235958021 bi-apps-financial-analytics-on-jde
Transcript of 235958021 bi-apps-financial-analytics-on-jde
© Peak Indicators Limited
BI Apps - Financial Analytics on – JD Edwards
Overview, Implementation and Next Steps
Tony Cassidy & Shaun Mullen
June 2012
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Agenda
Introduction
BI Apps - Overview
BI Apps – Financial Analytics
BI Apps – Financial Analytics – JD Edwards Specifics
BISC Implementation
Customisation
Security
ETL Statistics
Training
Key Success Factors - General
Key Success Factors - BISC
Next Steps
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Introduction
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Customer: In Ireland
Business Needs: Ability to report on Non Pay and Open Commitments
Ability to report More Frequently than before
Open to Overall Improvements on Operational Financial Reporting
Deploy in relatively short time frame
Budget
Solution Considerations: OBIEE Existing
JD Edwards Existing
Immediate Operational Financial Reporting Requirement (Non Pay)
TCO on BI Apps - Financial Analytics V OBIEE Custom Product Layers = Schemas, ETL, Adapters & Dashboards
ROI on BI Apps – Financial Analytics – Wider Usage
Decision: BI Apps – Financial Analytics on JD Edwards
Introduction Business Need & Solution Consideration
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Introduction Decision = BI Continuum for JD Edwards
Oracle
EPM
Futu
re O
riente
d
Strategic Dynamic
Static Operational Past
Ori
ente
d
JDE E1
JDE E1 Standardized Reporting
• JDE E1 UBE, QBE (Query By Example)
• Oracle BI Publisher
1 1
JDE E1 Operational Consoles
• Financial Mgmt & Compliance Console
• Plant Manager Dashboard
2 2
Oracle Predictive Modeling Tools
• Hyperion Essbase
• Real Time Decisions
5
5 Oracle EPM • Hyperion Planning and Budgeting
• Hyperion Financial Management
• more
4
4 Oracle BI Applications • Financial Analytics
• Supply Chain & Order Mgmt Analytics
• Procurement & Spend Analytics
• more
3
3
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BI Apps - Overview
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BI Apps - Overview
Oracle BI Applications (BI Apps) is a complete data-warehouse solution based on the Oracle BI Enterprise Edition product suite
BI Apps enables organisations to rapidly deploy an end-to-end analytics solution providing a comprehensive and rich set of Business Intelligence dashboards
BI Apps comes with pre-built meta-data to source from various source transactional applications including: Oracle eBusiness Suite Siebel CRM Peoplesoft JD Edwards
BI Apps is designed so that it can be tailored to suit an organisation’s own
individual reporting needs
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BI Apps - Overview
Faster Delivery, Lower TCO
Build from Scratch with Traditional BI Tools
Oracle Analytic Applications
Prebuilt Business Adapters for Oracle, PeopleSoft, Siebel, SAP, others
Prebuilt DW design, adapts to your EDW
Role-based dashboards and thousands of pre-defined metrics
Easy to use, easy to adapt
Weeks or Months
Back-end ETL and Mapping
DW Design
Define Metrics & Dashboards
Back-end ETL and Mapping
DW Design
Define Metrics & Dashboards
Training / Roll-out
Training / Rollout
Months or Years
Oracle Analytic Applications solutions approach:
• Faster time to value • Lower TCO • Assured business value
Source: Patricia Seybold Research, Gartner, Merrill Lynch, Oracle Analysis
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Oracle Business Intelligence Enterprise Edition Plus (OBIEE)
Oracle Business Intelligence Applications (BI Apps) –Prebuilt Metadata
BI Apps - Overview OBIEE V BI Apps – Why?
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Extension of DW Schema for extension columns, additional tables, external sources, aggregates, indices, etc.
Extension of ETL for extension columns, descriptive flex fields, additional tables, external sources, etc.
Additional derived metrics, custom drill paths, exposing extensions in physical, logical and presentation layer, etc.
Additional dashboards and reports, guided and conditional navigations, iBot’s, etc.
