4. Oracle Warehouse
Comprehensive & Integrated
Analytic Applications
Reports
Operational
Data
Oracle8i
Warehouse Application Discoverer
ERP Builder Server
Data
Darwin
Express
Oracle8i Express
External
Data
CWM and Repository
Designer and Enterprise Manager
5. Family of OLAP Products
Sales Financial
Third Party
Analyzer Analyzer
Oracle Oracle Express Express Express Web
Discoverer Reports Objects Analyzer Publisher
Express
Oracle Express Server
Web Agent
Relational Express
Access Manager Administrator
Legacy &
Relational Database Management System
External
8. Solutions Architecture
Balanced Scorecard
O F A; O S A
Strategy Value Activity
Formulation Based
& Based
Simulation Management Management
ERP/CRM Intel.
Oracle Warehouse
3rd Pty Legacy Oracle Apps
9. What is Oracle Financial Analyzer
Financial Analyzer is a distributed application for
financial reporting, analysis, budgeting, and
planning. By integrating a central source of
management data with powerful analytical tools,
the system enables organizations to meet their
critical financial objectives :
control costs, analyze performance, evaluate
opportunities, and formulate future direction.
10. Basic Overview
Spreadsheets
Two dimensional - row / column
combination holds information.
Good for basic
accounting and
Columns
analysis.
Rows
11. Basic Overview
Relational Tables
Two dimensional - row / column
combination from several tables
holds information
1,000,000 units
12. Basic Overview
Relational Tables (continued)
Oracle General Ledger is based on a
relational model.
Ideal for:
Transaction processing
Known reporting
requirements
“Simple” ad hoc
queries
13. OFA Overview
Multi-Dimensional Data Models
On-Line Analytical Processing
(OLAP) systems are based on multi-
dimensional
data models.
Page
Columns
Rows
14. OFA Overview
Multi-Dimensional Data Models
(cont.)
Oracle Financial Analyzer is based
on a multi-dimensional model.
Ideal for:
Dynamic on-line analysis
Complex ad-hoc queries
Financial modeling
15. Report and Analysis
Changing Paradigm
Model or Reporting Entity
Cost Centre Account Month
Record #1 CC1 A101 Jan 96 800
Rccord #2
Account
CC2 A105 Mar 96 250
or
Record #3 CC2 A115 Mar 96 900 Activity
Record #4 CC1 A167 Feb 96 400 or
Record #5 CC3
CC5
A100 Jan 96 700 Cost Obj Actual
Record #6 A105 Mar 96 600
Record #7 CC3 A189 Mar 96 650
Record #8 CC5 A167 Feb 96 850
PDS: Month
KEYS Budget, Actual
Relational View Multidimensional View
16. Multi Dimentional Analysis
Fast Flexible Access to Summarised Data
hy
ap
gr
eo
G
Product
Regional Manager View Product Manager View
Month
Financial Manager View Analyst View
17. Meets the Needs of the CFO
CFO
Controller Finance
- Accounts Payable - Budgets
- Accounts Receivable - Plans
- Fixed Assets - Forecasts
- Standard Financial Reports - What-If analysis
- Consolidations Oracle - Reporting
- Journal Entries Financial - Modeling
Analyzer
..... Day to Day Transactions
Oracle Other
Financials Data
18. Who Uses OFA?
Financial Analyst
Drive forecast and budgeting
process
Generate financial management
reports
Create models for profit
and loss analysis
Generate and maintain
cash flow statistics
19. Who Uses OFA?
Business Unit Manager
Effectively distribute information
throughout the organization
Low cost, web-based access
Manage divisional or product
performance
Plan vs. Actual variances
Business trends
Business unit forecasts
20. Who Uses OFA?
Chief Financial Officer
Examine risks and opportunities
Performance measurement
Planning for the future
What-If analysis
New opportunities
21. What is the GL/OFA Link?
The automated flow of
information enables users to
take advantage of the best of
both worlds.
22. What is the GL/OFA Link?
General Ledger Perspective
Data is recorded against a
chart of accounts structure.
Company
Department
General Ledger
Segments Account
Product
23. What is the GL/OFA Link?
Financial Analyzer Perspective
Data is associated with
dimensions and cubes.
Organization
Financial Analyzer
Line
Dimensions
Product
24. What is the GL/OFA Link?
TheLink integrates the
segment concept with the
dimension concept.
