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Data Engineer > Course 4: Introduction to Relational Databases (RDBMS) > Flashcards

Course 4: Introduction to Relational Databases (RDBMS) Flashcards

1
Q

information model

A

abstract, formal representation of entities that includes their properties, relationships and the operations that can be performed on them

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2
Q

data models

A

concrete, specific and include details

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3
Q

hierarchal data model

A

organizes its data using tree structure with root of the tree being parent and followed by child nodes

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4
Q

relational data model

A

most used model. data stored in tables, providing logical data independence, physical data independence, and physical storage independence

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5
Q

entities

A

noun such as a person, place, or thing and represented by rectangle in ER diagram

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6
Q

attributes

A

properties or characteristics of an entity

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7
Q

relationship sets

A

represented by diamonds with lines connecting associated entities to show relationship and whether one-to-one, one-to-many, or many-to-many relationship

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8
Q

relation

A

another term for table

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9
Q

relation instance

A

table made up of rows and columns

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10
Q

degree

A

number of attributes (columns) in a relation

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11
Q

cardinality

A

number of tuples (rows)

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12
Q

single-tier database architecture

A

database resides on user’s system and access is often limited to a single user. useful for dev or testing or when database is embedded in a local application

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13
Q

client-server (2-tier) database architecture

A

resides on a remote server and users access it from client systems often through web page or local app. used for multi-user scenarios and typical for production environments

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14
Q

cloud database architecture

A

easy for users to access and dont have to maintain support infrastructure. client apps and users typically access through an application server layer or interface in the cloud. flexible and used for dev, testing, and full production environments

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15
Q

layers of a database management system software

A

1 data access layer
2 database engine layer
3 database storage layer
4 data access layer

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16
Q

3-tier database architecture

A

resides on a remote server and users access it through a middle-tier

17
Q

distributed architectures

A
  • mission critical, large scale workloads
  • high availability and scalability
  • databases distributed on cluster of servers
  • shared disk storage
  • shared nothing architecture - replication and partitioning
18
Q

replication

A

changes taking place on db server are replicated to one or more db serverse

19
Q

high availability replica

A

when the replica is within the same location as primary db. clients can be rerouted to replica in case of primary failure

20
Q

partitioning

A

separating large quantities of data into multiple logical subsets

21
Q

sharding

A

when partitions are placed on separate nodes in a cluster and has its own compute resources

22
Q

3 main classes of database users

A

1 data engineers
2 data scientists and business analysts
3 app developers

23
Q

common data engineer and data administrator task tools

A

gui or web based management tools
graphical tools
command line interfaces
APIs

24
Q

common data scientist task tools

A 
jupyter
r studio
zeppelin
SAS
SPSS
SQL
25
Q

common business analyst tools

A 
excel
ibm congos
power bi
tableau
microstrategy
SQL
26
Q

application development popular ORM (object relational mapping) frameworks

A 
ActiveRecord in Ruby apps
Django in python
Entity Framework in .NET
Hibernate in Java
Sequelize in JavaScript
27
Q

storage engine

A

component that handles the SQL ops on a table and defines what features that table can use

28
Q

PostgreSQL

A

free open source object-relational database management system

29
Q

MySQL

A

object-relational database that supports many operating systems, a range of languages for client application development, relational and JSON data, multiple storage engines, and high availability and scalability options

30
Q

Data Definition Language Statements (DDL)

A

used to define, change, or drop database objects such as tables

31
Q

Data Manipulation Language Statements (DML)

A

are used to read and modify data in tables. These are also sometimes referred to as CRUD operations, that is, Create, Read, Update and Delete rows in a table

32
Q

Common DDL statement types

A

CREATE, ALTER, TRUNCATE, and DROP.

33
Q

Common DML statement types

A

INSERT, SELECT, UPDATE, and DELETE

Data Engineer (3 decks)

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