Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

PJATK > WSI > Flashcards

WSI Flashcards

Introduction to Information

1
Q

refers to databases that don’t follow the traditional relational model used by SQL databases. The term can be interpreted as “non-SQL” or “not only SQL.” NoSQL databases offer more flexibility and natural data storage compared to SQL databases. NoSQL is a broader database management approach, while SQL is specifically a query language.

A

NoSQL

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

database

A

Key-value database
Document database
Wide-column database
Graph database

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

is information that’s set up for easy access, management and updating.

A

database

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

HISTORY: Early databases used flat files, which were unstructured and inefficient. Hierarchical and network models were developed to improve organization and relationships between data. The relational database model, introduced by Edgar F. Codd, revolutionized database management by using tables with rows and columns. His ideas led to the development of SQL (Structured Query Language).

A

flat files -> Hierarchical -> network -> relational (Edgar F. Codd)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

define what constitutes a true relational database management system. The rules cover various aspects of data storage, access, manipulation, and integrity.
While no commercial database fully implements all 12 rules, they
serve as an ideal standard for relational database systems.

A

Codd’s rules

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Pioneered relational concepts and SQL.

A

IBM System R

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Early commercial RDBMS inspired PostgreSQL

A

Ingres

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

First commercial RDBMS, gaining market dominance.

A

Oracle

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Popularized relational databases for microcomputers

A

BASE II

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Robust, flexible, and advanced features.

A

PostgreSQL

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Fast, simple, and widely used for web applications.

A

MySQL

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Fork of MySQL with additional features and optimizations

A

MariaDB

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Microsoft’s RDBMS for enterprise environments.

A

MS SQL Server

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

IBM’s RDBMS for high availability and scalability.

A

DB2

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

The central component that stores, manages,
and processes data.

A

Server

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Applications that interact with the database
by sending requests to the server.

A

Client

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Clients send requests to the server,
and the server processes them and returns results.

A

Communication

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Centralized management, improved security,
better resource allocation, and scalability

A

Benefits

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q
  • Developed by IBM researchers Donald D. Chamberlin and Raymond F. Boyce in the 1970s
  • Based on Codd’s relational model.
  • Designed for querying, manipulating, and managing data in relational databases.
  • Standardized by ANSI and ISO.
  • Widely used in RDBMS such as MySQL, PostgreSQL, Oracle, and Microsoft SQL
A

SQL - Structured Query Language

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q
  • Unique Features: AUTO_INCREMENT, LIMIT, REPLACE INTO
  • Use Case: Web development and applications
A

MySQL

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q
  • Unique Features: JSON/JSONB, WINDOW FUNCTIONS, RETURNING clause
  • Use Case: Complex queries, data integrity, high concurrency
A

PostgreSQL

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q
  • Unique Features: TOP, TRY-CATCH, MERGE, CTEs
  • Use Case: Enterprise-level applications, Microsoft ecosystem
A

Microsoft SQL Server (T-SQL)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q
  • Unique Features: CURSORS, TRIGGERS, SEQUENCES, procedural extensions
  • Use Case: Large enterprises requiring complex business logic
A

Oracle SQL (PL/SQL)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q
  • Unique Features: Single-file database, limited concurrency, no user management
  • Use Case: Embedded systems, mobile apps, small-scale software
A

SQLite

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q
  • Unique Features: Virtual columns, storage engines, compatibility with MySQL
  • Use Case: Performance-enhanced alternative to MySQL
A

MariaDB

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q
  • Unique Features: PureXML, multi-dimensional clustering, RCAC
  • Use Case: Large organizations requiring high throughput and complex queries
A

IBM DB2

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
27
Q

For text fields like Title, Author, Category, ISBN, Publisher, Address, and Phone.

A

NVARCHAR(200):

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
28
Q

The process of organizing data to minimize redundancy and ensure data integrity.

A

Normalization

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
29
Q

A set of rules for achieving normalization.

A

Normal Forms

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
30
Q

Data in a row-column intersection should be indivisible

A

Atomicity

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
31
Q
  • Unique Identifier: A primary key uniquely identifies each record.
  • Avoid Changing: Primary keys should be stable to prevent errors.
  • Artificial Primary Key: A generated integer or other unique value.
A

Primary Key

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
32
Q

Separate Related Data: Move columns related to other entities into separate tables (e.g., publisher, author).

