2.3.1

Structuring Data - Records

Test yourself on Structuring Data - Records

Test your knowledge with free interactive questions on Seneca — used by over 10 million students.

Records

Structured data refers to any data that resides in a fixed field within a record or file so that it can be easily entered, stored, queried, and analysed.

Records

Records

  • Records are made up of fields.
  • For example, a person could be represented as a record where the fields include their name, age, and address.
Comma separated values (CSV)

Comma separated values (CSV)

  • One method of storing a record is using comma separated values.
  • Each record is put on its own line.
  • Each field is separated by a special character such as a comma.
Pros and cons

Pros and cons

  • Pros:
    • Very simple, text-based format.
    • Can be read by many applications.
    • Easy to use in programs.
  • Cons:
    • Inefficient for large datasets.
    • Can only store text data.
    • No built-in means of sorting or searching.
Jump to other topics
1

Computer Systems

1.1

Data Representation

1.1.1Binary Numbers1.1.2Negative Binary Numbers1.1.3Hexadecimal1.1.4Using Hexadecimal1.1.5Converting Binary & Hexadecimal1.1.6Converting Denary & Hexadecimal1.1.7Capacity1.1.8Calculating Capacity Requirements1.1.9Binary in Computer Systems1.1.10Data Compression1.1.11Run Length Encoding1.1.12File Formats
1.2

Data Transmission

1.2.1Packet Switching1.2.2Data Transmission1.2.3Universal Serial Bus (USB)1.2.4Parity Check1.2.5Checksum & Echo Checks1.2.6Encryption
1.3

Hardware

1.3.1Elements of Computer Systems1.3.2Types of Computer System1.3.3Von Neumann Architecture1.3.4The Fetch, Decode, Execute Cycle1.3.5Factors Affecting CPU Performance1.3.6Computational Logic1.3.7Input Devices1.3.82D & 3D Scanners1.3.9Code Readers1.3.10Solid State Storage1.3.11Magnetic Storage1.3.12Examples of Magnetic Storage1.3.13Optical Storage1.3.14Examples of Optical Storage1.3.15Types of Optical disk1.3.16Storage Requirements1.3.17Translation - Compilers1.3.18Translation - Interpreters1.3.19Translation - Assemblers1.3.20Acoustic Sensors1.3.21Flow Sensors1.3.22Gas Sensors1.3.23Humidity Sensors1.3.24Infrared Sensors1.3.25Level Sensors1.3.26Light Sensors1.3.27Magnetic Field Sensors1.3.28Moisture Sensors1.3.29pH Sensors1.3.30Pressure Sensors1.3.31Proximity Sensors1.3.32Temperature Sensors1.3.33Network Hardware
1.4

Software

1.4.1Operating Systems1.4.2Interrupts1.4.3High-Level Languages1.4.4Low-Level Languages
1.5

The Internet & its Uses

1.5.1The Internet1.5.2Uniform Resource Locators (URLs)1.5.3DNS1.5.4HTML1.5.5Cookies1.5.6Web Hosting1.5.7Digital Currency
1.6

Cyber Security

1.6.1Forms of Attack1.6.2Penetration Testing1.6.3Types of Malware1.6.4How Malware Spreads1.6.5Protecting Against Malware1.6.6Information Security1.6.7Structured Query Language (SQL) Injection1.6.8Firewalls1.6.9Authentication: User Access Levels1.6.10Authentication: Passwords1.6.11Social Engineering1.6.12Phishing1.6.13Denial of Service Attacks
1.7

Automated & Emerging Technologies

1.7.1Automated Systems1.7.2Robotics1.7.3Artificial Intelligence
2

Algorithms, Programming & Logic

2.1

Algorithm Design & Problem Solving

2.1.1Computational Thinking - Abstraction2.1.2Computational Thinking - Decomposition2.1.3Computational Thinking - Algorithmic Thinking2.1.4Pseudocode2.1.5Flow Diagrams2.1.6Interpreting, Correcting & Completing Algorithm2.1.7Correcting Algorithms2.1.8Completing Algorithms2.1.9Testing2.1.10Types of Testing2.1.11Test Plans2.1.12Validation & Sanitation2.1.13Authentication & Contingencies
2.2

Programming

2.2.1Programming Fundamentals - Variables & Constants2.2.2Programming Fundamentals - Comments2.2.3Programming Fundamentals - Input & Output2.2.4Data Types2.2.5Casting2.2.6Controlling Program Flow - Sequence2.2.7Controlling Program Flow - Selection2.2.8Controlling Program Flow - Iteration2.2.9Modularity - Subroutines2.2.10Modularity - Scope2.2.11Arrays
2.3

Databases

2.3.1Structuring Data - Records2.3.2Structuring Data - Databases2.3.3SQL
2.4

Boolean Logic

2.4.1Binary Systems2.4.2Logic Circuits2.4.3Truth Tables2.4.4Evaluating Expressions2.4.5Boolean Operators2.4.6End of Topic Test - Logic

Practice questions on Structuring Data - Records

Can you answer these? Test yourself with free interactive practice on Seneca — used by over 10 million students.

  1. 1
    Records are made up of:Multiple choice
  2. 2
    Which character separated each values of a CSV file?Multiple choice
  3. 3
    Cons of CSV filesFill in the list
  4. 4
    What are records composed of in structured data?Multiple choice
  5. 5
    How are records stored using comma separated values (CSV)?Multiple choice
Answer all questions on Structuring Data - Records

Unlock your full potential with Seneca Premium

  • Unlimited access to 10,000+ open-ended exam questions

  • Mini-mock exams based on your study history

  • Unlock 800+ premium courses & e-books

Get started with Seneca Premium

Arrays

Structuring Data - Databases