Oracle Hyperion Financial Data Quality Management Considerations for a scaled, expedited and integrated approach on data quality NCOAUG – Aug 15, 2008.

Slides:



Advertisements
Similar presentations
Bulk Data API Nick Simha Technical Alliance Manager.
Advertisements

Centre Consulting Experts in Enterprise Performance Management Toshiba Medical Systems roadmap to optimized Performance Management –
End to End Bill Reconciliation with Telesoft Consulting Ltd. Vienna,
Little Used, but Powerful Features with GP Cathy Fregelette, CPA, PMP Practice Manager BroadPoint Technologies September 20, 2012.
1 of 27 DA1241 Archive Companies Last updated: March-2004 DA1241 Archive Companies.
1 tRelational/DPS Overview. 2 ADABAS Data Transfer: business needs and issues tRelational & DPS Overview Summary Questions? Demo Agenda.
Introduction to OWB(Oracle Warehouse Builder)
© 2010 TIBCO Software Inc. All Rights Reserved. Confidential and Proprietary. TIBCO Spotfire Application Data Services TIBCO Spotfire European User Conference.
An overview of Data Warehousing and OLAP Technology Presented By Manish Desai.
FINANCIAL REPORTING. Corporate Overview HQ out of Tampa, FL Midwest Regional Office, Indianapolis, IN West Regional Office, Denver, CO Oracle Gold Partner.
ENOVIA SmarTeam Data Loading Strategies
BY LECTURER/ AISHA DAWOOD DW Lab # 3 Overview of Extraction, Transformation, and Loading.
Enhancing Spotfire with the Power of R
New Features of Financial Reporting David Grande eCapital Advisors.
IT Analytics for Symantec Endpoint Protection
Chapter 13 The Data Warehouse
Introduction to Costing with PPM Amanda Oliver 2008 PPM User Conference.
SOFTWARE PRESENTATION ODMS (OPEN SOURCE DOCUMENT MANAGEMENT SYSTEM)
Designing the Data Warehouse and Data Mart Methodologies and Techniques.
FDMEE Data Integrations for Hyperion Financial Management
Clicks to Code Series “Data Loaders”.
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Introduction and Update: Oracle Hyperion Financial Close Management CON8536 Richard.
1 Components of A Successful Data Warehouse Chris Wheaton, Co-Founder, Client Advocate.
Data Conversion to a Data warehouse Presented By Sanjay Gunasekaran.
Data Warehouse Tools and Technologies - ETL
Automated Integrations An End-to-End Solution August 15, 2008.
“This presentation is for informational purposes only and may not be incorporated into a contract or agreement.”
Intro Informatica Productivity Pack Save Time and Money while Increasing the Quality of Your PowerCenter Deployment Louis Hausle.
Copyright 2003 Accenture. All rights reserved. Accenture, its logo, and Accenture Innovation Delivered are trademarks of Accenture. Data Migration in Oracle.
Christopher Jeffers August 2012
9/10/20151 Hyperion Enterprise 6.5 New Features & Functionality Robert Cybulski, CPA Finit Solutions.
DTS Conversion to SSIS Conversion Best Practices Mike Davis
Phone: Mega AS Consulting Ltd © 2007  CAT – the problem & the solution  Using the CAT - Administrator  Mega.
ISetup – A Guide/Benefit for the Functional User! Mohan Iyer January 17 th, 2008.
1 Data Warehouses BUAD/American University Data Warehouses.
OLAP & DSS SUPPORT IN DATA WAREHOUSE By - Pooja Sinha Kaushalya Bakde.
1 Reviewing Data Warehouse Basics. Lessons 1.Reviewing Data Warehouse Basics 2.Defining the Business and Logical Models 3.Creating the Dimensional Model.
- Ahmad Al-Ghoul Data design. 2 learning Objectives Explain data design concepts and data structures Explain data design concepts and data structures.
DB2 Universal Database Confidential | July 2012 | India Software Lab Click to add text © 2012 IBM Corporation An End to End Windows Automation Framework.
1 Categories of data Operational and very short-term decision making data Current, short-term decision making, related to financial transactions, detailed.
Master Data Management & Microsoft Master Data Services Presented By: Jeff Prom Data Architect MCTS - Business Intelligence (2008), Admin (2008), Developer.
1 Extending Drill Through to Oracle Transaction Level Detail from Hyperion Essbase.
Best Practices for Implementing
7 Strategies for Extracting, Transforming, and Loading.
© 2012 Saturn Infotech. All Rights Reserved. Oracle Hyperion Data Relationship Management Presented by: Prasad Bhavsar Saturn Infotech, Inc.
2012 © Trivadis BASEL BERN LAUSANNE ZÜRICH DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. HAMBURG MÜNCHEN STUTTGART WIEN Welcome November 2012 Einführung in.
Oracle’s EPM System and Strategy
SSIS – Deep Dive Praveen Srivatsa Director, Asthrasoft Consulting Microsoft Regional Director | MVP.
WHAT EXACTLY IS ORACLE EXALYTICS?. 2 What Exactly Is Exalytics? AGENDA Exalytics At A Glance The Exa Family Do We Need Exalytics? Hardware & Software.
Explore engage elevate Data Migration Without Tears Mike Feingold Empoint Ltd Tuesday 10th November 2015.
Can you do this in SmarTeam?
AA202: Performance Enhancers for Laserfiche Connie Anderson, Technical Writer.
Getting the Most outof EPM Converting FDM to FDMEE – What’s it all about? March 16, 2016 Joe Mizerk
What is the future of OFA?. Bryan Eckle FullNorth Technology Group Provide expert resources for Oracle Applications and Business Intelligence from scoping,
3 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. PeopleSoft General Ledger 9.2 New Features 9.2 Release New Features.
Welcome to all Salesforce Enthusiasts Once Again (18-JUN-16)
LOCO Extract – Transform - Load
Overview of MDM Site Hub
PowerMart of Informatica
IBM DATASTAGE online Training at GoLogica
tRelational/DPS Overview
Azure's Performance, Scalability, SQL Servers Automate Real Time Data Transfer at Low Cost MINI-CASE STUDY “Azure offers high performance, scalable, and.
Swimming Through the FDM to FDMEE Upgrade
Presented by: Jeff Moore – Artsyl Technologies, Inc.
2010 NorCal OAUG Training Day One Touch EBS Close to HFM Consolidation Integration of E-Business Suite and HFM Data and Metadata using EPMA Architecture.
ITAS Risk Reporting Integration to an ERP
Oracle’s Reporting Strategy
Best Practices in Higher Education Student Data Warehousing Forum
David Gilmore & Richard Blevins Senior Consultants April 17th, 2012
Integrated Statistical Production System WITH GSBPM
Presentation transcript:

