Building Product Master Data from a Data Quality Foundation. Jim Hart Senior Developer DataFlux

Transcription

1 Building Product Master Data from a Data Quality Foundation Jim Hart Senior Developer DataFlux

2 Proven Market Leader in Data Quality Recognized as a leading provider of data quality, data integration and MDM solutions Support key enterprise initiatives around Data Governance, Compliance, Risk Management and MDM Over 1000 customers worldwide Offices throughout the US, the UK, France and Germany Founded in 1997 Acquired by SAS in 2000 Operates as a wholly-owned subsidiary

3 Gartner: Data Quality Magic Quadrant 2008 Figure 1. Magic Quadrant for Data Quality Tools The Magic Quadrant is copyrighted 2008 by Gartner, Inc. and is reused with permission. The Magic Quadrant is a graphical representation of a marketplace at and for a specific time period. It depicts Gartner s analysis of how certain vendors measure against criteria for that marketplace, as defined by Gartner. Gartner does not endorse any vendor, product or service depicted in the Magic Quadrant, and does not advise technology users to select only those vendors placed in the Leaders quadrant. The Magic Quadrant is intended solely as a research tool, and is not meant to be a specific guide to action. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. This Magic Quadrant graphic was published by Gartner, Inc. as part of a larger research note and should be evaluated in the context of the entire report. The Gartner report is available upon request from DataFlux. Source: Magic Quadrant for Data Quality Tools, 4 June 2008, Ted Friedman, Andy Bitterer.

4 Yphise: Master Data Quality 2008 Source: Yphise ISO 9001:2000-Certified Independent Assessment of Software Products

5 Industry Recognition 2008 Datamation Product of the Year award in the Network and Systems Management category 2007 Best Data Quality and Profiling Software 2007 CRM magazine Market Winner for Data Quality (third consecutive year) 2007 DM Review Innovative Solution Award for Data Integration (awarded to DataFlux customer RLPTechnologies)

6 Enterprise Class Solutions

7 Reward Data Governance Maturity Model HIGH Master Data Management CDI LOW CRM/SRM BPM Integration ERP Data Warehouse PDM Risk SFA Data Silos LOW UNDISCIPLINED REACTIVE PROACTIVE GOVERNED People, Process, Technology Adoption HIGH 6

8 Master Data Management Product Roadmap Business Master Data Management Business Process Automation Solutions Accelerators Customer Product Employee Asset Supplier Location Data Quality Integration Platform Data Profiling Data Quality Data Monitoring Metadata Discovery Data Standardization Data Enrichment Data Integration UNDISCIPLINED REACTIVE PROACTIVE GOVERNED 7

9 The Data Quality Integration Platform 8

10 Analyze - Profiling Metadata Analysis Visualization Pattern Recognition 9

11 Improve Quality Data Input Result Input Result DataFlux Corp. DataFlux Corporation DataFlux DataFlux Corporation DataFlux Corporation DataFlux Corporation DataFlux CORPORATION DataFlux Corporation MR JOHN SMITH Mister Smith, John Johnny Smith Mr. John Smith Mr. John Smith Mr. John Smith DataFlux corporation DATAFLUX CORPORATION #(877) ext x ext ext 250 DataFlux CORPORATION DataFlux corporation Fortress LPB QT/Liter PE MP Standardization Input 25 retractable tape measure Item Measure value 25 Measure UOM Type Parsing Result Retractable tape measure Foot Retractable Casing Input Result 100 Main St Address Line 1 Wintersville, OH City/State/ZIP c/o Mr. Blake Care of Line Billy s Bakery Organization Billy Blake Individual Identification 10

12 DataFlux Flexible Identity Recognition CRM Johnny Smith Acme Inc 201 W Main St (232) [email protected] ERP Acme Mfg, Incorporated 201 W. Main Street Cary, NC Cust ID Web Web John Smith Acme Inc (232) [email protected] External Marcus J Smith Jr AMI [email protected] (232)

13 DataFlux Flexible Identity Recognition CRM Johnny Smith Acme Inc 201 W Main St (232) [email protected] Web Web John Smith Acme Inc (232) [email protected] Master Database Master ID Company Acme Manufacturing Inc First Name John Last Name Smith Address 201 West Main Street City Cary State NC Zip Work Phone Home Phone [email protected] Alt [email protected] System Primary Key Match Code CRM $L421$$$$M5R32$$$1Q ERP $L421$$$$M5R32$$$1Q Web 12 23$L421$$$$M5R32$$$1Q External $L421$$$$M5R32$$$1Q ERP Acme Mfg, Incorporated 201 W. Main Street Cary, NC Cust ID External Marcus J Smith Jr AMI [email protected] (232)

14 In a Perfect MDM World We would have only one representation for every unique item that we use. That representation would reference everything we need to know about that item to define its uniqueness and support operational and analytical systems. Data would be presented in a consistent format. Everyone in our organization would use the same data to identify that item. Processes would prevent duplicates from ever entering our systems. Master data about that item could be shared across the organization and with our business partners. 13

