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Warranty Warehouse

Warranty Warehouse. Warranty Data Loaded. Currently. Defined 13 new data items (March) Initial Delivery Date, PT Expiration Date, Prime Part Labor Hours, Use Years, Use Months, Net Exchange Price Additive, Model Year, Build Date Updating the new data daily

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Warranty Warehouse

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  1. Warranty Warehouse

  2. Warranty Data Loaded

  3. Currently • Defined 13 new data items (March) Initial Delivery Date, PT Expiration Date, Prime Part Labor Hours, Use Years, Use Months, Net Exchange Price Additive, Model Year, Build Date • Updating the new data daily • Half done updating new data for history • Finalizing ‘MB’ data mart • Attended DB2OLAP

  4. Warranty Data Data in the ESIS and Y124 Warranty systems (i.e. branch, claim no, dealer no, failure date, prime parts, replaced parts, part amts, labor amts, additives, taxes, other costs, etc.) Supplier Data Data from CPS and WISE (i.e. Prime part supplier id, branch & factory costs, Prime Part Cost, Part description, etc.) Warranty vs. Supplier Data

  5. PRIME_PART_DSC WISE part term code PRIMEPARTFCTRY_AMT (Parts + Allow + Labor + Allow + Other + Tax + (Travel * % of TOTAL_CLAIM_AMT) - (Deductible * % of TOTAL_CLAIM_AMT)) * Factory Cost Participation % PRIMEPART_PART_AMT (Parts + Allow + Tax) PRIMEPART_LBR_AMT (Labor + Allow + Tax) PRIMEPART_CLM_AMT (Parts + Labor (no allow or tax)) PURCHASED_PART_IND S=PQS Supplier, W=WISE PRIMEPART_SPLR_ID Check PQS Supplier then WISE (using Factory, Pt, Primary Suplr, Purch.Ind, dates) MULTIPLE_SPLR_IND If > 1 PRIMEPART_SUPL_IDs PRIMEPART_COST_AMT Standard cost from PQS Supplier PRIMEPART_BUYER_ID Buyer Id from PQS Supplier PRIMEPART_BUYER_NM Buyer Name from PQS Supplier PRIMEPART_BRCH_AMT (Parts + Allow + Labor + Allow + Other + Tax + (Travel * % of TOTAL_CLAIM_AMT) - (Deductible * % of TOTAL_CLAIM_AMT)) * Branch Cost Participation % LOCAL & US columns for each of the six AMT columns to allow different currencies Supplier Data

  6. Data Mart Data Marts are aggregated data (summarized) for fast analysis; also referred to as ‘cubes’ Time Organization Product

  7. Data Mart Dimensions • Dimensions are the highest levels in the data mart structure. They are distinct groups of related data. Examples are: • Geographic units (countries, regions, states, markets) • Business units (divisions, departments, legal entities) • Time unit (days, months, quarters, years) • Accounts and measures (sales, expenses, profits, units shipped)

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