AgileAnalytics: Agile Real-Time BI with Oracle Business Intelligence, Oracle Data Integrator and Oracle GoldenGate

www.redpillanalytics.com info@redpillanalytics.com @RedPillA © 2014 RED PILL Analytics
AgileAnalytics: Real-Time BI with
Oracle Business Intelligence, Oracle
Data Integrator and Oracle GoldenGate
2
Stewart Bryson
medium.com/@stewartbryson @stewartbryson linkedin.com/in/stewartbryson

About Red Pill Analytics
Capacity Analytics
Agile Cloud Development for Oracle BI & Analytics
!
Checkmate
DevOps for Oracle BI (Cloud-hosted or On-premises)
!
Single Doses
Training + Strategy + Solutioning + Infrastructure + Support
3

Real Time BI with Kevin & Stewart
•19 episodes over the last 2
years
•Featured guests from the
Oracle BI & EPM industry
•Published on iTunes and
YouTube
•Join us at the Thursday
Deep-Dive session from
9-11am for a LIVE show that
will be simultaneously
broadcast online!
4

AgileAnalytics 1.0: Focus on Performance
5

AgileAnalytics 1.0: Focus on Performance
6
Exadata:
Extreme Performance
OBIEE:
Extreme Metadata
Agile:
Extreme Methodology

AgileAnalytics 2.0: Focus on Integration
7
GoldenGate:
Extreme Realtime
ODI:
Extreme Transformation

Oracle Information Management Reference Architecture
11

1212
Virtualization& 
QueryFederation
Enterprise
Performance
Management
Pre-built &  
Ad-hoc  
BI Assets
Information 
Services
Data Ingestion
Information Interpretation
Access & Performance Layer
Foundation Data Layer
Raw Data Reservoir
Data  
Science
Data Engines &  
Poly-structured  
sources
Content
Docs Web & Social Media
SMS
Structured
Data 
Sources
•Operational Data
•COTS Data
•Master & Ref. Data
•Streaming & BAM
Immutable raw data reservoir
Raw data at rest is not interpreted
Immutable modeled data. Business
Process Neutral form. Abstracted from
business process changes
Past, current and future interpretation of
enterprise data. Structured to support agile
access & navigation
Discovery Lab Sandboxes Rapid Development Sandboxes
Project based data stores to
support specific discovery
objectives
Project based data stored to
facilitate rapid content /
presentation delivery
Data Sources

13
Abstracts rate of
reception from rate of
distribution
Facilitates “right-time”
flow of data

14
Abstracts atomic data
from the business process.
Process-neutral;
Business logic agnostic

15
Process-specific
Imbued with business logic

SugarCRM (Our Sample Dataset)
16

Typical Waterfall Approach
•Interview users
•Construct requirements
•Create logical data model
•SQL prototyping of source
model
•Document source-to-target
mapping
•ETL development
•Front-end development
•Performance tuning
18

Alternative: Iterative Waterfall?
•Design iterations around smaller chunks
• Iteration 1: Interviews and user requirements
• Iteration 2: Logical modeling
• Iteration 3: ETL Development
• Iteration 4: Front-end development
•Requires 4 iterations before we get any
usable content
19

Manifesto for Agile Software Development
“We are uncovering
better ways of
developing software by
doing it and helping
others do it.
!
That is, while there is
value in the items on the
right, we value the items
on the left more.”
http://agilemanifesto.org/
22

Manifesto Applied to AgileAnalytics
•User Stories instead of
requirements documents
• User asks for content or
functionality through a
narrative
• Typically includes current
version of the report
•Time-boxed iterations
• Iteration has a standard length
• Choose one or more user
stories to fit in that iteration
•Rework is part of the game
• There are no “missed
requirements”... only those that
haven’t been delivered yet.
23

Rapid Development Sandbox
27
Oracle
GoldenGate can
bypass the
Staging layer to
trickle-feed the
Foundation layer
Staging layers exist
to support batch
load scenarios

28
We use our
Foundation layer
combined with any
Access & Performance
layer content to close
stories immediately

29
Developers can use
independent
development
sandboxes to work on
their issues in isolation

Are development sandboxes radical?