Oracle Hyperion Financial Data Quality Management Considerations for a scaled, expedited and integrated approach on data quality NCOAUG – Aug 15, :20 – 2:00 pm Matthias 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 Data Validated Data Export Output Files Notification about Data Quality (custom) Unmapped items? Mappings HFM Ess- base Custom System Load Custom DB Source Files Oracle 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 RequirementsProblems faced FDM 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 Import Delete (optional)Import data Map data Validate Fix mappings (manual / auto-map) Reapply mappings Export Export data Load Load data to target systemValidate results API Event Script

Expediting the Import process Import process step Problem: takes very long Import method DescriptionTime to process # rows 1 100K500K1G Import Format Parse data file based on Import Format 1:096:0313:10 Integration Script Access data directly from source database, add FDM meta data in script 3:4619:4041:42 FDM Enhancer 2 Pinnacle’s generic script for files and DB as data source 0:292:455:51 1 Tests performed in test environment, results may vary 2 Administration of “FDM Enhancer” available through User-Frontend (like Import Formats) Import DeleteImport 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) Import DeleteImport data Map data

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 Import DeleteImport data Map data

12 Automation / Integration Scheduler FDM Automation Script FDM Extension FDM Process Wait FDM* Export / Load Files Notification FDM Status Check if complete until 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 Import 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