a case study on data modeling for sap applications
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Copyright © 2015 Boeing. All rights reserved.
Information Technology | Information Technology
Engineering, Operations & Technology
Information Technology
Data Modeling for SAPCase: Boeing Material Services
Lorin Yeaton
Senior Information Architect
Author, 7/10/2014, Filename.ppt | 1
Copyright © 2015 Boeing. All rights reserved.
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The Company
The Boeing Company
▪ Celebrating 100 years in 2016
▪ 2014 Revenue: 90.76 Billion
▪ A Top US Exporter
▪ Merged with McDonnell Douglas in 1997
▪ Commercial Airplanes-
▪ Models in Production 737, 747, 767, 777, 787
▪ Defense & Space- Notable Products:
– Delta IV, Airforce One, International Space Station, B1B Lancer, A-10 Thunderbolt ,F15, F18, Satellites, Launch Services
▪ See www.boeing.com
Copyright © 2015 Boeing. All rights reserved.
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The Presenter
Lorin Yeaton
▪ BS Construction Management
▪ MBA-Management Information Systems
▪ DAMA CDMP, Mastery Level▪ Data Management Core and Data Warehousing
▪ 7 Years Construction Management
▪ 29+ Years at Boeing▪ Program Planning
▪ Systems Analysis & Modeling
▪ Data Management
– Data Architect- specialization in Product Data Management
Copyright © 2015 Boeing. All rights reserved.
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The Organization
Commercial Aviation Services, Material Management
Spare Parts Sales
Supporting 20K+ MD and Boeing airplanes
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The Program
Replace 1990 IMS/COBOL SPARES system
▪ And dozens of surrounding, “bolted on” systems
Significant Regulatory Requirement (FAA)
▪ Support Type Design- Life of airplane + 50 years
▪ Parts must be certified- form 8130
Implement SAP
▪ First BCA SAP Implementation Experience
▪ Hired a System Integrator, but
Responsible for Data Conversion and Integration
▪ Integrations Number in Low Hundreds
Copyright © 2015 Boeing. All rights reserved.
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The Data Model Challenge
EA Requirement: Produce Logical Data Model
• Why? Understand the target for
• Conversion & Integration
• Data Governance
• Existence in a System of Systems
No Business Exposure to Data Models
▪ And Not That Much on IT Team
SAP OOB 95,000 tables
▪ How to identify relevant subset
▪ Rich Metadata Set exists in SAP, but
▪ Normal Reverse Engineering Tools Do Not Work
▪ Metadata tied up in application layer
Thankfully, Supportive Management
▪ Purchased SAFYR- extracts data from application- benefits
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The Process
Tools
▪ ER/Studio + SAFYR + Web publishing
Inputs
▪ Our SAP implementation (late dev, early test)
▪ Conversion/integration mapping – intent to use
Process
▪ Decide on Scoping strategy-
▪ Have to have some way to reduce the 95K tables down to the ones you care about.
▪ Using SAFYR you can select business areas, specific t-codes, application functions.
▪ We scoped mostly C&I mapping because we wanted to limit attributes too
▪ Install SAFYR
▪ Extract MD from SAP
▪ Scope (ss, func area, sys)
▪ Export MD to modeling tool (ER Studio)
▪ Decide on partitioning
▪ Subject Area (Workstream, e.g. OTC, PTP, HR)
– Facet (Information Object) (SAP calls them data entities)
– Entity/Table
– Attribute/Column
SAFYR DEMO
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Subject Area Model
Subject = Workstream, e.g.
▪ PDM (Product Data Management)
▪ OTC (Order to Cash)
▪ PTP (Procure to Pay)
▪ WM (Warehouse Management)
Facets = Information Objects within workstream, e.g.
▪ Material Master (a PDM Object)
▪ Customer Master (an OTC object)
▪ Purchase Order (a PTP Object)
▪ Storage Bin (a WM object)
Copyright © 2015 Boeing. All rights reserved.
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Workstream ModelEntity Relationship Diagram
Presentation Choices:
Hybrid logical-physical models
▪ Business and technical constructs extracted from SAP via SAFYR
▪ Imported into modeling tool
▪ Laid out manually- optimized for audience
▪ Note: The closer you stay to physical, the more automated is the process
One model per Workstream (subject)
Boundary boxes within subject are information objects
▪ These are “real” objects within the application, e.g. they are archivable objects
Within each information object, the normalized(ish) things that make up the information object
▪ Logical entity (usually also a table)
▪ Relationships between entities (usually also foreign keys)
▪ Attributes within each entity (usually also columns)
Copyright © 2015 Boeing. All rights reserved.
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Example ERD
Procure to Pay Workstream
▪ Next Page
▪ Big Picture with unreadable details
▪ Keep Calm. (Provided for context)
▪ Then, a (nearly) Readable Subset
▪ Purchase Order
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Published to Web Page
Our Data Model Web Page
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Possible Futures
Governing
▪ Change Management
▪ Data Governance
Leading
▪ System Integrators weave into their processes
Trailing
▪ The way it is now
Enterprise
▪ Multiple SAP implementations- one model (or 3)
Safyr summary
• Increase value from packaged applications
• Alleviate data complexity
• Exploit metadata in IM projects
Want to learn more?
• Visit www.silwoodtechnology.com
• Exploratory call
• Ask us for demonstration
• Request evaluation software
Roland BullivantSales and Marketing Director
rbullivant@silwoodtechnology.com@rolandatsilwood
www.silwoodtechnology.com
Nick PorterTechnical Director
nporter@silwoodtechnology.com
EMBARCADERO TECHNOLOGIESEMBARCADERO TECHNOLOGIES
ER/Studio® for Enterprise
Data Architecture
Ron HuizengaSenior Product Manager – ER/StudioRon.Huizenga@embarcadero.com
EMBARCADERO TECHNOLOGIES
Keeping pace with the rapid growth of data, change and compliance
Evolving Database
EcosystemsVolume, Velocity,
Variety
Agile Development
CyclesMaximizing IT
InfrastructureComplianceLimited
Resources
Data Professionals Need the Right Tools
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EMBARCADERO TECHNOLOGIES
• Accurate forward & reverse engineering
• Easy comparison and reconciliation of model changes
• Model version control with the central repository
• Full data design perspectives with logical & physical models
• Collaboration on models and metadata with Team Server
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EMBARCADERO TECHNOLOGIES
Thank you for your interest!
• Learn more about the ER/Studio product family: http://www.embarcadero.com/data-modeling
• Trial Downloads: http://www.embarcadero.com/downloads
• To arrange a demo, please contact: sales@embarcadero.com
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