RPD Development requires a BI
Server
!
RPD Development requires a query
tool
!
RPD Development requires data
visualization

Oracle GoldenGate Architecture
32

Loading Foundation: Standard ETL Approach
33
Source System
Staging Layer
Foundation Layer

Loading Foundation: AgileAnalytics Approach
34
Source System
Staging Layer
Foundation Layer

GoldenGate for AgileAnalytics: Loading the Foundation Layer
35
map SUGARCRM.ACCOUNTS,
target SUGARFND.ACCOUNTS,
KEYCOLS(ID, FND_SCN),
INSERTALLRECORDS,
colmap(
USEDEFAULTS,
FND_SCN=@GETENV("TRANSACTION" , "CSN"),
FND_ROW_RANK=@TOKEN("TK_ROW_RANK"),
FND_COMMIT_DATE=@GETENV("GGHEADER" , "COMMITTIMESTAMP"),
FND_DML_TYPE=@GETENV("GGHEADER" , "OPTYPE")
);
Map SOURCE and
TARGET
KEYCOLS defines
matching criteria
USEDEFAULTS defines
column for column mapping Built-in attributes from the
“token” and the “header”

GoldenGate for AgileAnalytics: Loading the Foundation Layer
36
map SUGARCRM.ACCOUNTS,
target SUGARFND.ACCOUNTS,
KEYCOLS(ID, FND_SCN),
INSERTALLRECORDS,
colmap(
USEDEFAULTS,
FND_SCN=@GETENV("TRANSACTION" , "CSN"),
FND_ROW_RANK=@TOKEN("TK_ROW_RANK"),
FND_COMMIT_DATE=@GETENV("GGHEADER" , "COMMITTIMESTAMP"),
FND_DML_TYPE=@GETENV("GGHEADER" , "OPTYPE")
);
Map SOURCE and
TARGET
KEYCOLS defines
matching criteria
USEDEFAULTS defines
column for column mapping Built-in attributes from the
“token” and the “header”
INSERTALLRECORDS makes
this our Foundation Layer

GoldenGate INSERTALLRECORDS
37
NAME TICKER_SYMBO
L
OWNERSHIP FND_SCN FND_COMMIT_DATE FND_DML_TYP
ERed Pill Analytics 2992758 08/20/2012 12:00 AM INSERT
NAME TICKER_SYMBOL OWNERSHIP
Red Pill Analytics

38
NAME TICKER_SYMBO
L
Red Pill Analytics, LLC Private 2992760 03/13/2013 12:00 AM UPDATE
Red Pill Analytics, LLC Private

39
NAME TICKER_SYMBO
L
Red Pill Analytics, LLC Private 2992760 03/13/2013 12:00 AM UPDATE
Red Pill Analytics, Inc. RPAI Public 2992762 05/02/2013 12:00 AM UPDATE
Red Pill Analytics, Inc. RPAI Public

40
NVL (!
LEAD ( fnd_commit_date ) over !
!! ( PARTITION BY id !
!! ORDER BY fnd_commit_date ),!
to_date( '12/31/9999','mm/dd/yyyy' )!
)
NAME FND_SCN FND_COMMIT_DATE FND_EXPIRE_DATE FND_DML_TYPE FND_CURREN
TRed Pill Analytics 2992758 08/20/2012 12:00 AM 03/13/2013 12:00 AM INSERT N
Red Pill Analytics, LLC 2992760 03/13/2013 12:00 AM 05/02/2013 12:00 AM UPDATE N
Red Pill Analytics, Inc. 2992762 05/02/2013 12:00 AM 12/31/1999 12:00 AM UPDATE Y