Company
Organization
Department
Line
Account
Product
Product
General Ledger Financial Analyzer
Segments Dimensions
25. What is the GL/OFA Link?
Organization
Page
Line Columns
Product Rows
Time (GL)
Financial Analyzer OFA Cube
Dimensions (Balances)
26. What is the GL/OFA Link?
The automated flow of
information enables users to
take advantage of the best of
both worlds.
27. What is the GL/OFA Link?
Cost Centre Account Month
Organisation
Record #1 CC1 A101 Jan 96 800
Rccord #2 CC2 A105 Mar 96 250 Account
Record #3 CC2 A115 Mar 96 900
Record #4 CC1 A167 Feb 96 400
Record #5 CC3 A100 Jan 96 700
Record #6
Record #7
CC5
CC3
A105
A189
Mar 96
Mar 96
600
650
Actual
Record #8 CC5 A167 Feb 96 850
KEYS Month
Segments Dimensions
Segment Values Dimension Values
Rollups Hierarchies
Balances Data Items
28. What is the GL/OFA Link?
Cost Centre Account Month
Organisation
Record #1 CC1 A101 Jan 96 800
Rccord #2 CC2 A105 Mar 96 250 Account
Record #3 CC2 A115 Mar 96 900
Record #4 CC1 A167 Feb 96 400
Record #5 CC3 A100 Jan 96 700
Record #6
Record #7
CC5
CC3
A105
A189
Mar 96
Mar 96
600
650
Actual
Record #8 CC5 A167 Feb 96 850
KEYS Month
Budgets Scenario
Budget
Forecast
29. What is the GL/OFA Link?
Communicate with Oracle General Ledger
30. What are Benefits of the Link?
Manage Your Business Globally
Web deploy key information
throughout the organization
Make Better Decisions
Empower broad group of users
to leverage OLAP analysis
Develop better budgets with OFA
Automatically transfer budgets back
to GL
31. What are Benefits of the Link?
Lower Administrative Costs
Single point of entry for data
Consistent and reliable data for
analysis
Reduces maintenance
Share structures and data
Transfer any balance from GL to OFA
Reduces reconciliation issues
Automated data flow
37. Oracle Sales Analyzer is...
an enterprise wide on-line analytical
processing application designed for
managers and analysts to better utilize
their corporate data and data warehouses
38. User Target Audience
Marketing Managers Market Research Analysts
Product Managers Marketing Analysts
Market Planning Managers Sales Analysts
Merchandise Mgt. National Account Managers
Promotion Planners Field Sales
39. Common Application Areas
Competitive Analysis
l What are the driving factors for increasing my share?
l Where is my competition gaining?
Market Analysis / Segmentation
l How are our Key Accounts performing vs last year?
l Which products aren’t being ordered by our Key
Accounts?
Product Mix
What are my top 5 products in the US?
What’s the market/cost for new products?
Will our new product cannibalize existing ones?
Promotional Effectiveness
l Can we correlate sales to promotions?
l Was the promotion profitable ?
40. Sales Analyzer User Benefits
Ad-Hoc Reporting/Graphs
l Drill-down & Data Rotation
l Dynamic Ranking & Exceptions
Powerful Data Query
l By Level, Attribute & Hierarchy
l Top/Bottom and Exception based on Data
Database Analytics
l User-Defined Aggregates
l New Measure Creation
l Forecasting
l Pre-built analysis libraries
41. Custom Measures
Common Sales & Marketing
calculated measures
Arithmetic (+, -, /, x)
Variance
% Change vs Last Year / Prior Period
% Share
Moving Average / Maximum / Minimum /
Total
. . . using simple templates
42. Sales Analyzer IS Benefits
Built-in Bridge to Data Mart / Data
Warehouse
l (using Express Relational Access Manager)
l Periodic maintenance minimized
Manages user objects
l DBA not necessary to create reports & graphs
Built-in distribution routines
l Standard objects can be centrally distributed
l User to user distribution
Data security
l Users can only see what they have access to.
43. Oracle Sales Analyzer
Modes of Operation
‘Client / Server & Web’ PC
Sales Analyzer Sales Analyzer
PC Express
Client
Sales Analyzer
Express
Server
46. Data Warehouse Integration
Data Mart / Warehouse
Calculation
Sales
Engine Analyzer
Data & Metadata
Sales
Relational Analyzer
Access Web
Manager
Sales
Analyzer
RDBMS Express Server Mobile
47. OSA As A Data Mart
The data loader is a set of Express
programs that uses flat files to
build a multidimensional database
for use in Oracle Sales Analyzer.
