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Oracle Hyperion Financial Data Quality Management

Considerations for a scaled, expedited and integrated approach on data quality

NCOAUG – Aug 15, 2008 1:20 – 2:00 pmMatthias Heilos, Pinnacle Group Worldwide

Introduction – Matthias Heilos

• Consultant at Pinnacle Group Worldwide

• Hyperion Expertise: Financial Data Quality Management, Essbase, Planning, Financial Management

• Prior: European IT & Management Consulting firm• Business Intelligence • EPM, Reporting, Planning, CRM

Agenda

• Introduction to FDM• Situation at a Fortune 100 client• Enhancing FDM to succeed• Automation / Integration• Useful features• Questions

What is FDM?

Oracle’s Hyperion Financial Data Quality Management • Is a transformation tool that feeds source level data to

consolidation, reporting, planning, and analytical applications

• provides an audit trail to the source financial data, helping ensure data integrity and mapping consistency that allows for easy reconciliation

• offers a consistent, end user-friendly environment that provides a uniform data collection process for all reporting units within the organization

Source: FDQM Quick Start Guide

FDQM Architecture

FDQM

Batch Loader (optional)

Import Formats Imported

DataValidated

DataExport

OutputFiles

Email Notification aboutData Quality (custom)

Unmappeditems?

Mappings

HFM

Ess-baseEss-base

Custom SystemCustom System

LoadCustom

DBCustom

DB

Source Files

Source Files

Oracle E-BusinessOracle E-Business

New

Situation at a Fortune 100 client

• M&A data integration of 11 locations

• Data volume: 3.5 million records (3 locations > 1 mio), time frame: 2 hours

• > 50 attributes• Complex multi-step

mappings• Automated and integrated

process

• Import and Mapping takes very long

• Too many attributes• Problems with DB

transaction handling• Multi-step mappings not

supported• Export fails due to large

amount of data

Requirements Problems faced

FDM can meet these

requirements using

Pinnacle’s FDM EnhancerFDM can meet these

requirements using

Pinnacle’s FDM Enhancer

Limitation: Too many attributes

• Import process step• Problem: too many attributes• Solution: “FDM Extension”

• Add row number to each record in source file• Separate dimensional data and attributes, process

attributes via FDM extension (custom attribute table)• Merge data during FDM Export based on row number

Internal Processes – Overview

ImportImport

Delete (optional) Import data

Map data

ValidateValidateFix mappings

(manual / auto-map)Reapply mappings

ExportExport

Export data

LoadLoad

Load data to target system Validate results

API Event Script

Expediting the Import process

• Import process step• Problem: takes very long

Import method

Description Time to process # rows1

100K 500K 1G

Import Format

Parse data file based on Import Format

1:09 6:03 13:10

Integration Script

Access data directly from source database, add FDM meta data in script

3:46 19:40 41:42

FDM Enhancer2

Pinnacle’s generic script for files and DB as data source

0:29 2:45 5:51

1 Tests performed in test environment, results may vary 2 Administration of “FDM Enhancer” available through User-Frontend (like Import Formats)

ImportImport

Delete Import data

Map data

Pinnacle’s Integration is at least 50% faster than out-of-the-box features

Expediting the Mapping process

• Mapping process step• Problem: takes very long

• Mapping types besides Explicit and Between:• IN: should not contain many values, rather split 1 large

mapping into several mappings with only few values• LIKE: convert * * to 1* 1*, 2* 2* etc. (map-thru)

ImportImport

Delete Import data

Map data

“FDM Enhancer” can significantly lower processing time • Map-Thru only on database level via custom script: no

mappings for map-thru dimensions• Mapping process entirely based on SQL script, no costly

update statements needed

“FDM Enhancer” can significantly lower processing time • Map-Thru only on database level via custom script: no

mappings for map-thru dimensions• Mapping process entirely based on SQL script, no costly

update statements needed

Enhancing the Mapping process

• Mapping process step• Problem:

• FDM does not support complex mappings (look up data from a database or several transformation steps), only hard-coded mappings based on information in source data file can be applied

• Solution:• Create custom mapping script for complex transformations

which will be applied after FDM’s mapping step

ImportImport

Delete Import data

Map data

12

Automation / Integration

Scheduler

FDMAutomation

Script

FDMExtension

FDMProcess

Wait

FDM*

Export /LoadFiles

EmailNotification

FDM StatusCheck if completeuntil timeout

Attribs

Dims

* Validation step skipped as integrated in enhanced Import step (including data quality checks)

Data Quality at a glance

Conclusion

• FDM was created to support data quality processes of financial data and integrate this data into Oracle’s EPM suite (Financial Management, Planning etc.)

• Supports Oracle’s “Management Excellence”• Using Pinnacle’s FDM Enhancer, handling large

amounts of data is possible. Tool selection should be primarily based on purpose – should the process be controlled by business user or IT

• Pinnacle Group Worldwide leads even large FDM data integration projects to success. FDM Enhancer offers a variety of pre-built features and methods to improve, enhance, scale and expedite FDM’s performance.

Questions

Scalability: Resource usage

• Delete process step• Problem: rollback segment in parallel mode

exceeded, too many transactions per commit cycle• Solution: Paging algorithm to delete subsets of data

in smaller transactions prior to FDM step

ImportImport

Delete (optional) Import data

Map data

Scalability: Export process

Problems: 1) ADODB Recordset exceeds 2GB memory limit

2) Extract routine is time-consuming (data mart adapter)

Solutions: 1) Paging algorithm to extract

2) Create dynamic SQL script, use DB Tool for extraction into delimited flat file

Useful features

• Data quality at a glance, including enhanced management information (see next slide)

• System integrity checks• Number of mappings per dimension and location• Compare mappings between periods

• Archive existing mappings• Custom logging, can be retrieved per day,

location, and process step as stored in database