A

Redundancy

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
33
Q
  • Foreign Key Constraints: Automatically enforce referential integrity by ensuring foreign key values point to existing primary key values.
  • Data Integrity: Prevent orphaned records and broken references.
A

Constraints: Ensuring Data Integrity

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
34
Q
  • SQL is declarative, allowing users to specify the desired result without detailing the process.
  • This simplifies querying and makes it efficient for large datasets.
A

Declarative Language

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
35
Q
  • Different database systems have their own SQL dialects with variations in syntax and features.
  • This provides flexibility and optimization for specific use cases.
A

SQL Dialects

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
36
Q
  • DQL (Data Query Language): Retrieves data.
  • DDL (Data Definition Language): Defines database structure.
  • DML (Data Manipulation Language): Modifies data.
  • DCL (Data Control Language): Manages permissions and security.
  • TCL (Transaction Control Language): Manages transactions.
A

SQL Sublanguages

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
37
Q
  • DQL (Data Query Language):
A

Retrieves data.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
38
Q
  • DDL (Data Definition Language):
A

Defines database structure.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
39
Q
  • DML (Data Manipulation Language):
A

Modifies data.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
40
Q
  • DCL (Data Control Language):
A

Manages permissions and security.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
41
Q
  • TCL (Transaction Control Language):
A

Manages transactions.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
42
Q
  • CREATE TABLE: Creates a new table.
  • ALTER TABLE: Modifies an existing table.
  • DROP TABLE: Deletes a table.
  • CREATE INDEX: Creates an index for faster querying.
  • DROP INDEX: Deletes an index.
A

DDL Statements

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
43
Q

Returns rows that have a match in both tables.

A

INNER JOIN

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
44
Q

Returns all rows from the left table, along with matching rows from the right table.

A

LEFT JOIN

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
45
Q

Returns all rows from the right table, along with matching rows from the left table.

A

RIGHT JOIN

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
46
Q

Returns all rows from both tables, whether or not they have a match in the other table.

A

FULL OUTER JOIN

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
47
Q

Types of Data Models

A

Hierarchical Data Model
Network Data Model
Relational Data Model
Entity-Relationship (ER) Model
Object-Oriented Data Model
NoSQL Data Models

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
48
Q
  • Tree-like structure with parent-child relationships.
  • Limited flexibility due to rigid hierarchy.
A

Hierarchical Data Model

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
49
Q
  • Extends hierarchical model with multiple parents per child.
  • Complex and challenging to manage.
A

Network Data Model

50
Q
  • Organizes data into tables with rows and columns.
  • Most widely used model for structured data.
  • Offers simplicity, flexibility, and powerful querying capabilities.
A

Relational Data Model

51
Q
  • Visual representation of entities and their relationships.
  • Used for database design and understanding data structures.
A

Entity-Relationship (ER) Model

52
Q
  • Represents data as objects with properties and methods.
  • Supports complex data structures and object-oriented programming paradigms
A

Object-Oriented Data Model

53
Q
  • Designed for large-scale, unstructured or semi-structured data.
  • Includes various types:
    o Key-value stores
    o Document databases
    o Columnar databases
    o Graph databases
  • Offers scalability, high performance, and flexibility for specific use cases.
A

NoSQL Data Models

54
Q

o Composed of rows and columns forming cells.
o Cell addresses are unique (e.g., A1).

A
55
Q

o Number Formats

A

General, Number, Currency, Accounting, Date, Time, Percentage, Fraction, Scientific, Text.

56
Q

Adjusts based on cell position.

A

o Relative

57
Q

Remains constant (uses “$”).

A

o Absolute

58
Q

Combines relative and absolute addressing.

A

o Mixed

59
Q

Ideal for visualizing mathematical functions and trends.

A
  • Scatter Charts
60
Q

Effective for displaying proportions and percentages.

A
  • Pie Charts
61
Q
  • Suitable for plotting functions with x and y values.
  • Requires careful data entry and series selection.
  • Can plot multiple functions on the same chart.
A

Scatter Charts:

62
Q
  • Represent data as proportions of a whole.
  • Customize with data labels, legends, and 3D effects.
A

Pie Charts:

63
Q

: Powerful tool for data analysis and summarization.

A

Pivot Tables

64
Q
  • Creation:
    o Select data in the spreadsheet.
    o Go to “Insert” > “PivotTable.”
    o Choose location and click “OK.”
A
65
Q
  • Fields:
    o Drag fields into “Row Fields,” “Column Fields,” “Values,” and “Filters” areas.
    o “Values” can be summarized (sum, average, count, etc.).
A
66
Q
  • Data Manipulation:
    o Filtering: Select specific categories or values.
    o Sorting: Arrange data in ascending or descending order.
    o Calculations: Perform calculations (sum, average, etc.) within the pivot table.
A
67
Q
  • Data Updates:
    o Refresh the pivot table to reflect changes in the source data.
A
68
Q
  • Data Preparation:
    o Ensure data is clean and organized (no empty rows/columns, consistent headers).
    o Convert text to numbers if necessary.
A
69
Q
  • Calculated Fields:
    o Create new fields within the pivot table using formulas.
    o Combine existing fields to derive new insights.
    o Enhance data analysis by adding custom calculations.
A
70
Q
  • Grouping:
    o Group data into ranges (e.g., sales ranges, date ranges).
    o Customize group intervals (equal or unequal).
    o Combine and ungroup groups as needed.
A
71
Q
  • Data Manipulation:
    o Sort, filter, and rearrange data within the pivot table.
    o Modify field names and formats.
    o Hide and show details for better readability.
A
72
Q
  • Advanced Techniques:
    o Use GetTableData function for more flexible formula creation.
    o Combine grouping with other pivot table features.
A
73
Q

is a graphical representation of a database that shows the entities (important objects), their attributes (descriptive details), and the relationships between them. It helps us understand the structure of a database before it is actually built.