Flat Files
Data Loader
48. Sample OSA Application Data
Model
Dimensions, Levels, Hierarchies, and Attributes
•Product •Time •Geography •Channel
Standard Standard Shipping Market Segment Standard
Total Products Year (Date, Total Geographies Total Segments Total Channels
Timespan)
Class Region Segment Channel
Quarter (Date,
Family Timespan) Warehouse Account
Month (Date,
Item (Package) Ship-To Ship-To
Timespan)
Variables
•Sales (Geography, Product, Channel, Time) •Price (Product, Time)
•Units (Geography, Product, Channel, Time) •Cost (Product, Time)
50. Oracle Sales Analyzer
Distributed Architecture
Thick Client Thin Client Web Client
Sales Analyzer Sales Analyzer Browser
Express
PC Client XCA SNAPI Web Agent
Sales Analyzer
Server Express
51.
52. Sales Analyzer: Web Access
Accessthrough a Web
browser
l Zero footprint. No other software
needed on workstation!
User security
l ID authenticated upon connection
l Scoping on data and documents
Dynamic generation of
displays (it’s live!).
53. Sales Analyzer: Web
Functionality
Create/save/delete reports and graphs
Forecast Wizard
Maintain Folders
Custom Aggregates
Custom Measures
Explorer ‘Tree’ display for Folders /
Documents
Publish Documents (maintain libraries)
Web Analysis Library
Selector Tools (Level, Family, Attribute,
Exception, Top/Bottom)
55. Analysis Library for the Web -
What is it ?
Fast Answers to Sales & Marketing
Questions
19 pre-defined Sales and Marketing
oriented documents, plus two review
documents, e.g.
Growth
Trend (e.g. Cumulative Sales Trend)
Ranking
Distribution (e.g. products / customers with
increasing / decreasing sales)
80/20 Analysis (e.g. 20% of products / customers
making up 80% of the business)
56.
57.
58. Analysis Library for the Web -
How do you configure it ?
Analyzer Web Administrator
page
Enable Analysis Library
documents for a specific
Database, by launching . . .
Analysis
Library
Administration page
Select documents to generate
by document / dimension, plus
specify certain default selection
information
61. Sales Analyzer Forecasting
Wizard Based
Generates Forecast Document
Generates Forecast Measure
Both Document and Measure can
be published
Fully Integrated With OSA
Works with Slice, Client / Server, RAM
Forecast Document / Measure can be
created and viewed via the Web
Intended as a personal analysis
tool, not as an enterprise wide
forecasting system
68. OSA 6.3
100% Java Printing; no longer
relying on the browser
Panelling of logical pages to
physical pages
One or all pages
Print preview
Headers, footers
Page layout, ie portrait/landscape,
margins
number of copies
69. OSA 6.3
ImprovedExport to Excel
(windows client)
Export multi-page report to multiple
worksheets
Automatically create a table of contents,
with a link to each worksheet
Automatically start up excel upon export
Performance improvements,
especially for RAM
implementations
70. Oracle Sales Analyzer - TODAY
Wide range of implementation options
...
Scalable MOLAP databases using OSA
Data Loaders and Express Server
ROLAP / HOLAP access to DW / Data
Mart via Relational Access Manager
Distributed client / server using either
‘thick’ or ‘thin’ client
Disconnected distributed access via
slices
Very light distributed access over
intranet / internet via Web Browser.
The benefits of Sales Analyzer from a users’ perspective are many. Sales Analyzer provides the user with the ability to analyze their information in a completely ad-hoc way. We provide data rotation and drill-down mechanism. In addition to that, knowing that a lot of marketing and sales analysis is exception based, Sales Analyzer provides a special report type just for Exceptions and rankings. Sales Analyzer also provides the user with very powerful data query and analysis functions. A user can query and drill into the data by levels of product (i.e., I want to see my product families), by attributes (I want to see only my customers in the Manufacturing industry), or by hierarchy (show me my Geographical rollups as opposed to my sales rollups). Additionally, the user can sub-set their selections based on the data (give me all my customers who have lost market share from last year). The users are also empowered to create their own views and ways to analyze the data. IS can never (at least as far as I know) predict all of the ways users will want to aggregate or view their data. Sales Analyzer provides a way for the user to create their own groupings. I want to group all the stores that I am promoting product x, y, and z and analyze those stores as one. The other tool the user has access to is one which allows them to create their own measures based on the data and dimensions which are in the database. A user can create a % Chg from Yr Ago measure or a moving average or total. Tons of power to the users (which can be cut back if desired).