Level of Effort
Degree of Customization
Easy
Moderate
Intermediate
Involved
Dashboards & Reports
OBIEE Metadata
DW Schema
ETL
BI Apps - Overview Effort & Customization Balance
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Ad
min
istr
atio
n
Met
adat
a
Oracle BI Presentation
Services
Dashboards by Role
Reports, Analysis / Analytic Workflows
Metrics / KPIs
Logical Model / Subject Areas
Physical Map
Oracle BI Server
Direct Access to Source Data
Data Warehouse / Data Model
ETL
Load Process
Staging Area
Extraction Process
DA
C
Federated Data Sources
Siebel Oracle PSFT EDW Other
Role Based Dashboards
Analytic Workflow
Guided Navigation
Security / Visibility
Alerts & Proactive Delivery
Logical to Physical Abstraction Layer
Calculations and Metrics Definition
Visibility & Personalization
Dynamic SQL Generation
Highly Parallel
Multistage and Customizable
Deployment Modularity
Abstracted Data Model
Conformed Dimensions
Heterogeneous Database support
Database specific indexing
BI Apps - Overview Architecture
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BI Apps - Financial Analytics
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Travel & Trans
Auto Comms & Media
Complex Mfg
Consumer Sector
Energy Financial Services
High Tech
Insurance & Health
Life Sciences
Public Sector
Oracle BI Suite Enterprise Edition
Prebuilt adapters:
Sales Service & Contact Center
Marketing Order Management & Fulfillment
Supply Chain Financials Human Resources
Pipeline Analysis
Triangulated Forecasting
Sales Team Effectiveness
Up-sell / Cross-sell
Cycle Time Analysis
Lead Conversion
Absence Management
Compensation Analysis
HR Performance
Workforce Profile
Learning Management
Recruitment Management
A/R & A/P Analysis
GL / Balance Sheet Analysis Customer & Product Profitability
P&L Analysis
Expense Management
Cash Flow Analysis
Supplier Performance
Spend Analysis
Procurement Cycle Times
Inventory Availability
Employee Expenses
BOM Analysis
Order Linearity
Orders vs. Available Inventory
Cycle Time Analysis
Backlog Analysis
Fulfillment Status
Customer Receivables
Campaign Scorecard
Response Rates
Product Propensity
Loyalty and Attrition
Market Basket Analysis
Campaign ROI
Churn Propensity
Customer Satisfaction
Resolution Rates
Service Rep Effectiveness
Service Cost Analysis
Service Trends
BI Apps – Financial Analytics Financial Subject Areas
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Payables Analytics Provides visibility into payments due to suppliers and expense line detail so managers can manage cash outflows and control expenses. When combined with Supply Chain Analytics, it allows full procurement analysis from Requisition to Check.
Receivables Analytics Monitors collections processes to show what customers buy and how they pay, enabling managers to identify overdue balances and other receivables bottlenecks. When combined with Oracle Sales Analytics and Oracle Order Management & Fulfillment Analytics, it enables more efficient management of the entire Lead to Cash process.
General Ledger & Profitability Analytics Incorporates detail-level general ledger transactions and cash flow analysis across locations, customers, products, sales territories, distribution channels, and business units. Identifies the customers and transactions that are providing maximum profits by product, location, department, and geographic detail. When combined with Marketing Analytics, it enables analysis of Campaign ROI and assists in customer segmentation.
BI Apps – Financial Analytics Comprehensive View of Financial Performance
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Pre-mapped metadata, including embedded best
practice calculations and metrics for Financial,
Executives and other Business Users.
Presentation Layer
Logical Business
Model
Physical Sources
3
Pre-built ETL to extract data from over 3,000
operational tables and load it into the DW,
sourced from JDE, PSFT, and other sources.