15 But What We Get Is # /4" Cap Screw #5-40 CAP SCREWS SOCKET HEAD CAP SCREW CAP SCREW SCREWS CAP 5/16x1/ CAP SCREWS; NON-STANDARD 92210A150 CAP SCREW; NON-STANDARD LOW HD CAP SCREW SCREW,CAP, 1/2"-13 X 2-1/2" 92865A808 hex cap screw 5/8 X; NONSTD M6 30MM Bttn Hd Cap Screw SCREW, CAP SOCKET HD SCREW,CAP-SCH CAPSCREW,.45MM SCREW, CAP HEX HD SCREW, CAP, BTNHD 0.75 SOCKET CAP SCREW 91247A806 Hex Cap Screw; NONSTD PFSCSH8C38-1 CAP SCREWS SCREWS-CAP Hex Cap Screw,Stl,M16x2x50mm,PK A262 CAP SCREW CAP SCREW 1/4"-20x3/4" Bttn Hd Cap Screw CAP SCREW 0-80 X 1/4 HEX CAP SCREW PK 10 SCREW,CAP,SOCKETHEAD 14

16 Data Classification Answering the question What is it? 16' tape measures TAPE MEASURE METRIC 10FT TAPE MEASURE, 25' Tape Measure,Blade 3/4 Wx12 ft L 1" X 25' TAPE MEASURE 27: Tools and General Machinery TAPE MEASURE - 16'; NON- 2711: Hand tools STANDARD : Measuring and layout tools TAPE MEASURES #G12-12 TAPE MEASURE : Tape measures MEASURING TAPE # #1: TAPE, MEASURING TAPE MEASURE TAPE MEASURES

17 Data Quantification Answering the question Which type is it? 16' tape measures TAPE MEASURE METRIC 10FT TAPE MEASURE, 25' Tape Measure,Blade 3/4 Wx12 ft L 1" X 25' TAPE MEASURE TAPE MEASURE - 16'; NON- STANDARD TAPE MEASURES #G12-12 TAPE MEASURE 10 MEASURING TAPE TAPE MEASURE TAPE MEASURES LENGTH UNKNOWN

18 Data Standardization Providing a Consistent Description 16' tape measures TAPE MEASURE METRIC 10FT TAPE MEASURE, 25 Tape Measure,Blade 3/4 Wx12 ft L 1" X 25' TAPE MEASURE TAPE MEASURE - 16'; NON- STANDARD TAPE MEASURES #G12-12 TAPE MEASURE 10 MEASURING TAPE TAPE MEASURE TAPE MEASURES TAPE, MEASURING: 16 TAPE, MEASURING: 10 TAPE, MEASURING: 25 TAPE, MEASURING: 12 TAPE, MEASURING: 25 TAPE, MEASURING: 16 TAPE, MEASURING: 12 TAPE, MEASURING: 10 TAPE, MEASURING: NOS TAPE, MEASURING: 16 TAPE, MEASURING: 25

19 DataFlux qmdm Creating Master Records 16' tape measures TAPE MEASURE METRIC 10FT TAPE MEASURE, 25 Tape Measure,Blade 3/4 Wx12 ft L 1" X 25' TAPE MEASURE TAPE MEASURE - 16'; NON- STANDARD TAPE MEASURES #G12-12 TAPE MEASURE 10 MEASURING TAPE TAPE MEASURE TAPE MEASURES TAPE, MEASURING: TAPE, MEASURING: TAPE, MEASURING: TAPE, MEASURING: TAPE, MEASURING: NOS 25 TAPE, MEASURING: 16 TAPE, MEASURING: 12 TAPE, MEASURING: 10 TAPE, MEASURING: NOS TAPE, MEASURING: 16 TAPE, MEASURING: 25

20 qmdm Master Repository Manager 19

21 Better, But Far From Perfect We would have only one record for every unique item that we use. That record would reference everything we need to know about that item to define uniqueness. Data would be presented in a consistent format. Everyone in our organization would use the same record to identify that item. Processes would prevent duplicates from ever entering our systems. Master data about that item could be shared across the organization and with our business partners.

22 Master Data: The Central Repository Master Data Purchasing Production Inventory Sales Suppliers

23 Service-Oriented Architecture Using DataFlux as a web service. Integrated into SAP, J.D. Edwards, Oracle, Ariba, other applications. All applications confirm master data through SOA Web Service calls.

24 Data Monitoring Identify trends in data quality metrics and data values Provide instant alerts for violations of pre-established business rules Quantify the costs associated with data quality and business rule violations Detect variances from cyclical runs Recognize when data exceeds pre-set limits, allowing you to immediately update this data by addressing the problems up front before the quality of your data declines

25 Questions? BUILDING PRODUCT MASTER DATA FROM A DATA QUALITY FOUNDATION 25