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Overview of PeopleSoft Data Warehouse Implementation

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In star schema development it is the central table used to connect dimensions ... General Ledger and Profitability. Hyperion Integration. Implementation Consideration ... – PowerPoint PPT presentation

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Title: Overview of PeopleSoft Data Warehouse Implementation


1
Overview of PeopleSoft Data Warehouse
Implementation
  • August 3, 2006

2
EPM Architecture
3
Multidimensional Warehouse
  • Facts typically numeric values to quantify or
    calculate a companys activities. In star schema
    development it is the central table used to
    connect dimensions

4
Multidimensional Warehouse
  • Dimensions - Allow analytics across subject
    matter areas
  • Uses Conformed dimensions - dimensions that
    mean the same thing in every possible fact table
    to which they can be joinedand therefore the
    same thing in every functional warehouse.
  • Common (Calendar, Time, Business Unit, Time Zone,
    Unit of Measure, Currency, Language)
  • Shared (Department, Item, Account, Person,
    Jobcode, etc.)
  • Subject Area (Billing Status GL Prof, Aging
    Category- Payables)

5
PeopleSoft Mart
  • Mart refers to a PeopleSoft product that contains
    specific subject areas related to one of the
    delivered PeopleSoft functional warehouses.
  • Marts are derived from the MDW and are modeled to
    support analytic requirements, but not limit you
    to reporting only in that subject area.
  • Must license a supported reporting tool
    separately (e.g. Hyperion Reports) to access data
    open reporting structure

6
Supply Chain Warehouse
  • Supports reporting for the following business
    processes
  • Order Fulfillment
  • Procurement
  • Datamarts
  • Procurement
  • Spend
  • Inventory
  • Sales Orders

7
Financial Warehouse
  • Supports reporting for the following business
    processes
  • Procurement
  • Financial Control and Reporting
  • Project Management
  • Financial Control and Reporting
  • Datamarts
  • Payables
  • General Ledger and Profitability

8
Hyperion Integration
9
Implementation Consideration
  • Our project timeline and scope will be dependent
    on Transaction applications.
  • Understanding Source data, customizations and
    configuration is necessary to validate delivered
    transformations, dimensions, and facts.

10
Overview of reporting environment
  • Datamarts
  • Payables
  • General Ledger and Profitability

11
Overview of reporting environment
Rept Rqmt 2
Rept Rqmt 5
Rept Rqmt 1
Rept Rqmt 3
Rept Rqmt 4
Rept Rqmt 6
12
GL Profitability
D_DEPT
D_DET_PERIOD
F_JOURNAL
D_JRNL_SOURCE
D_ACCOUNT
13
GL Profitability
D_DEPT_TBL
D_DET_PERIOD
F_LEDGER
D_BOOK_CODE
D_ACCOUNT
14
GL Profitability
D_ABM_OBJECT
D_DET_PERIOD
F_PROFITABILITY
D_PRJ
D_ACCOUNT
15
Payables
D_DEPT
D_PATTERN_DAY
F_AP_ACCOUNT_LN
D_BU_LED_GRP_TBL
D_ACCOUNT
16
Payables
D_PERSON_AP_OPID
D_DAY
D_AP_VTR_TYPE
F_AP_TRAN
D_AP_PTR_TYPE
D_AP_DOC_TYPE
D_ACCOUNT
17
Payables
D_SUPPLIER
D_DAY
F_VCHR_MTCH_EXP
D_PERSON_APOPID
D_ MATCH_RULE
18
Inventory
D_LOT
D_DAY
F_INV_LDGR
D_UOM
D_ INV_ITEM
19
Inventory
D_LOT
D_DAY
F_INV_TRANS
D_RECV_LN_SHP
D_DEMAND_INF_INV
D_ PHYSICAL_INV
20
Inventory
D_LOT
D_DAY
F_PHYSICAL_INV
D_INV_LOCATION
D_PO_STATUS
D_ SUPPLIER
21
Inventory
D_LOT
F_INV_CYCLE_CNT
D_INV_LOCATION
D_ INV_ITEM
22
Procurement
D_PO_LINE
F_PO_SHIP_RCPT
D_ACCOUNT
D_ DLVRY_STATUS
23
Procurement
D_RTVLN_STATUS
F_RTV_DIST
D_SUPPLIER
D_ VOUCHER
24
Procurement
D_MTCH_STATUS
F_MTCH_ANLYS
D_MATCH_RULE
D_ INV_ITEM
25
Procurement
26
Spend
D_PO_HDR
D_DAY
F_VCHR_LN
D_SUPPLIER
D_ INV_ITEM
27
Justification Done Planning Need Project
Plan Business Analysis Not done Design Not
done but a huge head start Construction Not done
but a huge head start Deployment Not done
Delivered Vanilla Design and Construction is
STRONG - Huge Head Start
28
(No Transcript)
29
Recommended reporting solutions
  • Divided into major categories
  • Data Warehouse
  • On-line Lookup
  • Delivered report (i.e. SQR)
  • Defer until later phase
  • Download
  • Not needed
  • Considerations
  • Sufficient granularity
  • Sufficient timeliness (i.e. Data Warehouse 1 day
    lag)
  • Has all the fields?
  • Issues decision still pending on data capture
  • Issues requires further development in Data
    Warehouse
  • Historical data will not be there day one
  • Goal To have the best solution for this phase,
    with time and resource constraints.

30
Status of report development
  • Data in Warehouse
  • Models in Warehouse
  • complete (i.e. 7 out of 40)
  • Design status
  • Design pending issues, Design Not signed off,
    Design signed off
  • Development status
  • In development
  • Developed, ready to be QAd
  • Development QAd and Signed off
  • Naming standards used

31
Technical Side
32
Tip for organizing documentation
33
ETL Ascential Jobs
34
Tip for organizing ETL Ascential Jobs
35
Tip for organizing ETL Ascential Jobs
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