2 A “best practice” library of over 360 pre-built
metrics, Intelligent Dashboards, 200+ Reports and
alerts for CFO, Finance Controller, Financial
Analyst, AR/AP Managers and
Executive
4
Pre-built warehouse with more than 15 star-
schemas designed for analysis and reporting on
Financial Analytics
1
BI Apps – Financial Analytics Product Layers
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BI Apps – Financial Analytics – JD Edwards Specifics
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JDE Approach
Created new Data Source Num IDs
ETL (Informatica)
Map from JDE E1 tables to the existing staging tables (SDE)
Configuration (.csv) files, domain values
DAC parms (new and existing), DAC execution plan
No OBIA data model changes except:
Added 20 additional attributes to 4 dimensions to support JDE E1 Category Codes
Data Source Name Data Source Number
JDE_8.11 SP1 15
JDE_8.12 15
JDE_9.0 25
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Financial Analytics – Dimensions
Dimension Primary JDE E1 Source Table
W_MCAL_PERIOD_D F0008 – Fiscal Date Patterns
W_MCAL_CAL_D F0008 – Fiscal Date Patterns
W_MCAL_CONTEXT_G F0010 – Company Master
W_INT_ORG_D F0010 – Company Master
F0006 – Business Unit Master
W_LEDGER_D F0010 – Company Master
W_PROFIT_CENTER_D F0010 – Company Master
W_COST_CENTER_D F0006 – Business Unit Master
W_INT_ORG_DH F0050 – Organizational Structure Master
W_GL_ACCOUNT_D F0901 – Account Master
W_HIERARCHY_D F0901 – Account Master
W_GL_SEGMENT_D F0901 – Account Master
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Financial Analytics – Dimensions
Dimension Primary JDE E1 Source Table
W_PARTY_ORG_D
F0101 – Address Book Master
F03012 – Customer Master by Line of Business
F0401 – Supplier Master
W_CUSTOMER_LOC_D F0101 – Address Book Master
W_USER_D F0101 – Address Book Master
W_CUSTOMER_FIN_PROFL_D F03012 – Customer Master by Line of Business
W_CUSTOMER_ACCOUNT_D F03012 – Customer Master by Line of Business
W_SUPPLIER_ACCOUNT_D F0401 – Supplier Master
W_PRODUCT_D F4101 – Item Master
W_EMPLOYEE_D F060116 – Employee Master
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Financial Analytics – Dimensions
Dimension Primary JDE E1 Source Table
W_AP_TERMS_D F0014 – Payment Terms
W_PAYMENT_TERMS_D F0014 – Payment Terms
W_CODE_D F0005 – User Defined Code Values
W_STATUS_D F0005 – User Defined Code Values
W_XACT_TYPE_D F0005 – User Defined Code Values
W_PAYMENT_METHOD_D F0005 – User Defined Code Values
W_EXCH_RATE_GS F0015 – Currency Exchange Rates
W_JDEE1_DECIMALSHIFT_G F9210 – Data Dictionary
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Financial Analytics – Facts
Dimension Primary JDE E1 Source Table
W_AP_XACT_F
F0411 – Accounts Payable Ledger
F0413 – Accounts Payable Matching Document Header
F0414 – Accounts Payable Matching Document Detail
W_AR_XACT_F
F03B11 – Customer Ledger
F03B13 – Receipts Header
F03B14 – Receipts Detail
W_GL_REVN_F F0911 – Account Ledger
W_GL_COGS_F F0911 – Account Ledger
W_GL_OTHER_F F0911 – Account Ledger
W_GL_BALANCE_F F0902 – Account Balances
W_ACCT_BUDGET_F F0902 – Account Balances
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Other JDE E1 Adapter Notes
Rely on Universal Adapter for:
W_BUDGET_D
W_CUSTOMER_COST_LINE_F
W_PRODUCT_COST_LINE_F
JDE E1 Adapter does not support the following:
W_BANK_D
W_TAX_TYPE_D
W_PARTY_PER_D
W_TAX_XACT_F
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Data Model
AP
AR
GL
Custom Tables
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Many JDE E1 Modules Feed Accounts Payable
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JDE E1 Accounts Payable - Process Flow
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Financial Analytics Data Model
Base Fact “Primary” JDE E1 Source Tables
W_AP_XACT_F
F0411 – Accounts Payable Ledger
F0413 – Accounts Payable Matching Document Header
F0414 – Accounts Payable Matching Document Detail
Only mapping transactions that have been posted
