CompSci - Databases Flashcards

(44 cards)

1
Q

Database

A

Contains individual attributes about entities structued in various data structures.

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2
Q

Data Consistency

A

Ensures data is correct by controlling all occurences of the same data item to be updated dynamically.

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3
Q

Referential Integrity

A

Ensuring that foreign keys in tables refer to valid records/tables.

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4
Q

Data Redundancy

A

Ensures that data isn’t duplicated, wasting storage

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5
Q

Data Independence

A

Ensures the database is a separate system from its application so that changes are simpler to make.

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6
Q

Atomic Data

A

Attributes that are broken down into their fundamental parts to maximise flexibility.

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7
Q

DBMS

A

Database Management System

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8
Q

DBMS Tools

A

IQRAMS DUM

Integrity
Queries
Report generation
Access levels
Maintenance
Security

Dictionaires
User interface
Manipulation

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9
Q

Primary Key

A

Unique identifier for an entity

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10
Q

Compound Key

A

Unique identifier with >1 fields for an entity

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11
Q

Candidate Key

A

Any field other than a dedicated ID that can be used as a primary key.

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12
Q

Foreign Key

A

A primary key from another table to represent a relationship between the objects

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13
Q

Secondary Key

A

A second primary key, allowing users to access the data in some other order

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14
Q

Validation Techniques

A

Presence
Format
Length
Range
Lookup
Type

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15
Q

Verification Techniques

A

Double-Entry
Proof-reading

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16
Q

Big Data

A

A large & complex set of data collected from various sources that can be analysed using dedicated systems to find trends and patterns.

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17
Q

Predictive Analysis

A

An active process that relates past patterns and trends with potential future behaviour using modelling and machine learning to inform business risks or opportunities.

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18
Q

Data Warehousing

A

Storing big data sets in a centralised location from several sources that support analysis.

19
Q

Data Mining

A

A passive process that uses automated software to find patterns and relationships in large data sets.

20
Q

0NF

A

Flat file (contains a number of single tables w no links between them)

21
Q

1NF

A
  • Primary Key
  • Fields are atomic
  • No repeating rows / columns
22
Q

2NF

A

Attributes are dependent on only one primary key (split into tables).

23
Q

3NF

A

No transitive partial dependency (no composite keys).

24
Q

SQL - TABLE

A

CREATE TABLE [name] (
[var1] Int PRIMARY KEY
[var2] Varchar(n)
[var3] Varchar(n) NOT NULL
)

25
SQL - SELECT
SELECT */### FROM [table_name] WHERE [condition]
26
SQL - INSERT
INSERT INTO [table_name] VALUES [vars]
27
SQL - DELETE
DELETE FROM [table_name] WHERE [condition]
28
Purpose of SQL (Data Operations)
CSS TRIM but on databases Copying Searching Sorting Traversing Removing Inserting Merging
29
Normalisation Format
TABLE_NAME ([underscore]PK[underscore], extras, [overscore]FK[overscore])
30
IQRAMS DUM - Integrity
If any data is updated, linked data in other tables is updated
31
IQRAMS DUM - Queries
Can use code to perform commands to manipulate the database
32
IQRAMS DUM - Report gen.
Generate a visual represntation of database contents
33
IQRAMS DUM - Access lvls.
Users can only view the data they are granted to see
34
IQRAMS DUM - Maintenance
Ensures that data is stored properly in memory
35
IQRAMS DUM - Security
Data is protected with passwords or other methods
36
IQRAMS DUM - Dictionaries
Allows users to specify the structure of data and the metadata of each attribute (length, type...)
37
IQRAMS DUM - User Interface
Provides a visual representation of the database that users can interact with
38
IQRAMS DUM - Manipulation
CSS TRIM Copying Searching Sorting Traversing Removing Inserting Merging
39
Distributed Database Benefits
NASCRHp Network bottleneck Access can be limited Scalable Cost Resilient High performance
40
SQL - UPDATE
UPDATE [table_name] SET [table_var = var]
41
SQL - JOIN
SELECT */### FROM [table_name] JOIN [other_table] WHERE [condition]
42
Data Normalisation
Reorganising data in a database to make it more convenient, simple and flexible.
43
Distributed Processing
Loading programs and processes onto several devices that can be run independently and the output is compiled for the overall result
44
Distributed Processing Factors
Availability of equipment Availability of wide/local area network with high enough bandwidth Consideration of other tasks needed with network Security