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Ariba Spend Visibility Data Schema Training Tomkins May 17, 2010

Ariba Spend Visibility Data Schema Training Tomkins May 17, 2010. Keith Luers, C.P.M. SV Project Mgr. Agenda. Brief overview of Spend Visibility project as needed High level Data Schema overview, Scope & Process Suggestions Detailed review of Data Schema Data Overview Policy Questions.

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Ariba Spend Visibility Data Schema Training Tomkins May 17, 2010

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  1. Ariba Spend VisibilityData Schema TrainingTomkinsMay 17, 2010 Keith Luers, C.P.M. SV Project Mgr

  2. Agenda • Brief overview of Spend Visibility project as needed • High level Data Schema overview, Scope & Process Suggestions • Detailed review of Data Schema • Data Overview Policy • Questions

  3. Spend Visibility Overview • Any outstanding questions from the SV overview session?

  4. What is a “Source System”? • SV Source System • A standalone system that will be accessed to provide actual payment transactional data • The creation of a complete set of data may require feeds from multiple types of systems to augment the Accounts Payable data • Need a complete listing of source systems that need to be built along with who needs capability to load in data

  5. Scope of Extract – These questions need to be answered before an extract can be generated • What constitutes an Accounts Payable (AP) Spend Event (Approved Invoice entered for eventual payment; Invoice receipt, Invoice payment, PO receipt)? • *What types of transactions/spend should be included/excluded? • Invoice supported by PO • Invoice without supporting PO • P-Card • Expenses • Check Requests • Wire Transfers • Intra/Inter-Company • Payroll (should probably be excluded from extract) • Other Transaction Type(s) • Which ERP date field should be used to determine transactions that are in scope/out of scope? • Which timeframe should the extract include? • How should taxes be handled? • Is it necessary to flag Direct vs. Indirect spend? • Is it necessary to flag Internal vs. External Suppliers? • Are there specific requirements for enrichment we should be aware of upfront? *In Analysis, is it necessary to be able to track these transaction types?

  6. Suggested Extract Process 1. Define Business Requirements/Scope (see previous slide) 2. Develop Mapping Document (provided) • This document should include all the fields of the Ariba Data Acquisition Schema and mapped (if used) to the client ERP fields • Any filters used should be described • This document should be the basis for development of the script itself • Provide finalized document to Ariba for the review to ensure critical data elements are included in the extract files 3. Develop Script 4. Generate Test Files and upload to Spend Visibility site (narrow date range, this serves to ensure correct formatting/table joins, etc.) 5. Generate the production files with the complete set of the data in scope once any issues from Test Files are resolved

  7. Ariba Data Acquisition Schema • Provides a roadmap to create files in the proper format • Helps define the data to include for upload • Provides technical “do’s” and “don’ts” for the data extraction • Defines the various tables and fields, and the requirements for their successful creation • Is the primary and final reference for all matters relating to data extraction and file creation

  8. Data Schema Relationships • Schema consists of one main table (Invoice2.csv) and many supporting tables • Enrichment is based on Invoice data and supporting tables used to define attributes of invoice data

  9. Data Flow • List of tables/files include: • "Invoice2.csv" for AP transactions table • “PO2.csv” for Purchase Order Line transactions • “Account.csv” for General Ledger accounts table • “CompanySite.csv” for Facility/Site location Master table • “Contract.csv” for Contract Master table • “CostCenter.csv” for Cost Center Master table • “CostCenterMgmt.csv” for Cost Center management hierarchy • “ERPCommodity.csv” for the Material Code Master table • “FlexDimension1.csv” for other related dimensions • “FlexDimension2.csv” for other related dimensions • “FlexDimension3.csv” for other related dimensions • “FlexDimension4.csv” for other related dimensions • “FlexDimension5.csv” for other related dimensions • “FlexDimension6.csv” for other related dimensions • “Part.csv” for Item Master table • “Supplier.csv” for Supplier Master table • “User.csv” for the Buyer Master table • “CurrencyMap.csv” for mapping Currency codes • “UOMMap.csv” for Item Master table

  10. Data Flow • Data extracts from each data source will be loaded from a single ZIP file named for the source system. • The zip file should include individual text files named exactly as listed • Files uploaded as .csv can have any name

  11. Data Field Conventions • Each file must have a header row containing the data element field names as specified in the Data Acquisition document • Data must be provided in comma delimited format • Double-quotes (“) are used at the beginning and end of each field • Double quotes imbedded within the data should be escaped with second double quotes (“replaced with “”) • The comma delimiter is still necessary where no information is available – null values

  12. Example of Field Conventions

  13. Data Field Types • ‘Text’ for alphabetic (a-z and symbols including the special characters and digits) • ‘Number’ for digits 0 to 9 • Negative values are expressed with negative sign (“-“) preceding the number • Use a period (“.”) to denote decimal amounts • Currency marks ($ for example) should NOT be used in numbers • ‘Date’ in the format yyyy-mm-dd where yyyy, mm and dd are appropriate integer values for year, month number and date number, respectively • Example: 2005-05-04 represents 4 May 2005 • Note: zero padding required for month and days

  14. Use Data Acquisition Schema documents for detailed Review / Notes TakingMapping guide & Schema instructions

  15. Common Data Collection Problems • Duplicate Records • Invalid joins between supporting tables • Different ID structure • Missing data on supporting table • Commas/Double Quotes in data • Incorrect date format (YYYY-MM-DD) • Schema mapping is not tracked • Huge impact if the extract is manual labor intensive • Prevents timely refreshes • Prevents new team members from coming up to speed quickly • Forget currency conversion load if applicable • Confirm Fiscal Year settings in site

  16. Overview of Data Policies • The Ariba Project Manager will offer support and guidance when data changes are necessary, but due to data security policies, the Ariba Project Manager is not be able to manipulate or update data. It is the responsibility of the customer to make changes to their data. • Common Requests: • Populate Flex Field after deployment • Flag invoice and supplier type • Fixing hierarchy errors in data • Any data problems that cause load error

  17. Action Items • Complete list of needed source systems to have built in SV system and corresponding Tomkins associates who can load in data • Provide complete zip file • Presentations • Data Schema mapping • Data Schema instructions/file structure • Sourcing systems listing • Upload instructions

  18. QUESTIONS? • Keith Luers,C.P.M. • kluers@ariba.com • 719 260 6333

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