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Many JDE E1 Modules Feed Accounts Receivable
Contact and Service Billing
Accounts Receivable
General Accounting
Address Book
Sales Order Management
Service & Warranty Management
Real Estate Management
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JDE E1 Accounts Receivable - Process Flow
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Financial Analytics Data Model
Base Fact “Primary” JDE E1 Source Tables
W_AR_XACT_F
F03B11 – Customer Ledger
F03B13 – Receipts Header
F03B14 – Receipts Detail
Only mapping transactions that have been posted
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Financial Analytics Data Model
Base Fact “Primary” JDE E1 Source Tables
W_GL_REVN_F F0911 – Account Ledger
W_GL_COGS_F F0911 – Account Ledger
W_GL_OTHER_F F0911 – Account Ledger
W_GL_BALANCE_F F0902 – Account Balances
Only mapping transactions that have been posted
Only mapping “actual” ledger types
The Financial Statement Item Code associated with the Account on the GL transaction (F0911) determines if a GL Transaction is mapped to W_GL_REVN_F, W_GL_COGS_F, or W_GL_OTHER_F
Other JDE E1 Adapter Notes:
Don’t support Reconciliation process that exists with EBS Adapter
Don’t support drill back from GL to AP or AR
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Financial Analytics Data Model
Base Fact “Primary” JDE E1 Source Tables
W_ACCT_BUDGET_F F0902 – Account Balances
Only mapping transactions that have been posted
Only mapping “budget” ledger type
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Category Codes
20 new attribute columns were added to the following dimension tables and their associated _DS tables:
W_INT_ORG_D – Attribute columns were added to support Business Unit (F0006) category codes.
W_CUSTOMER_ACCOUNT_D – Attribute columns were added to support Customer Master by Line of Business (F03012) category codes.
W_PARTY_ORG_D – Attribute columns were added to support Address Book Master (F0101) and Customer Master by Line of Business (F03012) category codes.
W_PRODUCT_D – Attribute columns were added to support Item Master (F4101) category codes.
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Additional Tables for Category Codes
Table Column W_INT_ORG_DS STATE_REGION
W_INT_ORG_DS COUNTRY_REGION
W_INT_ORG_DS CONFIG_CAT_CODE
W_PRODUCT_DS INDUSTRY_CODE
W_PRODUCT_DS BRAND
W_PRODUCT_DS COLOR
W_PRODUCT_DS UNIV_PROD_CODE
W_CUSTOMER_ACCOUNT_DS ACCOUNT_TYPE_CODE
W_CUSTOMER_ACCOUNT_DS ACCOUNT_CLASS_CODE
W_PARTY_ORG_DS LINE_OF_BUSINESS
W_PARTY_ORG_DS REGION
W_PARTY_ORG_DS ACCNT_AHA_NUM
W_PARTY_ORG_DS ACCNT_CLASS
W_PARTY_ORG_DS ACCNT_HIN_NUM
W_PARTY_ORG_DS ACCNT_REGION
W_PARTY_ORG_DS ACCNT_VALUE
W_PARTY_ORG_DS CUST_CAT_CODE
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User Defined Codes
The file_udc_category_mapping_jde.csv file loads JDE E1 user defined codes (UDCs) into the Code (W_CODE_D) dimension. Use the flat file to specify a particular set of UDCs that you want to load.
There are three columns in the CSV file. The first two columns are used to identify the system codes and user defined codes. Together, these columns are used to identify the UDCs that will be loaded into W_CODE_D. The third column is the category into which you want to load the codes in W_CODE_D.
Categories in W_CODE_D are used to group together codes intended for a similar purpose. For example, UDC 00||CN stores the country code and description. To store this under the COUNTRY category in W_CODE_D, enter the following row in the CSV file: 00 CN COUNTRY
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User Defined Codes
In the CSV file, you specify the system code and user defined code and associate it with the category to which you want the UDCs loaded. This data is loaded into UDC_CATEGORY_MAP_TMP table, which leverages the data and loads the relevant codes into the Code dimension.