41
CASE!
WHEN ( RANK() over (PARTITION BY id !
! ! ORDER BY fnd_commit_date desc )) = 1!
THEN 'Y'!
ELSE 'N'!
END
NAME FND_SCN FND_COMMIT_DATE FND_EXPIRE_DATE FND_DML_TYPE FND_CURREN
TRed Pill Analytics 2992758 08/20/2012 12:00 AM 03/13/2013 12:00 AM INSERT N
Red Pill Analytics, LLC 2992760 03/13/2013 12:00 AM 05/02/2013 12:00 AM UPDATE N
Red Pill Analytics, Inc. 2992762 05/02/2013 12:00 AM 12/31/1999 12:00 AM UPDATE Y

Model-Driven Development
• Start with thin requirements
• Sample reports
• SQL whenever possible
• Annotated discrepancies
• Development against the
Foundation Layer
• Top-down approach
• Build empty BMM containing
logical “facts”, “dimensions”
and “hierarchies”
• Map physical sources to the
BMM
• Develop permanent, high-
impact dashboards
• No work in this iteration is
throw-away
43

44
• Start with thin requirements
• Sample reports
• SQL whenever possible
• Annotated discrepancies
• Development against the
Foundation Layer
• Top-down approach
• Build empty BMM containing
logical “facts”, “dimensions”
and “hierarchies”
• Map physical sources to the
BMM
• Develop permanent, high-
impact dashboards
• No work in this iteration is
throw-away

45
Simplification of the Data Model 
Integration of Disparate Data Sources 
Addition of Business Logic and Calculations

OBIEE is for star schemas
False

Logical Table Sources
(LTS) provide the
functionality for mapping
transactional schemas as
dimensional models.
!
Siebel initially acquired
nQuire and the
technology that would
become OBIEE to report
against Siebel CRM.

Model-Driven: Mapping Physical to Logical
50

Dragging and dropping tables from
the Physical Layer is the only way to
create logical tables in the Business
Model

OBIEE Gestures
53

OBIEE Gestures
54

Model-Driven: Dimension Tables
55
1
2
3

56

57

58

59

Model-Driven: Fact Tables
60
1
2
3

61

62

63

64

Model-Driven: EDW Content (Date Dimension)
65
1
2
3

66

67

68

69

Model-Driven: Initial Dashboard
70
Dimensional Prompts
Performance Tiles
Operational Metrics
Trending Information

ETL Development
•We us GoldenGate to
populate our Staging
layer
• Standard batch
• Micro batch
•Use Oracle Data
Integrator (ODI) to
transform our data to
meet business
requirements
•Need to decide what
flavor of GoldenGate to
use
• Extend our current
implementation
• Use ODI journalization
framework
72

Loading Access and Performance: Standard Approach
73
Staging Layer
Foundation Layer
Access & Performance

Loading Access and Performance: AgileAnalytics Approach
74
Staging Layer
Foundation Layer
Source System Access & Performance

74
GoldenGate handles
Staging and Foundation
layers
Staging Layer
Foundation Layer

74
ODI from Staging for
transactional table loading
GoldenGate handles
Staging and Foundation
layers
Staging Layer
Foundation Layer
ODI from
Foundation
for complex
calculations
and
integration

Oracle Data Integrator (ODI)
•Data Integration tool within Oracle
Fusion Middleware 12c
•Robust sources and targets
• Relational databases
• Essbase
• Flat file and XML
• Web services
• Big Data
•Declarative design
• Logical implementation
• Physical implementation
•ETL or E-LT
• Database as ETL engine
• Java Agents as ETL engine
75

Where Have We Seen This Before?
76

78

79

•Abstraction of
physical sources
using logical
entities
•Logic built into a
model instead of a
process
•Metadata-based
paradigm selection
•“Do the work once”
80

