Is there some truth on this?

USING COMMON DATA MODELS Track 2, Session #6, June 3, 2014 Alex Fung, Solution Lead – Enterprise, ACL & Manuel Coello, Senior Manager, Audit Analytics, General Electric

INTRODUCTION

Alex Fung Solution Lead – Enterprise Professional Services Group, ACL

Manuel Coello Senior Manager – Audit Analytics, General Electric

THE COMMON DATA MODEL Scattered Technology Landscape

How did we get here?

19

20-year history of our profession

1995 2000 2005 2010 2015

Audit Automation

Big Data CAATs ERM

Y2K

Audit Innovation

Self-Audit SOX

Fraud ERP Implementation

Regulations ERP Implementations

Acquisitions

Shared Services Outside Processors

Acquisitions Globalization

Diversification Remote Sites

THE COMMON MODEL

■ Traditional Approach x Number of ERPs you have

Reporting Follow-up

Results

Data Analysis

Analytics

Usability Custom

Fields

Prepare

Data Import

from ERP

Import

Reporting Follow-up

Results

Data Analysis

Analytics

Usability Custom

Fields

Prepare

Data Import

from ERP

Import

Reporting Follow-up

Results

Data Analysis

Analytics

Usability Custom

Fields

Prepare

Data Import

from ERP

Import

Reporting Follow-up

Results

Data Analysis

Analytics

Usability Custom

Fields

Prepare

Data Import

from ERP

Import Reporting Follow-up

Results

Data Analysis

Analytics

Usability Custom

Fields

Prepare

Data Import

from ERP

Import

Reporting Follow-up

Results

Data Analysis

Analytics

Usability Custom Fields

Prepare

Data Import

from ERP

Import

THE COMMON DATA MODEL

ACL

SAP

Oracle

MSSQL

Homegrown

Others

Prepared Data

THE COMMON DATA MODEL Tackle the fragmentation problem

Why creating a common data model?

Automation! – running scripts with the less amount of clicks One version of scripts – data import, data preparation, tests Simplified process – only need to update the data map for each data source Expandable – once the foundation is built, same code-base can be reused for other processes Data accumulation – ability to consolidate data from different systems

THE COMMON DESIGN MODEL Planning, Design and Considerations

CREATING A COMMON DATA MODEL

Data Acquisition

Save files within the same ACL project

Fill out mapping Prepare project

Fill out the name & fields with the ACL

Design

1| Create Analytics Framework 2| Required Fields 3| Create a mapping file 4| ACL Import Script

Create project and add files & templates

Process

Run Import Script

Run import script

Create Tables

Run import script

DESIGNING THE IMPORT SCRIPT

■ Useful ACL commands used in the process ■ SPLIT() – for text file source, the content may come in different lengths every time; use SPLIT() first instead of a SUBSTRING command

■ FTYPE() – to determine what data type is imported as, then you can apply proper commands to convert

■ SUBSTRING() – control the size of the data element

■ GROUP – in scripts only, process the same data file once (read it once) and perform a few tasks at the same time

DESIGNING THE IMPORT SCRIPT

■ User-Input ■ //PASSWORD – allow masked password to be entered, making the script more flexible

■ Ask for start and end dates, make it optional – user can confine the scope of data, optionally you can have the script automatically calculate a proper start/end date (last month for example) if the values are bypassed

■ Controlling complex input with external files such as Excel, but lock down the format

DESIGNING THE IMPORT SCRIPT

■ Flexibility ■ Use “variable substitution”, but not an overkill

■ Determine, at run time, the number of times a helper script needs to be re-executed based on the source input. Avoid hard-coding values if necessary

■ Controlling complex input with external files such as Excel, but lock down the format

CONTROL YOUR SCOPE! … or else it’s Alice down the rabbit hole

Sample – Demo using Excel for User Input

THANK YOU CONTACT ME AT ALEX_FUNG@ACL.COM

Questions?

Impact Awards Luncheon Crystal Ballroom 1-5