Example…..
System Code User Defined Code Category
00 PY SUPPLIER_PAYMENT_METHOD
00 CN COUNTRY
01 GD GENDER
01 LP LANGUAGE
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Group Account Numbers
Group Account numbers are configured in the same way as EBS through the file file_group_account_codes_jde.csv The file has an additional column of company required for JDE.
COMPANY FROM ACCT TO ACCT GROUP_ACCT_NUM
00000 4100 4190 AP
00000 1200 1299 AR
00000 2120 2195 ACC DEPCN
00000 4200 4211 ACC LIAB
00000 1100 1121 CASH
00000 4900 4910 CMMN STOCK
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GL Hierarchy
The JDE E1 account dimension mapping generates hierarchies for each AID (Account ID) based on the LDA (Level of Detail). This is a relative hierarchy dependant on the order of incoming records.
Check the results with JDE functional consultant & Config guide to confirm. The ETL generates a hierarchy as below:
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Rate Type
The concept of Rate Type in JDE is different than how it is defined in the Warehouse. In JDE, the rate type is an optional key; it is not used during exchange rate calculations.
DAC uses the $$JDE_RATE_TYPE source system parameter to populate the Rate_Type field in the W_EXCH_RATE_GS table. By default, the $$JDE_RATE_TYPE source system parameter in DAC has a value of "Actual."
The query and lookup on W_EXCH_RATE_G will fail if the RATE_TYPE field in the W_EXCH_RATE_G table does not contain the same value as the GLOBAL1_RATE_TYPE, GLOBAL2_RATE_TYPE 2 and GLOBAL3_RATE_TYPE fields in the W_GLOBAL_CURR_G table.
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Integrated Security
Elements of
Security
JDE E1 OBIEE/OBIA Integrated Security
Option
User Security - Validate username/pw - Validate username/pw - Maintain JDE E1 credentials
in LDAP so OBIEE can
leverage it
Object
Security
- Based on User ID and Role
Note: Roles are not based on
“job function” or
“responsibility”
- Based on Security Groups
- Security Groups based on
user’s job function. User’s
job function can be derived
from the roles/resp. in the
OLTP system if the OLTP
roles/resp. are “job-function”
based.
- LDAP schema supported by
JDE E1 could contain Security
Group, so both JDE E1 and
OBIEE object security can be
set up in LDAP
Data Security - Based on User ID and
Role, defined at the
table/row/column level
Note: User ID (Profile) is not
associated with an
“organization”
- Based on Organization/Job
function , applies to all
tables
- Can be derived from the
OLTP system if the OLTP’s
user profile contains the
user’s “organization”
Dual Maintenance Required
- JDE E1 User ID (Profile) is
not associated with an
“organization” yet an
“organization” is required for
Integrated data security
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BISC Implementation
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BISC Implementation
Week 15
Weeks 5-12
Weeks 2-4
Weeks 13-14
Week 1
Install & Populate BI Application
Unit Testing
System Testing
Development
Review Contents
Prioritise Requirements
User Training
UAT Migration
UAT
Deploy to PROD
Post-Live Support (BISC)
Project Plan
Workshops
Questionnaire
Expert Services
(BISC)
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BISC Implementation
BISC Project Team
Business Business Sponsor
Business Analysts
Users
BISC Team
0.5 - BISC Project Manager
0.5 - BI Architect
1 - BI Specialist
1 - BISC Consultant
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BISC Implementation
Installation
Financial Analytics 7.9.6.3 configured for the following build: Microsoft Windows Server 2003 Standard Edition OBIEE 10g OBIA 7.9.6.2 DAC 10.1.3.4.1 Informatica 8.6.1
3.5 days for complete installation and a full ETL run.
Produced an install guide running over 70 pages for installation and
configuration of all software components.
Peak installed on DEV and then the Internal BISC team were able to follow the install guide and install both UAT and PROD with minimum fuss.
