During this session, we will explore a variety of different techniques that can be utilized to decrease the time between data entry and data analysis and reporting. We will use real-world examples and use cases to demonstrate different methods that will minimize time between input and analysis. We will review best practices for utilizing data maps in conjunction with forms, simple groovy scripting while using pre-built functionality within PBCS. Attendees will walk away with a better understanding and a new way of thinking about data movement between PBCS cubes. Hosted by Sara Beth Good at the OATUG Forum Collaborate 2020

2. Session ID:
Prepared by:
Remember to complete your evaluation for this session within the app!
11717
Utilizing Groovy and Data Maps
for Instantaneous Analysis
between ASO and BSO cubes
April 29, 2020
Sara Beth Good
Lead Consultant
Alithya

3. 3
Agenda
Introductions
Historical Data
Movement
Architecture
Future Data
Movement
Architecture
Q&A

4. Introductions

5. Who Am I
Sara Beth Good
• Lead Consultant at Alithya
• Live in Houston Texas
• EPM Consultant for 8 years
• Hobbies include reading, boxing, traveling
• Random Fact: In college I had an internship that
required me to be the mascot for the Houston Dynamo
(MLS Soccer Team)
5

6. > Alithya offers EPM, ERP, & Analytics
solutions
> Proven business analytics leader
with a history of successful
implementations & growth
> 20+ years of implementations
6
Advisory
Services
Implementation
Services
Technical
Services
Hosting &
Support
Training
Services
Intellectual
Property
>1,000+ clients
>4,000+ projects
>150+ Cloud implementations
>7 Oracle ACEs
>Certified Cloud resources

7. Historical Data
Movement
Architecture

8. Tired of Waiting?
8
Sound
Familiar
??!!

9. Tired of Waiting?
9
There is a better way! Today we are
going to discuss alternative options that
allow INSTANTANEOUS data analysis
Scheduled
Data Pushes
Reporting and
Analysis
(ASO Cube)
Data Input
(BSO Cube)

10. What’s the difference between ASO and BSO?
ASO- Aggregate Storage Option
Aggregate storage is the Essbase database storage model that supports large-scale,
sparsely distributed data that is categorized into many, potentially large dimensions.
Selected data values are aggregated and stored.
ASO cubes are also called reporting cubes and are great for quickly aggregating
data
BSO- Block Storage Option
Block storage is the Essbase database storage model that categorizes dimensions as
sparse or dense and stores data in blocks. Block storage is designed for applications that
perform interactive planning, allocations, and sophisticated analytics
BSO Cubes are great at calculating complex logic
10

11. What’s the difference between ASO and BSO?
ASO cubes are also called reporting cubes and are great for quickly
aggregating data
BSO Cubes are great at calculating complex logic
Tip: Let the BSO cubes do what BSO cubes do BEST and
let ASO cubes do what ASO Cubes do BEST!
11

12. Traditional Data Movement Diagram
12
Users
Input data
to BSO
Cube
Rules
are run
in BSO
Cube
Data gets pushed to ASO
cube at scheduled intervals
Reporting
and
Analysis
can begin

13. Same Architecture + New Tool Set = New Mind Set!
13
Groovy
Data Maps
The Cloud provides
access to new tools!
New Data Movement
Strategy
Smart Push

14. New Mind Set!
14
New Data Movement Strategy
• Scheduled Mass Data Movements
• Tiny data movements every time data is input and rules are run
VS

15. New Data Movement Strategy
15
Users Input data to BSO Cube using forms
On Save rules/logic is kicked off
Data gets
pushed to
ASO cube
instantly
Reporting and
Analysis can begin

16. Future Data
Movement
Architecture

17. Data Maps
• Data Maps are mapping tables used to move data from one cube to another.
17

18. What do I need to Know about Data Maps?
18
• Data maps are multi-talented, they support the movement of the
following:
• Comments
• Attachments
• Supporting Detail
• Data
• Data Maps can be used to map
• Smartlists
• Dimensions

19. How to Launch Data Maps?
• Manually
• Forms
• Groovy Rules
• Scheduler
19

20. Data Map Pro Tips
Utilize the Functions when setting up mappings ie: Ancestors,
Children, Level 0 Descendants
Create as few data maps as possible and then use them for multiple
purposes
Synchronize Data Maps as part of regular Metadata update process
Data maps used in conjunction with smartlists can minimize the
dimensionality required within a cube
20

21. Smart Push and Groovy
21
Groovy
Data Maps
Smart Push

22. Data Maps + Forms = Smart Push
When Data Maps are launched from forms it is called Smart Push
Smart Push allows incremental updates to be made to the reporting cube
instantaneously
22
• Setting up Smart Push
– Data Map Creation
– Create and Manage
Forms
– Smart Push Options

23. Smart Push Helpful Information
Smart Push Order of Operations
1. Data Input and Form is saved
2. Rules launched
3. Smart Push
More than 1 data map can be associated with a single form
Smart Push Honors security considerations
23

24. 24
Groovy is a scripting language used for Java
that is supported by Calculation Manager.
Next, we are going to take a look at
how to utilize Groovy in conjunction
with Data Maps and Smart Pushes to
facilitate INSTANTANEOUS reporting.
Groovy!
What’s Groovy?

25. – Groovy Scripts can be run from:
• Calculation Manager
• Rules
• Scheduler
• Forms
• EPM Automate
25
Using Groovy to Launch Data Maps- Basics

26. Using Groovy to Launch Data Maps- Basics
• Getting Started
– Create new rule in Calculation Manager and select Groovy Script for Script
Type
26
Groovy Code to Launch Data Map
operation.application.getDataMap(“Data Map Name").execute(true)
Groovy Code to Launch Smart Push
operation.application.getDataMap("Data Map Name").createSmartPush().execute()

27. Using Groovy to Launch Data Maps-
Getting Fancy
27
Call Data
Map/Smart
Push with
specific
periods
identified
Launch Data Maps/Smart Push for a range of time periods

28. Using Groovy to Launch Data Maps-
Getting Fancy
28
Identify Run-
Time-Prompts
Defining and
Storing Run-
Time-Prompts
as a string
Call Data
Map/Smart
Push
Launch Data Maps based on Run Time Prompts

29. Using Groovy to Launch Data Maps-
Getting Fancy
Use Cases for using Groovy Script to launch Data
Maps and Smart Pushes
– Launch Data Maps/Smart Push based on edited data
– Launch Data Maps/Smart Push for dynamic time periods
– Utilize Data Maps within the context of business rule
logic ie: Allocations
– Data Archiving Processes
– Moving data amongst business processes within an
application ie: Workforce to Financials
29

30. In Summary…
30
VS

31. References
31
Oracle’s EPM Groovy Reference:
https://docs.oracle.com/en/cloud/saas/enterprise-performance-management-
common/groov/index.html
Oracle EPM Documentation:
https://docs.oracle.com/en/cloud/saas/enterprise-performance-management-
common/cgsad/index.html

32. Q&A

33. Session ID:
Please remember to complete the session evaluation that you
will receive via email from the webinar service provider.
11717
sarabeth.good@alithya.com