This document summarizes a presentation about implementing version 8.2.1 of the SunGard Oracle Operational Data Store and its impact on using Banner as a source system. The presentation explores technical differences with the new version, including moving to a new Oracle Streams data replication process to reduce impact on Banner and enable near continuous data feeds. It discusses managing the new replication methodology, including determining resource needs, addressing errors, patching, and upgrading considerations.
It symposium 2011-ods821_data_replication_04-11-2011
1. IT Symposium 2011
Tennessee Board of Regents
Operational Data Store – Data Replication
Presented by Greg Turmel & Pamela Clippard
Tennessee Board of Regents
Monday, April 11th 2011
Session 1.3
Time: 9:15a – 10:00a
2. ODS 8.2.1 Data Replication
Abstract:
This presentation will explore and discuss technical and
functional differences seen when implementing the SunGard
Oracle Operational Data Store version 8.2.1, its impact to
Banner as a source system, and the expectations for securing
quality data feeds into the Enterprise Data Warehouse
version 8.2.
The open discussion segment of the session will attempt to
answer many of the questions surrounding the expected
changes from current replication methodologies used in ODS
8.1 reporting processes.
3. ODS 8.2.1 Data Replication
Where is the value?
Data Replication services provide a core business process
for Research Reporting.
This version reduces the existing frustrations and high
impact on transactional systems (Banner).
It can be a key part of daily operations instead of Banner.
Value increases when used for longitudinal analysis and
trending for analytical decision support.
4. ODS 8.2.1 Data Replication
Managing Business Processes:
Defining the scope of the problem and support it with
research.
Leveraging trend analysis opportunities.
Decision Support based on key performance indicators:
evaluating available courses of action.
selecting a course of action.
implementing the selection.
Continuous improvement: Evaluating and monitoring
Achieving a “Total Quality management” model.
http://home.pacbell.net/johanes/Applied_research_journal.htm
5. ODS 8.2.1 Data Replication
Determining the resource scope will center on:
Time constraints on personnel or requester...
[e.g.] Institution, State, THEC/US Higher Ed.
The availability of data...
[e.g.] No current collection process defined.
The nature of the decision that must be made…
[e.g.] Student Retention/Graduation.
The value of the research in relation to its costs…
[e.g.] Funding.
6. ODS 8.2.1 Data Replication
Purpose: Financial responsibility is key to any mission and
should be a core strategy in data replication.
Governance: Workflows should involve approvals by
required personnel.
Structure: Reporting designs and access levels should
maintain the integrity of a reporting system.
Policies: Clarify and redefine budgetary policies and develop
additional accounting policies. [e.g.] SAN
Reference: http://www.nacubo.org/Business_Officer_Magazine/Current_Issue/February_2011/Put_Data_in_the_Drivers_Seat.html
7. ODS 8.2.1 Data Replication
Processes: Specific changes should result in more timely,
detailed financial reporting.
Culture: All changes should be made with due consideration of
the overall campus culture.
Infrastructure: Changes should support features and
functionality of both new/existing software tools.
Information: Changes to any structures should be based on
information‐timely relevant data provided in a format that
enables campus leaders to make informed decisions in response
to emerging trends.
Reference: http://www.nacubo.org/Business_Officer_Magazine/Current_Issue/February_2011/Put_Data_in_the_Drivers_Seat.html
9. Streams Administration: ODS 8.2.1
Database Server # A Database Server # B
Composite
User or process input
Views
MST*
Banner Transactional System
mappings
OAV: Object
Operational Data Store
Access Views
Tx-composite
Changes
Tx-composite
Complex Join
Redo.log
Groups Query
Queue Queue
Streams Capture Streams Apply
Propagation
Write
10. Streams Administration: ODS 8.2.1
Summary
Banner ODS 8.2
Production
ETL – Load, Delete,
• Banner Table Update • ODS Tables
Changes and • Replicated And Views
the Redo Logs Banner Tables
for Staging
Reporting
Streams Views & Tables
Capture
Streams Apply
Streams
Propagation
11. Replication Terminology
Streams Capture: Reads the database redo logs. Collects DML
and DDL changes that have been made on the
Banner source table
Streams Propagation: The process moves changes (LCR) from the
Banner source DB to the ODS target DB
Streams Apply: Takes the changes into the ODS stage tables.
