Working with Data in Similar Time Periods

In certain applications, such as general ledger and legacy systems, tables may be organized so that columns identify similar time periods. For example, a single row may include all months of a year. In this case, each subsequent row includes a measure category as a data value; for example, a specific account number.

Table 14. Columns Defining Time Periods

PRODCODE

STATE

ACCOUNT

JAN

FEB

MAR

...

100-10-C001-S002-P001

AZ

Sales

672.00

241.00

287.00

 

100-10-C001-S002-P001

AZ

COGS

403.00

132.00

177.00

 

100-10-C001-S002-P001

CA

Sales

401.00

143.00

378.00

 

100-10-C001-S002-P001

CA

COGS

260.00

101.00

226.00

 
       

To create a dimension of the type time, Integration Server requires that all time identifiers be in one column and that accounts identifiers be in separate columns, as shown in Table 15. If data is stored with each month as an individual column, as shown in Table 14, restructure the data. Individual months should be data values in a MONTH column, and the measures categories, such as SALES, should be separate columns.

Table 15. Time Periods Stored as Data Values

PRODCODE

STATE

MONTH

SALES

COGS

100-10-C001-S002-P001

AZ

1

672.00

403.00

100-10-C001-S002-P001

AZ

2

241.00

132.00

100-10-C001-S002-P001

AZ

3

287.00

177.00

     

100-10-C001-S002-P001

CA

1

401.00

260.00

100-10-C001-S002-P001

CA

2

143.00

101.00

100-10-C001-S002-P001

CA

3

378.00

226.00

100-10-C001-S002-P001

AZ

1

672.00

403.00

     

You can write a program to convert the data to a table that uses the appropriate format or use the source database to transpose the columns (see Transposing Columns and Rows).