IST 318 Database Administration Lecture 1 What Is a DBA?

Topics DBMS and DB Applications Database, Data, and System Administration DBA Tasks Types of DBAs Test and Production

DB Applications Data is the lifeblood of computerized applications  Business today is data Using DBMS is the efficient way for data persistence and manipulation DBA is at the center of the development lifecycle

Database vs. DBMS Database  An organized store of data  Data can be accessed by names DBMS  Software that enable users or programmers to share and manage data

Enterprise IT Infrastructure – a big picture

Application Development Lifecycle

Data Administration Concentrate on the business aspects  Business lexicon  logical data model  Requirements gathering, analysis, and design Typical tasks include  Identifying and cataloging business data  Producing conceptual and logical data models  Creating enterprise data model  Setting data policies and standards Concerns more about metadata

Metadata Metadata is often described as data of data  Definition  Business name  Abbreviation  Type and length/accuracy  Domain, or range of valid values

Data Models – three levels Conceptual model  Outlines data requirements at a very high level  Describes data mostly in business context Logical model  Provides in-depth details of data types, lengths, relationships, and cardinality Physical model  Defines the way data is organized in physical medium

DBA vs. DA DBAs have to take care the first two levels if no DA roles are implemented in an organization

System Administration SAs are more concerned about the installation and setup of DBMS Typical SA tasks include  Underlying OS systems  DBMS Installation, modification, and support  System configurations enabling DBMS to work with other software systems

DBA Tasks Ensuring data and databases are useful, usable, available, and correct Typical DBA tasks include  DB design and implementation  Performance monitoring and tuning  Availability  DB security and authorization  Backup and recovery  Data integrity  DBMS release migration

DB Design & Implementation Understand and adhere to sound relational design principles  Relational theories and ER diagrams  DBMS specifics Understanding conceptual/logical models and being able to transform to physical DB implementation  Poor design can result in poor performance

Performance Monitoring & Tuning Performance = the rate at which the DBMS supplies info to its users Influenced by five factors  Workload  Throughput  Resources  Optimization  Contention

Availability Multifaceted process  Keep the DBMS up and running  Minimize the downtime required for admin tasks Technologies and up-front planning can help

DB Security & Authorization Ensure data is available only to authorized users by granting privileges to different (groups of) users Actions need to be controlled  Creating/altering DB objects and/or their structures  Reading/modifying data from tables  Starting/stopping DB and/or associated objects  Running stored procedures or DB ultilities

Backup & Recovery Be prepared to recover DB in the event of  Improper shutdown of DB applications, due to Software error Human error Hardware failure Types of recovery  Recover to current  Point-in-time recovery  Transaction recovery

Data Integrity Store the correct data in the correct way Physical integrity  domains and data types Semantic integrity  quality data with no redundancy Internal integrity  internal structures and code

Types of DBAs System DBA DB architect DB analyst Data modeler Application DBA Task-oriented DBA Data warehouse administrator

Test & Production At least two separate environments must be created for quality DB implementation  Testing (aka development)  QA (aka staging)  Production Differences  They should share the same configuration  They don’t need to be identical Testing DB may have only a subset of data

Multiple DB Environments