CA ERwin Data Modeling's Role in the Application Development Lifecycle
Hybrid Data Protection DH010SN CA ERwin Data Modeling's Role in the Application Development Lifecycle Donna Burbank CA Technologies Insert customer/partner logo here
abstract A data model is a critical part of any application lifecycle, whether on-premise or in a Cloud environment. Using a model-driven architecture, core data assets can be reused to ensure consistency, increase quality and reduce the time and costs associated with the development and maintenance of applications. A data model helps: Create a visual inventory of source/target systems "Know what data you have" Communicate key business requirements between business and IT stakeholders - "Know what your data means" Define standards for reuse and consistency "Know your data is correct" 3
agenda The Challenge: Data + Application Complexity The Importance of Data in Application Development The ITKO and ERwin Solution: Optimizing the Application Lifecycle 4
Why Optimize the Application Lifecycle? How do I deliver the services my customers demand faster, better and cheaper? What if I could be sure that my customer-facing applications are delivered faster and perform exactly as expected? What if I could not only identify and resolve software issues in production up to 70% faster, but prevent the most costly problems before they get to production? What if I could automate and virtualize these software processes and labs to reduce labor and infrastructure costs by up to 30% or more over the next 12 months? What if I were able to have confidence in my data in order to make strategic decisions? Would this create a competitive advantage for my business?
Innovate or die. The Product is the entire brand and customer experience Service-oriented products are delivered late, over budget and with questionable quality WHY?
modern application development architecture Increasing Complexity New applications are composite and highly integrated CRM App Collaboration App External Infrastructure Portal Data Warehouse Financials Mainframe Web Interface Routing Service Partners BPMS Products ESB Virtual Service Messaging Service Web/WAP Interface SOAP Help Engine Cloud Business Rules Content Database Internal File System BI Tools EJB RMI Objects Most new application development is self-service and customer-facing making complexity exponential Most of the information developers need is outside of their control when they need it Limited predictability on how it s going to perform and where it s going to break
modern application development architecture Data is at the Core New applications are composite and highly integrated CRM App Collaboration App External Infrastructure Portal Data Warehouse Financials Mainframe Web Interface Routing Service Partners BPMS Products ESB Virtual Service Messaging Service Web/WAP Interface SOAP Help Engine Cloud Business Rules Content Database Internal File System BI Tools EJB RMI Objects Most new application development is self-service and customer-facing making complexity exponential Most of the information developers need is outside of their control when they need it Data is at the Core of Application Development Limited predictability on how it s going to perform and where it s going to break
the challenge: managing data complexity Too Much Data, Too Little Time More Data & Platforms to Support Most organizations have more than one database platform it s hard to be an expert in all The number of databases is growing, with more and more applications to support Many organizations are trying to integrate multiple systems The decision of what data to move to the Cloud is an important consideration Fewer Staff and Resources Organizations are cutting back on IT staff, making it difficult to manage these growing databases Skill sets for individual databases are very specialized. It is unrealistic (and expensive) to have multiple experts for all platforms
creating a data inventory Know what data you have Create a visual inventory of source and target systems Ensure that your data is consistent Build consistent database structures CA ERwin Data Modeler DB2 MySQL Oracle Sybase Oracle SQL Server SQL Server Sybase DB2 Teradata Teradata MS SQL Azure MySQL
the importance of data definitions What is a vehicle? We all know that, right?
why does a data model matter? The management of a leading US auto manufacturer wanted to know how their vehicle sales compared to the competition. The report showed that they sold 110% more vehicles than their competitors. Confident in their success, management decided to increase their production of their SUV and truck lines. A year later, they declared bankruptcy. What went wrong?
know what your data means What is a Vehicle? 13
the results of making business decisions based on bad data The reports given to the management team did not include Hybrid Vehicles, sales of which were increasing dramatically among their competitors. Why? The data model, and resulting database queries that build the report, were based on an incorrect business definition. The Result: The company s decision to increase Truck and SUV production, instead of Hybrid production, put them in bankruptcy a year later.
understanding your data puts power in your hands MS SQL Azure
optimizing the application lifecycle Data plays a critical role Portfolio Management Requirements Design Dev System Test Integration Test UAT Performance Test Deploy Monitor Application Lifecycle ERwin CA ERwin Data Modeler Business Requirements Database Design Planning & Governance Service Virtualization LISA DevTest Cloud Manager Test Automation Defect Collaboration Continuous Validation Production & Support Platforms for agile composite app dev Requirements Management Test Management Defect Management IDE Source Code Management Build Static Code Analysis Code Security Application Lifecycle Management
LISA s virtual Test Data Management approach Service Virtualization methods from data Capture directly or import from transactions, databases, files Dynamically adjusts data for time or situational relevance Heal the data model from the live system when invalid or outdated Automatically Desensitizes live data for security and compliance
identify in-scope data with ERwin, then virtualize test data with LISA SaaS TDM Tool SQL Ops GDS SAP CRS GDS Input Data Booking Engine Oracle FF Using ERwin as a roadmap helps identify in-scope data
optimizing the application lifecycle continuous feedback Loop Portfolio Management Requirements Design Dev System Test Integration Test UAT Performance Test Deploy Monitor Application Lifecycle ERwin CA ERwin Data Modeler Business Requirements Database Design Planning & Governance Service Virtualization LISA DevTest Cloud Manager Test Automation Defect Collaboration Continuous Validation Production & Support Platforms for agile composite app dev Requirements Management Test Management Defect Management IDE Source Code Management Build Static Code Analysis Code Security Application Lifecycle Management
summary a few words to review Optimizing the Application Lifecycle helps: Increase Quality Reduce Development Time and Costs Data is a critical part of the Application Lifecycle Managing Data effectively increases both Technical and Business outcomes Combining ITKO and ERwin helps Optimize the Application Lifecycle, aligning data models with data analyzed in the virtual environment 20
Recommended Sessions SESSION # TITLE Date / Time DH001SN Data Management Focus Area Opening Session 11/14/2011 at 4:00pm AO001SS ITKO Introduction: Where Agility Takes Flight 11/15/2011 at 11:00am
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