Shorten each development cycle process, reduce errors and rework, and minimize impact

In this way, DBAs can adapt to a more agile and iterative approach to application development

Develop and promote abstract and reusable data objects without tightly coupling applications to data schemas

DBAs should promote database standards and best practices as requirements

Involving the DBA in the project definition phase helps ensure that the project methodology is used throughout the entire software development life cycle

Involve the DBA in the project analysis and design phases and clarify expectations for DBA tasks, standards, work results, and development work schedules

is a collection of stored data

Some large databases are also called "instances" and "schema"

Perform controlled access to a specific storage area through database software

An organization often uses different storage areas to execute multiple instances simultaneously

Each instance is independent from all other instances

Is a subset of database objects in a database or instance

Schemas are used to organize database objects into manageable collections

Usually a schema has a user and a specific access list for accessing the content of the schema

Common usage

Can also represent a collection of similar database structures

A single computer as part of a distributed database that processes or stores data

Common application interface API is usually used to call database functions

This way, an application can connect to different databases without the developer having to know which databases all functions may call.

Advantage

shortcoming

Production DBA

Application DBA

Process and Development DBA

Centralized database management single database

Distributed database manages multiple databases on multiple systems

Centralized databases store all data in one system in one place

All users connect to this system for data access

Centralization may be ideal for some data with limited access, but for data that requires large-scale, widespread use, centralized databases may be risky

federated database

Blockchain database

Providing computing, software, data access and storage services without requiring end users to know the physical location and related configuration of the service systems provided

Can be deployed locally or remotely

Implement database methods

Atomicity

Consistency

Isolation

Durability

In relational database storage, ACID related technology is the most important tool, usually using SQL interface

background

Basically Available

Soft State

Eventual Consistency

BASE-type systems are usually used in big data environments, such as large Internet companies and social media companies.

Record and store unstructured data

Theories proposed in the evolution of centralized systems toward distributed systems

The CAP theorem means that it is impossible for a distributed system to meet all the requirements of ACID at the same time.

The larger the system scale, the fewer requirements points it meets.

Distributed systems must trade off various properties (requirements)

theorem

The CAP theorem states that in any system that shares data, at most two of these three requirements can be satisfied.

The production environment refers to the technical environment where all production business processes occur

The production environment is very important, if it stops running, all business processes will stop, ultimately resulting in loss of business, while negatively impacting those customers who cannot access the service

System changes need to be developed and tested in a non-production environment before they are actually deployed to the production environment.

In non-production environments, problems caused by changes can be checked and dealt with in advance without affecting normal business processes.

Classification

The data storage system provides a way to encapsulate the instructions required to put data on disk and manage and process these data, so developers can simply use the instructions to operate the operating system

Databases are usually organized in three forms: hierarchical, relational, and non-relational. These classifications are not completely mutually exclusive.

Some database systems can simultaneously read and write data organized in relational and non-relational structures.

Hierarchical database can be mapped into relational table structure

Reused in early large-scale database management systems, its structural requirements are the most stringent.

Data is organized into a tree structure with enforced parent-child relationships

Each parent can have many children, but each child has only one parent

Relational database management system is called RDBMS

Relational databases are row-oriented

include

Store data as simple strings or complete files

Non-relational databases can be row-oriented, but they don’t have to be

NoSQL databases are increasingly used in big data and real-time WEB applications

include

The process of migrating data from an immediately accessible storage medium to a storage medium with lower query performance

Archived data can be restored to the original system for short-term use

Data that does not need to actively support application processing should be migrated to less expensive disks, tapes, CD/DVDs for archiving

It is wise to conduct regular recovery testing of archives to ensure that in the event of an emergency, unrecoverable surprises are avoided

The process of detecting changes in data and ensuring that information related to the changes is appropriately recorded

Usually refers to log-based replication, which is a non-invasive method of replicating data changes to the target without affecting the source.

CDC only sends changed content (incremental information), so the receiving system can update appropriately.

Detect and collect changes methods

Refers to the process of completely deleting data from storage media and rendering it unrecoverable

The primary goal of data management is that the cost of maintaining data should not exceed its value to the organization

Cleaning data reduces costs and risks

Considered outdated and unnecessary even from a regulatory perspective

If it lasts longer than necessary, it will become a burden

Clearing this data also reduces the risk of its misuse

Active replication

passive copy

Copy method

Database resilience is a measure of a system's tolerance for error conditions

A system is resilient if it can tolerate a high level of error handling and still work as expected

If you collapse when encountering unexpected conditions, you have no resilience.

Recovery type

Refers to how long the data remains available

Data retention planning should be part of the physical database design

Data retention needs also impact capacity planning

Failure to retain certain data for an appropriate period of time may result in legal consequences

Data can become a burden if kept longer than specified

It is a process of isolating a part of the database