7 11 In addition to being integrated with one another, Oracle's BI tools are also integrated parts of Oracle's total data warehouse solution. We're focusing today on the front end BI capabilities, but the Oracle Warehouse also includes tools for defining and building a warehouse or data mart, mapping to various data sources, loading data into the warehouse, and managing metadata at each level. Oracle 8i obviously provides a powerful platform for data warehousing--and I'll talk a bit more about how our BI tools leverage the features of 8i--but the Oracle Warehouse approach also supports other data structures such as Express multidimensional OLAP cubes and data in Oracle's Darwin data mining engine. In addition to providing the various components for customers to assemble their own solutions, Oracle offers a number of analytic applications that package various pieces of this solution.
OFA supports a full range of financial mangement applications. Organisations / Finance can address their current top issue - may be the annual budgeting process, and then move on to address strategic opportunities like Profit Management & ABC. The key is its the same single system, same skills. Integrated strategic financial management not ad hoc, haphazard, individual project based financial mangement. Investment in the future. So what’s different about OFA?
Actual financial data is the starting point for the financial management process. To ensure integrity, Oracle Financial Analyzer can load data from external sources, typically a general ledger. Translating the data stored in the general ledger from a relational view to a multidimensional view is an important step in providing data optimized for query and analysis. Where an Oracle general Ledger is the source, the Oracle GL DBA has specific functionality in the GL to mapp the data struactures. The mapping is achieved by filling in simple tables as part of the a pre-defined link capability. An example would be that Segments, Company / Cost Centre could be mapped onto one dimension - Organisation. The hierarchies defined over the two GL segments would be intelligently combined to generate an Organisation hierarchy in OFA. This mapping at source ensures accurate data transfer and the basis for sound decision making.
Finalised budget or plan data can be passed back to Oracle Financials or any other ledger.
What? Sales Analyzer is an enterprise wide on-line analytical processing application designed for managers and analysts to better utilize either corporate data and data warehouse. It is used in industries as varied as pharmaceutical to manufacturing to oil & gas to telecommunications I think we can all agree that to be successful today, we can no longer rely on paper reports and/or simple query tools. We have to be able to make decisions based on knowledge as opposed to Information or intuition. We need the power of an on-line analytical processing system for the entire enterprise.
WHO? Within these companies, who are the users? Well, as you can see, the users are generally marketing or sales based analysts. People like product managers, marketing analysts and researchers and sales analysts. As I said earlier, Sales Analyzer is used by a broad base of marketing and sales analysts and professionals.
The benefits of Sales Analyzer from a users’ perspective are many. Sales Analyzer provides the user with the ability to analyze their information in a completely ad-hoc way. We provide data rotation and drill-down mechanism. In addition to that, knowing that a lot of marketing and sales analysis is exception based, Sales Analyzer provides a special report type just for Exceptions and rankings. Sales Analyzer also provides the user with very powerful data query and analysis functions. A user can query and drill into the data by levels of product (i.e., I want to see my product families), by attributes (I want to see only my customers in the Manufacturing industry), or by hierarchy (show me my Geographical rollups as opposed to my sales rollups). Additionally, the user can sub-set their selections based on the data (give me all my customers who have lost market share from last year). The users are also empowered to create their own views and ways to analyze the data. IS can never (at least as far as I know) predict all of the ways users will want to aggregate or view their data. Sales Analyzer provides a way for the user to create their own groupings. I want to group all the stores that I am promoting product x, y, and z and analyze those stores as one. The other tool the user has access to is one which allows them to create their own measures based on the data and dimensions which are in the database. A user can create a % Chg from Yr Ago measure or a moving average or total. Tons of power to the users (which can be cut back if desired).
The benefits of Sales Analyzer from a users’ perspective are many. Sales Analyzer provides the user with the ability to analyze their information in a completely ad-hoc way. We provide data rotation and drill-down mechanism. In addition to that, knowing that a lot of marketing and sales analysis is exception based, Sales Analyzer provides a special report type just for Exceptions and rankings. Sales Analyzer also provides the user with very powerful data query and analysis functions. A user can query and drill into the data by levels of product (i.e., I want to see my product families), by attributes (I want to see only my customers in the Manufacturing industry), or by hierarchy (show me my Geographical rollups as opposed to my sales rollups). Additionally, the user can sub-set their selections based on the data (give me all my customers who have lost market share from last year). The users are also empowered to create their own views and ways to analyze the data. IS can never (at least as far as I know) predict all of the ways users will want to aggregate or view their data. Sales Analyzer provides a way for the user to create their own groupings. I want to group all the stores that I am promoting product x, y, and z and analyze those stores as one. The other tool the user has access to is one which allows them to create their own measures based on the data and dimensions which are in the database. A user can create a % Chg from Yr Ago measure or a moving average or total. Tons of power to the users (which can be cut back if desired).
