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Managing Database Change with Data Modeling

Managing Database Change with Data Modeling. Bert Scalzo, PhD Bert.Scalzo@Quest.com. Bert Scalzo …. Database Expert & Product Architect for Quest Software Oracle Background: Worked with Oracle databases for over two decades (starting with version 4)

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Managing Database Change with Data Modeling

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  1. Managing Database Change with Data Modeling • Bert Scalzo, PhD • Bert.Scalzo@Quest.com

  2. Bert Scalzo … Database Expert & Product Architect for Quest Software Oracle Background: Worked with Oracle databases for over two decades (starting with version 4) Work history includes time at both “Oracle Education” and “Oracle Consulting” Academic Background: Several Oracle Masters certifications BS, MS and PhD in Computer Science MBA (general business) Several insurance industry designations Key Interests: Data Modeling Database Benchmarking Database Tuning & Optimization "Star Schema" Data Warehouses Oracle on Linux – and specifically: RAC on Linux Articles for: • Oracle’s Technology Network (OTN) • Oracle Magazine, • Oracle Informant • PC Week (eWeek) Articles for: • Dell Power Solutions Magazine • The Linux Journal • www.linux.com • www.orafaq.com 2

  3. Books by Bert … Coming in 2009 … Out Now … 2nd Edition Coming Soon 3

  4. Agenda • Define Database Change Management • Examine Common DBA Options for Managing Database Structural Changes • Examine the World of Modeling • Why Data Modeling Often Makes Sense as the Change Management Methodology • Examples using Toad Data Modeler

  5. Presentation Objectives To demonstrate: • Why a change management system is essential • That database structural changes can be accomplished in many ways • How data modeling tools can be an essential part of database change management • The advantages of data modeling in change management

  6. What is Database Change Management? …Ensuring that the source and target databases are in sync after changes to the environment: • Development database • Test database(s) • Production database • Distributed databases • Replicated databases Task is harder than you may think!

  7. Common Database Change Management Tasks

  8. Change Management Can Be Tedious… • Some database sync tasks require lots extra, indirect work (depending on the Oracle server version) • Drop table columns • Resize (i.e. shorten) table columns • And a few others … • Therefore, the DBA must • Be aware of all these scenarios • Write extended alteration scripts • E.G. copy table, copy data, rename, grants

  9. Common Change Management Options • Direct to Database • One Way DDL Scripts • One Way DDL Scripts + Version Control • Two Way DDL Scripts • Two Way DDL Scripts + Version Control • DB Schema Managers

  10. #1: Direct to Database • Pros: • Method of least resistance (i.e. easy) • Manually alter the database directly • Often use highly visual tools like TOAD DBA and OEM • Requires no extra tools (no extra $ or learn curve) • Cons: • The database is the Master • Totally ad-hoc database mods can be problematic • Extended alters require lots manual DBA time • History of structural changes is lost

  11. #2: One Way DDL Scripts • Pros: • An Old Timer’s favorite • Manually edit a Master DDL script • Requires no extra tools (no extra $ or learn curve) • Cons: • The DDL Script is the Master • Can forget & thus loose ad-hoc database mods • Extended alters require lots manual DBA time • History of structural changes is lost

  12. #3: One Way DDL Scripts + Version Control • Pros: • Manually edit a version of Master DDL script • Requires source control tool (free on UNIX) • Addresses history shortcoming of prior method • Cons: • The DDL Script is the Master • Can forget & thus loose ad-hoc database mods • Extended alters require lots manual DBA time

  13. #4: Two Way DDL Scripts • Pros: • Manually create DDL script based upon compare • Requires DDL extract tool (can be SQL script) • Cons: • The DDL Script is the Master • Can miss & over-ride ad-hoc database mods • Extended alters require lots manual DBA time • History of structural changes is lost

  14. #5: Two Way DDL Scripts + Version Control • Pros: • Manually create DDL script based upon compare • Requires DDL extract tool (can be scripts) • Requires diff & source control tools (free on UNIX) • Addresses history shortcoming of prior method • Cons: • The DDL Script is the Master • Can miss & override ad-hoc database mods • Extended alters require lots manual DBA time

  15. #6: DB Schema Managers • Pros: • Automatically create DDL script or directly apply selected changes (i.e. sync) based upon compare • Requires DB comp & sync tool, but then no other tools • Addresses history shortcoming of prior methods • Extended alters as easy as any other modification • Cons: • Disconnect between data models and database

  16. Data Modeling as a Change Management Methodology • Works off the meta-data documenting the business requirements (i.e. the true source code so to speak) • Requires using just one tool – the data modeling tool • Eliminates having multiple steps and branch points • Sometimes picture of what’s changed is more readily apparent and understandable than the alternatives • By very nature, keeps database & its requirements in sync!

  17. The World of Modeling … • Improve process efficiency • Define/document Bus. Processes - create correct and complete application requirements Business Process Modeling (BPM) • End-user • IT Partner/Liaison • Business Analyst • Support for all UML diagrams - Analyze requirements - Design application • Reverse/forward engineer code Object-Oriented Modeling (OOM - UML) • System Architect • System Analyst • App Developer • Identify all data & relationships - E/R (Entity/Rel’ship) diagrams - DB independent view • Business Rules? Conceptual Data Modeling (CDM – E/R) • Bus. Analyst • Data Architect • Data Analyst • DB-specific model • Reverse engineer existing DB • Create/Update DB from model • Data Warehouse Modeling Physical Data Modeling (PDM) • DBA • DB Developer • DB Architect

  18. #6: Data Modeling Tools Toad Data Modeler Toad Data Modeler • Pros: • Automatically create DDL script or directly apply selected changes (i.e. sync) based upon compare • Requires DB compare & sync tool, but then no other tools • Addresses history shortcoming of prior methods • Extended alters as easy as any other modification • No disconnect between data models and database

  19. Handle Like Programming Code

  20. Compare & Sync Combinations • Can compare & sync • Logical to Logical • Logical to Physical • Physical to Logical • Physical to Physical • Script to Physical • Database to Physical • Database to Database • Version to Version

  21. MOVIES Data Model

  22. Here we go … • “Best laid plans of mice and men”  • Real life is not as rigid or structured as we plan • Thus even when adopting a data modeling change management approach, two way compare/sync will still be critical (need to catch exceptions to method) • In following demo: • Will change some live database objects using Toad (e.g. alter table, create table, drop table) • Will change some source code or data modeling items (e.g. alter entity, create entity, drop entity) • See how modeling tool can find and fix these!

  23. Parting Thoughts • Data modeling can be an invaluable method for managing and addressing change in your DB environments • There are many other issues data modeling can address: • Modeling accurate business requirements • Transforming logical into physical models • Breaking data models into sub-models • Round-trip Engineering: • Conceptual -> Physical Model compare and sync • Physical Model -> Database compare and sync • Repository-based collaborative modeling • Horizontal and Vertical Partitioning • Data Warehousing (Star Schema design) • Object-Relational Mapping

  24. Questions and Answers … Thank You Presenter: Bert Scalzo: Bert.Scalzo@Quest.com

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