A

An Entity-Relationship Diagram (ERD)

74
Q
  • Represent real-world objects or concepts (e.g., Human, Pet, Vet).
  • Shown as rectangles in the ERD.
A

Entities

75
Q
  • Provide details about the entities (e.g., Name, Surname, Pesel for
    Human).
  • Shown inside the entity rectangles.
A

Attributes

76
Q
  • Show how entities are connected (e.g., a Human owns a Pet).
  • Represented by lines connecting the entity rectangles.
A

Relationships

77
Q
  • A unique identifier for each entity record (e.g., Pesel for Human).
A

Primary Key

78
Q
  • A reference to a primary key in another entity (e.g., Owner_Pesel
    in Pet points to Pesel in Human).
A

Foreign Key

79
Q
  • A process of organizing the database to minimize data redundancy and improve data integrity.
A

Normalization

80
Q
  • A way to create new entities that inherit attributes from existing entities (e.g., Owner and Vet inherit attributes from Person).
A

Inheritance

81
Q
  • An entity used to represent a many-to-many relationship between two entities (e.g., Owns table to connect Humans and Pets).
A

Associative Entity

82
Q
  • When the same data is stored in multiple places in a database, which can lead to inconsistencies.
A

Data Redundancy

83
Q

Used to retrieve data from one or more columns.

A
  • SELECT
84
Q

select all columns

A

o SELECT * FROM table

85
Q

select specific columns

A

o SELECT column1, column2 FROM table

86
Q

Specifies the table from which to retrieve data

A
  • FROM
87
Q

Filters data based on conditions.

A
  • WHERE
88
Q

o WHERE column = value
o WHERE column > value
o WHERE column BETWEEN value1 AND value2
o WHERE column IN (‘value1’, ‘value2’)
o WHERE column IS NULL / IS NOT NULL

A
89
Q

Sorts the results.

A
  • ORDER BY
90
Q

Removes duplicate values.

A
  • DISTINCT
91
Q

o SELECT DISTINCT column FROM table

A
92
Q

Renames columns.

A
  • AS
93
Q

o SELECT column AS new_column_name FROM table;

A
94
Q

Concatenates strings.

A
  • ||
95
Q

o SELECT column1 || ‘ ‘ || column2 FROM table;

A
96
Q

Used for pattern matching.

A
  • LIKE
97
Q

contains pattern

A

o WHERE column LIKE ‘%pattern%’

98
Q

starts with pattern

A

o WHERE column LIKE ‘pattern’

99
Q

second character is pattern

A

o WHERE column LIKE ‘_pattern’

100
Q

Extracts the year from a date.

A
  • EXTRACT(YEAR FROM column):
101
Q
  • Use NVL() function to handle NULL values.
A
102
Q
  • SQL commands are case-insensitive (e.g., SELECT and select are the same).
A
103
Q

Combines data from two or more tables based on a related column.

A
  • JOIN
104
Q

o SELECT * FROM table1 JOIN table2 ON table1.column = table2.column;

A
105
Q

Adds new rows to a table.

A
  • INSERT
106
Q

o INSERT INTO table (column1, column2) VALUES (value1, value2);

A
107
Q

Modifies existing data in a table.

A
  • UPDATE
108
Q

o UPDATE table SET column1 = value1, column2 = value2 WHERE condition;

A
109
Q

Removes rows from a table.

A
  • DELETE
110
Q

o DELETE FROM table WHERE condition;

A
111
Q

(DDL):

A

Data Definition Language

112
Q

Creates a new table with specified columns and data types

A
  • CREATE TABLE
113
Q

o CREATE TABLE table_name (column1 data_type, column2 data_type, …);

A
114
Q

Modifies the structure of an existing table.

A
  • ALTER TABLE
115
Q

o ALTER TABLE table_name ADD column data_type;
o ALTER TABLE table1 ADD CONSTRAINT fk_name FOREIGN KEY (column1) REFERENCES table2(column2);

A
116
Q

Deletes an entire table.

A
  • DROP TABLE
117
Q

o DROP TABLE table_name;

A
118
Q
  • DML commands manipulate data within existing tables.
  • DDL commands change the structure of the database itself.
  • Use DML commands with caution, as they can permanently alter data.
  • Always test DDL commands carefully before executing them on a production database.
A
119
Q

Automatically generates a list of all the headings and subheadings within a document, along with their corresponding page numbers.

A

Table of Contents

120
Q

Creates a list of all the figures (images, charts, diagrams) used in the document, along with their captions and page numbers.

A

Table of Figures

121
Q

Creates a formatted list of all the sources cited within the document.

A

Bibliography

PJATK (8 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2025 Bold Learning Solutions. Terms and Conditions