 MAT015 2 Case 3 20000705
CUST012 SREP11 MAT015 3.5 Case 4 20001225

The data in these tables represent a simplified business scenario. In the real world, you might have years of data and millions of records.

To succeed in the face of fierce market competition, you need to have a complete and up-to-date picture of your business and your business environment. The challenge lies in making the best use of data in decision support. In decision support, you need to perform many kinds of analysis.

This type of online analytical processing (OLAP) consumes a lot of computer resources because of the size of data. It cannot be carried out on an online transaction processing (OLTP) system, such as a sales management system. Instead, we need a dedicated system, which is the data warehouse.

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