Matches and updates the modified record in
the ODS target table
Error Queue: Low level streams data errors encountered can
be reviewed and reprocessed.
12. Replication Terminology
LCR —Logical Change Record Includes the old and new values from
the source table for each record
column replicated.
ODS Apply Error— An error recorded when the old
record value in the source table
cannot be matched in the target table
Re‐stage Process— A target table is dropped from the
ODS database which allows the
staging process to re‐create that
target table.
Note: When target tables are re‐staged – any insert_ods_change triggers for that
table need to be re‐created!
13. Transactional Source system (Banner)
Replication Advantages:
Banner [e.g.] SOKODSF, ODS Triggers, Views removed.
Banner data changes captured in redo logs.
Reduced impact to Banner operations [e.g.] CPU,
Memory, processes, back up schedules…
Replication Disadvantages:
Staged tables and Views/Materialized Views can no
longer be used for daily reporting in Banner.
Banner patching break/fit support changes radically.
New streams capture process to support.
14. Data Store - Target system (ODS)
Replication Advantages:
ODS objects are all on the down line system with minimal
exceptions. [e.g.] Blobs (img file), clobs… use a DB_LINK.
Minimized impact to student registration, grade posting,
or payroll [e.g.] Views supporting ODS are gone in
Banner.
Changes are propagated from Banner redo logs, not
triggers that interfere with other baseline processes.
No more bulk loads against Banner scheduled: impacting
Banner backups, Database Statistics jobs, or the data
quality in the loads due to a disabled trigger.
Faster refresh of ODS, near continuous feeds. [e.g.]
Smaller redo logs now equates to quicker refresh rates. 3
sets x 100 meg is less efficient (slower) than 6x50 meg.
15. Data Store - Target system: (ODS)
Replication Disadvantages:
Staged tables can’t be used for daily reporting.
[e.g.] Briefly contains only the changes.
Banner patching potentially breaks ODS objects.
[e.g.] Banner object changes are replicated automatically.
New streams propagation and apply processes.
[e.g.] New processes means new methods of support and
training.
Still requires a schedule for changes to load.
[e.g.] Data replicated by streams still requires a job to move
to ODS tables and materialized views.
Streams error logs to review: data left unapplied.
[e.g.] Requires intervention by IT to review, consult, apply.
16. Academic Outcome: Graduation - ODS
SGHE Banner Operational Data Store
Contains data about all awards sought
Description Details include program of degree GPA, total credits GOVERNMENT_ACADEMIC_OUTC
and/or earned by a student.
academic study, majors, earned etc. OME reporting view
One row per person per outcome
Key & Frequency
number.
PERSON_UID,OUTCOME_NUMBER
STATUS,STUDENT_LEVEL
Recommended Search Columns ACADEMIC_PERIOD_GRADUATION
PROGRAM,MAJOR,PERSON_UID
COLLEGE,DEPARTMENT,PERSON_UID
Target Column Business Definition Database Data Type Source Name Source Column
Academic period or time frame
ACADEMIC_PERIOD VARCHAR2(63) SHRDGMR SHRDGMR_TERM_CODE_STUREC
associated with this degree record.
ACADEMIC_PERIOD_DESC Academic period description. VARCHAR2(255) FUNCTION GOKODSF.F_GET_DESC
Academic period when graduation
ACADEMIC_PERIOD_GRADUATION VARCHAR2(63) SHRDGMR SHRDGMR_TERM_CODE_GRAD
requirements will be completed.
ACADEMIC_PERIOD_GRAD_DESC Academic period description. VARCHAR2(255) STVTERM STVTERM_DESC
Academic year associated with this
ACADEMIC_YEAR_GRADUATION VARCHAR2(63) SHRDGMR SHRDGMR_ACYR_CODE
graduation date.
ACADEMIC_YEAR_GRADUATION_DESC Academic year description. VARCHAR2(255) STVACYR STVACYR_DESC
Organization-oriented identifier for the
ADMINISTRATIVE_GROUP record used to determine access VARCHAR2(255) NA NA
authorization to this record.
Indicates whether the person has
APPLIED_FOR_OUTCOME_IND applied to officially receive this VARCHAR2(1) FUNCTION F_APPLIED_FOR_DEGREE
specific degree.