81
Abstraction of physical sources 
Logic built into Models not Processes 
Metadata-based paradigm-selection

ETL Development: Joins with Declaration
82

ETL Development: Joins with Declaration
83

ETL Development: Collateral from Model-Driven Development
84
1

84
1
2

84
1
2
3

84
1
2
3
WITH
SAWITH0 AS (select count(T2196.ID) as c1,
sum(T2196.AMOUNT) as c2,
concat(concat(T3853.FIRST_NAME, ' '), T3853.LAST_NAME) as c3,
T2196.LEAD_SOURCE as c4,
T2196.SALES_STAGE as c5
from
SUGARFND.ACCOUNTS T2041 /* Accounts (Standard) */ ,
SUGARFND.USERS T3853 /* Users (Account Owner Role) */ ,
SUGARFND.OPPORTUNITIES T2196 /* Opportunties (Standard) */ ,
SUGARFND.ACCOUNTS_OPPORTUNITIES T2221 /* Accounts Opportunities (Standard) */
where ( T2041.ASSIGNED_USER_ID = T3853.ID and T2041.ID = T2221.ACCOUNT_ID and T2196.ID = T2221.OPPORTUNITY_ID )
group by T2196.LEAD_SOURCE, T2196.SALES_STAGE, concat(concat(T3853.FIRST_NAME, ' '), T3853.LAST_NAME)),
SAWITH1 AS (select distinct 0 as c1,
D1.c3 as c2,
D1.c4 as c3,
D1.c5 as c4,
D1.c2 as c5,
D1.c1 as c6
from
SAWITH0 D1)
select D1.c1 as c1, D1.c2 as c2, D1.c3 as c3, D1.c4 as c4, D1.c5 as c5, D1.c6 as c6, D1.c7 as c7, D1.c8 as c8 from (
select D1.c1 as c1,
D1.c2 as c2,
D1.c3 as c3,
D1.c4 as c4,
D1.c5 as c5,
D1.c6 as c6,
sum(D1.c5) over (partition by D1.c3) as c7,
sum(D1.c6) over (partition by D1.c3) as c8
from
SAWITH1 D1
order by c1, c7 desc, c3 ) D1 where rownum <= 65001 4

ETL Development: Finished Product
85

86

87

88

89

Build Now, Refactor Later
92

93
Front-end
developers
aggressively
close stories any
way they can
Complex
calculations,
direct SQL, BI
Publisher,
Custom
JavaScript:
Nothing is off
limits
A new “Refactor”
Story is opened
for the Metadata
Developer to
consider this
content for
inclusion in the
RPD

94
Metadata developer
decides if the complex
front-end content is
viable
If viable, the
developer aggressively
solves the Refactor
Story using complex
calculations or opaque
views
The original Refactor
Story is reassigned to
the front-end
developer to have the
analysis point instead
to the new metadata
A new Refactor Story
is opened for the ETL
developer for any
complex
transformations that
may belong in the ETL
layer

95
ETL Developer
decides if the
transformations
are viable, and
if so, adds new
transformations
The Refactor
Story is then
reassigned to the
Metadata
developer to
rework the RPD
using new
database
attributes

96

Realtime Integration
99
ETL added latency
Pure batch: significant
Micro batch: medium
We lost our Realtime
capability when we added
our Access & Performance
layer

Realtime Integration
101
ETL added latency
Pure batch: significant
Micro batch: medium
We need to a way to get
that back utilizing the
Foundation layer
OBIEE
Fragmentation