The benefits of Sales Analyzer from a users’ perspective are many. Sales Analyzer provides the user with the ability to analyze their information in a completely ad-hoc way. We provide data rotation and drill-down mechanism. In addition to that, knowing that a lot of marketing and sales analysis is exception based, Sales Analyzer provides a special report type just for Exceptions and rankings. Sales Analyzer also provides the user with very powerful data query and analysis functions. A user can query and drill into the data by levels of product (i.e., I want to see my product families), by attributes (I want to see only my customers in the Manufacturing industry), or by hierarchy (show me my Geographical rollups as opposed to my sales rollups). Additionally, the user can sub-set their selections based on the data (give me all my customers who have lost market share from last year). The users are also empowered to create their own views and ways to analyze the data. IS can never (at least as far as I know) predict all of the ways users will want to aggregate or view their data. Sales Analyzer provides a way for the user to create their own groupings. I want to group all the stores that I am promoting product x, y, and z and analyze those stores as one. The other tool the user has access to is one which allows them to create their own measures based on the data and dimensions which are in the database. A user can create a % Chg from Yr Ago measure or a moving average or total. Tons of power to the users (which can be cut back if desired).
If you thought the users have it easy, let me describe to you some of the benefits from the IS standpoint. Firstly, Sales Analyzer is an application developed and supported by Oracle. This gets you the support, documentation, maintenance, and the thousands for highly trained consultants we have in the field. Secondly, an option with Sales Analyzer is what is called the SQL Bridge. The SQL bridge is a built-in link between Oracle (or any RDBMS) and Sales Analyzer which allows users to access (t run-time when they request it), Oracle data. No more specific IS requests for reports for each user. Thirdly, the user is empowered to create their own “objects” to do their analytics. This means that they can create their own reports, graphs, measures and custom aggregations of the data. Not only can the users create their own objects, but they can distribute them to other users and the DBA as well for more enterprise wide use. The DBA can additionally create “standard” objects which everyone has access to. Security is also a feature of Sales Analyzer. The DBA can (but is not required) to set up users’ and determine what data/information each user or group of users can access. Now, why do we view an OLAP application such as Sales Analyzer is necessary in todays market?
The benefits of Sales Analyzer from a users’ perspective are many. Sales Analyzer provides the user with the ability to analyze their information in a completely ad-hoc way. We provide data rotation and drill-down mechanism. In addition to that, knowing that a lot of marketing and sales analysis is exception based, Sales Analyzer provides a special report type just for Exceptions and rankings. Sales Analyzer also provides the user with very powerful data query and analysis functions. A user can query and drill into the data by levels of product (i.e., I want to see my product families), by attributes (I want to see only my customers in the Manufacturing industry), or by hierarchy (show me my Geographical rollups as opposed to my sales rollups). Additionally, the user can sub-set their selections based on the data (give me all my customers who have lost market share from last year). The users are also empowered to create their own views and ways to analyze the data. IS can never (at least as far as I know) predict all of the ways users will want to aggregate or view their data. Sales Analyzer provides a way for the user to create their own groupings. I want to group all the stores that I am promoting product x, y, and z and analyze those stores as one. The other tool the user has access to is one which allows them to create their own measures based on the data and dimensions which are in the database. A user can create a % Chg from Yr Ago measure or a moving average or total. Tons of power to the users (which can be cut back if desired).
18 21 39 That is why Oracle has acquired and integrated the Express technology with its industry leading warehouse and data mart technology. Express is the calculation engine and multidimensional caache for analysis.
Understanding the Sample OSA Applicition Data Model In the pictured example, there are four dimensions. Note that the lowest levels in both of the Geography hierarchies is Ship-To. The Product, Channel, and Time dimensions each have one hierarchy, the Standard hierarchy. The Geography dimension has two dimensions, the Market Segment hierarchy and the Shipping hierarchy. Each hierarchy is composed of two or more levels. The Product and Time dimensions have attributes associated with one or more levels. In the Product dimension, the Package attribute is applied to the Item level. In the Time dimension, the Date and Timespan attributes are applied to the Year, Quarter, and Month levels. There are four variables in this example. The Sales and Units variables are dimensioned by all four dimensions, while the Price and Cost variables are dimensioned only by Product and Time.