17. Preparing for Implementation
Evaluate your database configuration
Run the SGHE script: SGHE_BPRA_Check_Streams_Config.sql to
review the DB parameters
AQ_TM_PROCESSES = 1
shared_pool_sizemin. 256
streams_pool_sizemin. 256
global_names= true
Compatible 10.2 or higher
job_queue_processes>= 4
_job_queue_interval= 1
10g _CMPKEY_ONLY = ‘N’
11g COMPARE_KEY_ONLY = ‘N’
PARALLELISM = 0 (review defect correction 1‐H4R3OC)
If you are planning to use RAC configuration Streams propagation must be queue_to_queue
20. Patching and Upgrading
ODS ‐ Apply Errors
ORA‐01435: user does not exist ORA‐06512
at SYS.LCR$_DDL_RECORD
Fixed in patch P1‐BXVYD5_ODS8020113
Banner
Do not change the ODSSTG password in
Banner –It is used by the db_link from ODS
to Banner
23. Cloning with Streams turned on
Follow SunGard Higher Education’s recommended
procedure for cloning both Banner and ODS.
FAQ 1‐B2VYHB
How to backup and clone environments for ODS and
streams using RMAN
FAQ 1‐B2UMX7
Post clone steps of an ODS and Banner environment with
ODS streams
24. Cloning with Streams turned on
Cloning: both ODS and Banner environments at the same time
Cloning: the ODS target only
Cloning: the Banner source only
FAQ#: 1‐BM5JZA ODS 8.2: Steps to remove ODS stream objects
from a clone banner environment
Remember to re‐point the db_link to the correct database and also
complete a password rotation for your ODS and OWB component.
26. EDW: Star Schema Design
EDW Dimensional Model for Enrollment
The star schema is the simplest data warehouse schema. It is called
a star schema because the diagram resembles a star, with points
radiating from a center. The center of the star consists of one or
more fact tables and the points of the star are the dimension tables,
as shown in the following discussion.
The most natural way to model a data warehouse is as a star
schema, only one join establishes the relationship between the fact
table and any one of the dimension tables.
A star schema optimizes performance by keeping queries simple and
providing fast response time. All the information about each level is
stored in one row.
29. EDW : Star Schema Design
Enrollment Star Report: Target Reports – Description
WDT_ACADEMIC_STUDY
Academic Study Dimension Academic Study Dimension table provides
information for the program of study for the individual. This may be the data
on the admission application or the academic outcome record that identifies
the major subject area and sought award or degree, etc.. It uses the cleansing
rules in the EDW for the short and long descriptions.
WDT_DEMOGRAPHIC
Demographic Dimension Demographic Dimension table provides information
for the person that is consistent whether this is an employee, inquirer,
applicant, student or graduate at the institution. This information includes
gender, ethnicity, age range and family income range. It uses the cleansing
rules in the EDW for the short and long descriptions as well as the definition of
the ranges in this dimension.
30. EDW : Star Schema Design
WDT_ENROLLMENT_STATUS
Enrollment Status Dimension Enrollment Status Dimension table provides information
for the person that includes the time frame status of enrollment. This information
includes whether they intended to study full or part time, whether or not they are
currently enrolled and their current time status based on the institution defined rules.
It uses the cleansing rules in the EDW for the short and long descriptions.
WDT_STUDENT
Student Dimension Student Dimension table provides information for the person as the
student for the time frame. This information includes student population (New first
time, continuing, re‐admit, etc.), year of study or student class, residency (in district or
out) and campus affiliation. It uses the cleansing rules in the EDW for the short and long
descriptions.
31. EDW: Star Schema Design
WDT_TIME
Time Dimension Time Dimension table provides information on the time
frame for which the rest of the associated dimension and fact table are storing
the information in the star. The time dimension may be based either on a
calendar, academic, financial aid or fiscal year, The time frame will go down at
least one and sometimes two layers to periods and or sub periods of time. It
uses the cleansing rules in the EDW for the short and long descriptions.
WFT_ENROLLMENT
Enrollment Fact Table Enrollment Fact table provides measures that may
be compared and displayed based on the dimensions in this star schema. This
set of measures is stored per person per enrollment academic period