Realtime: Foundational Federation
102

103

104

105

106

107
WITH
SAWITH0 AS (select T8974.OPPORTUNITY_COUNT as c1,
T8974.AMOUNT as c2,
T8939.INDUSTRY as c3,
T8981.NAME as c5,
T8981.OPPORTUNITY_ID as c6
from
EDW.OPPORTUNITY_DIM T8981 /* Opportunity Dim (Standard) */ ,
EDW.ACCOUNT_DIM T8939 /* Account Dim (Standard) */ ,
EDW.OPPORTUNITIES_FACT T8974 /* Opportunities Fact (Standard) */
where ( T8939.ACCOUNT_KEY = T8974.ACCOUNT_KEY and T8939.INDUSTRY = 'Technology' and
T8974.OPPORTUNITY_KEY = T8981.OPPORTUNITY_KEY and T8981.LEAD_SOURCE = 'Conference' and 'EDW' =
'Foundation' ) ),
SAWITH1 AS (select cast(1 as INTEGER ) as c1,
T2196.AMOUNT as c2,
T2196.ID as c4,
T2196.NAME as c6
from
where ( T2041.ID = T2221.ACCOUNT_ID and T2196.ID = T2221.OPPORTUNITY_ID and T2196.LEAD_SOURCE =
'Conference' and case T2041.INDUSTRY when ' ' then 'Not Applicable' else T2041.INDUSTRY end =
'Technology' and TO_DATE('2013-08-15 00:00:00' , 'YYYY-MM-DD HH24:MI:SS') < T2196.DATE_ENTERED ) ),
!
(continued...)

108
WITH
T8974.AMOUNT as c2,
T8981.NAME as c5,
from
'Foundation' ) ),
T2196.AMOUNT as c2,
T2196.ID as c4,
T2196.NAME as c6
from
!
(continued...)

108
WITH
T8974.AMOUNT as c2,
T8981.NAME as c5,
from
'Foundation' ) ),
T2196.AMOUNT as c2,
T2196.ID as c4,
T2196.NAME as c6
from
!
(continued...)
SAWITH2 AS ((select D0.c3 as c3,
D0.c4 as c4,
D0.c5 as c5,
'EDW' as c6,
D0.c6 as c7,
D0.c1 as c8,
D0.c2 as c9
from
SAWITH0 D0
union all
select case D0.c3 when ' ' then 'Not Applicable' else D0.c3 end as c3,
D0.c5 as c4,
D0.c6 as c5,
'Foundation' as c6,
D0.c4 as c7,
D0.c1 as c8,
D0.c2 as c9
from
SAWITH1 D0)),
SAWITH3 AS (select sum(D3.c8) as c1,
sum(D3.c9) as c2,
D3.c3 as c3,
D3.c4 as c4,
D3.c5 as c5,
D3.c6 as c6,
D3.c7 as c7
from
SAWITH2 D3
!
(continued...)

109
WITH
T8974.AMOUNT as c2,
T8981.NAME as c5,
from
'Foundation' ) ),
T2196.AMOUNT as c2,
T2196.ID as c4,
T2196.NAME as c6
from
!
(continued...)
SAWITH2 AS ((select D0.c3 as c3,
D0.c4 as c4,
D0.c5 as c5,
'EDW' as c6,
D0.c6 as c7,
D0.c1 as c8,
D0.c2 as c9
from
SAWITH0 D0
union all
select case D0.c3 when ' ' then 'Not Applicable' else D0.c3 end as c3,
D0.c5 as c4,
D0.c6 as c5,
'Foundation' as c6,
D0.c4 as c7,
D0.c1 as c8,
D0.c2 as c9
from
SAWITH1 D0)),
SAWITH3 AS (select sum(D3.c8) as c1,
sum(D3.c9) as c2,
D3.c3 as c3,
D3.c4 as c4,
D3.c5 as c5,
D3.c6 as c6,
D3.c7 as c7
from
SAWITH2 D3
!
(continued...)
BI Server does a union
between the
Foundation and
Performance layers
Union is eliminated
when the
“fragmentation
column” is used as a
filter

AgileAnalytics: Real-Time BI with
Oracle Business Intelligence, Oracle
Data Integrator and Oracle GoldenGate
110
Stewart Bryson
medium.com/@stewartbryson @stewartbryson linkedin.com/in/stewartbryson

AgileAnalytics: Agile Real-Time BI with Oracle Business Intelligence, Oracle Data Integrator and Oracle GoldenGate

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