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BISC Implementation
Requirements Capture
Every customer is different when it comes to their requirements – leading into an entirely different extension to BI Apps.
A series of demos and workshops and questionnaire driven requirements capture.
Requirements specification document created and signed-off
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BISC Implementation
Configuration
Financial Ledgers – Actual & Commitment ledgers
Mapping Account Segment codes to columns in F0901 account master table
Accounting Aggregates – which account segments to produce aggregates for
Date patterns to support fiscal quarters
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BISC Implementation
Configuration
Set DAC parameters determining volume of historical data in Data Warehouse: Initial Extract Date - date from which to extract data Analysis Start- date from which to extract data Analysis End - date to which data should be extracted
Other DAC parameters
Currencies • $$GLOBAL1_CURR_CODE
Rate Types • $$GLOBAL1_RATE_TYPE
Calendar • $$GBL_CALENDAR_ID • $$GBL_DATASOURCE_NUM_ID
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Customisation
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Customisation
Requirements
Extensions
to Out-of-Box with additional 120+ fields related to...
Non-Pay Subject Area
Ability to report on Non-Pay data in OBI since last three years.
Ability to report on Non-Pay data for different time periods – weekly, monthly, annually.
Ability to replicate current reporting on JDE.
Ability to report more accurately on Non-Pay Transactions.
Ability to report more accurately on changes between any two dates.
Ability to report on Transactions between any two dates.
Ad-hoc reporting of Orders and Suppliers with specific filters.
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Security
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Security
Application Roles
ETL Informatica
JD Edwards Data Warehouse
Staging Star Schemas
Oracle Business Intelligence • BI Presentation Services • BI Server • BI Scheduler
Oracle BI “Application Roles”
Core finance team have high visibility
Cost Centre managers have restricted visibility based on
application role
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ETL Statistics
Full Load • 10 Hours (DEV) • 6 Hours (UAT & PROD)
Incremental • 5.5 Hours (DEV) • 3.5 Hours (UAT & PROD)
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Training
Client specific Training Manual Delivered training on Reports and Dashboard A further BI Apps Bootcamp training is planned Parallel Support period ensures additional detailed Knowledge Transfer
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Key Success Factors - General
Proven BI Apps implementation experience Peak Indicators has a combined total of over 20 years in-depth experience
implementing various modules of BI Apps Utilising Peak’s “Quick-Start” approach
Extended OOTB subject areas utilising 90% of OOTB contents rather than
building new subject areas from scratch. Controlled Project scope within the “Quick Start” approach System and UAT testing Strong BI Project Management Executive level sponsorship
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Key Success Factors - BISC
Use of the Peak Indicators BISC Approach.
What is BISC? BISC is the “New Improved Generation” of BICC or BICoE! Forrester and the BISC:
“Forrester firmly believes that tried and true best practices for enterprise software development and support just don’t work for business intelligence (BI). Earlier-generation BI support centers — organized along the same lines as support centers for all other enterprise software — fall short when it comes to taking BI’s peculiarities into account. These unique BI requirements include less reliance on the traditional software development life cycle (SDLC) and project planning and more emphasis on reacting to the constant change of business requirements. Forrester recommends structuring your BISC along somewhat different lines than traditional technical support organizations. “ ... “A permanent, cross-functional, virtual or physical organizational structure, loosely coupled for flexibility and agility, responsible for the governance and processes necessary to deliver or facilitate the delivery of successful BI solutions, as well as being an institutional steward of, protector of, and forum for BI best practices.” REF: http://blogs.forrester.com/category/bisc
Parallel Support and Knowledge Integration to internal BISC Detailed Requirements Definition completed by internal BISC Conformity to Internal Governance and development standards by internal BISC
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Next Steps
Current implementation – Non-Pay Transactions (20 Named Users)
On Site Support in Internal BISC Remote Advanced Support in BISC
Future Phases – Wider Rollout (20+ Users) Roll out additional dashboards and reports (20+ Named Users)
Training – BI Apps Bootcamp - http://www.peakindicators.com/index.php/obiee-training
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Questions?
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Helping Your Business Intelligence Journey