Data sets so large, fast-arriving or varied that conventional database tools cannot capture, store or analyse them.

Give an example of a Big Data source.

Sensor readings from a utility network, social media activity, or the click history of a large retail site.

Why do relational databases struggle with Big Data?

Much of it is unstructured, its volume exceeds one machine, and normalised joins are too slow at that scale.

What is a data warehouse?

A large store of historical data drawn together from several operational systems and organised for analysis rather than for transactions.

How does a data warehouse differ from an operational database?

The operational database supports many small current transactions; the warehouse holds history, is read far more than written, and is optimised for large queries.

WJEC A-Level Computer Science 601-5345-3

Hardware: Architecture, Memory and Storage

Topic overview Components of a computer system and how they connect Von Neumann architecture and the CPU The fetch-execute cycle Memory and caching Parallel processing Input and output devices and their uses Secondary storage, fragmentation and defragmentation

Networks and Data Transmission

Topic overview Serial and parallel transmission Simplex, half duplex and full duplex Multiplexing and switching Packets and the TCP/IP protocol stack Networks, standards and protocols Collisions and shared media Routing, addressing and the internet

Logic Gates and Boolean Algebra

Topic overview Logic gates and their truth tables Boolean notation and expressions Building and reading truth tables Boolean identities and rules Simplifying Boolean expressions De Morgan's laws Masking and clearing registers

Data Representation and Data Types

Topic overview Bits, bytes and words The binary number system Hexadecimal notation Character sets and storing characters Primitive data types and storage requirements Binary arithmetic and negative numbers Real numbers, truncation and rounding

Data Structures

Topic overview Data structures and data types One-dimensional arrays Two-dimensional arrays Manipulating arrays Records and fields Arrays of records Choosing a data structure

Organisation of Data: Files and Records

Topic overview Files, records and fields Fixed and variable length records Master and transaction files File access and organisation methods Sequential file access and update algorithms File security, backup and archiving Data validation and verification

Database Systems

Topic overview Flat files and the relational model Relational and other contemporary database systems Primary, foreign, composite and candidate keys Indexes and links between tables Entity relationship modelling Normalisation to third normal form The database management system, queries and user views

The Operating System

Topic overview The need for an operating system The kernel and process management Memory protection and the backing store The user interface between user and hardware Directory structures and file attributes Utility software Batch, real time control and transaction processing

Algorithms and Programs

Topic overview Defining and designing algorithms Variables, constants and identifiers Scope, subprograms and parameter passing Sequence, selection and repetition Mathematical and logical operations Standard algorithms: sorting, searching and compression Dry running, trace tables and test data

Principles of Programming

Topic overview Procedural programming Event-driven and visual programming Mark-up languages Object-oriented programming: objects, classes and methods High-level languages Low-level languages Choosing a language for a problem

Systems Analysis

Topic overview The systems life cycle and the feasibility study Methods of investigation Analysis, abstraction and decomposition Design and data flow diagrams Testing and changeover Maintenance Backup, recovery and documentation

Software Engineering and Program Construction

Topic overview Integrated development environments and their purpose Editors, syntax highlighting and code entry tools Debugging tools: breakpoints, stepping and watches Translation, source code and object code Lexical analysis and the symbol table Syntax and semantic analysis Code generation and optimisation

Types of Software System

Topic overview Off-the-shelf, bespoke and custom software Open source and proprietary software Computers in weather forecasting Computer aided design and manufacture Robotics in industry Computer generated graphics and animation Expert systems

Practical Programming

Topic overview Designing data structures: fields, records and data types Key fields and methods of access Validation of input data Designing routines with pseudocode Tracing code and test data Prototyping and evaluating a solution Annotated listings and readable code

Data Security and Integrity

Topic overview Dangers of holding files of personal data Levels of permitted access and access control Passwords and authentication Clerical procedures and write-protection Threats to computer systems Malicious and accidental damage to data Contingency planning and disaster recovery

Computing, Society and the Law

Topic overview Social and economic change from computing Computers and the nature of employment The digital divide and cultural change Environmental cost of computing Data protection and freedom of information law The Computer Misuse Act 1990 and computer crime Copyright, surveillance and professional codes

Advanced Data Structures and Logic

Topic overview Arrays in three dimensions Stacks and queues using pointers and arrays Linked lists using pointers and arrays Binary trees using pointers and arrays Hash tables and collision resolution NAND, NOR and Boolean simplification Masking, clearing registers and encryption

Recursion, Sorting and Searching

Topic overview Recursion Quicksort and merge sort Comparing sorting algorithms Big O notation and algorithm complexity Searching and shortest-path algorithms Traversal of data structures Data compression and its efficiency

Programming Paradigms and Translators

Topic overview Functional, declarative and imperative paradigms Classes, methods and object-oriented design Standardisation of computer languages Ambiguity in natural language and unambiguous notation Backus-Naur form and syntax diagrams Compilers, interpreters and assemblers Translation and execution errors

System Design and Human-Computer Interaction

Topic overview The waterfall approach Agile approaches Documentation and when it is produced Contemporary approaches to communicating with computers Natural language interfaces and spoken ambiguity Design review and validation Evaluating a computer based solution

Software Engineering Tools and Professional Practice

Topic overview Software tools for the software engineering process Software packages in systems analysis and specification Software packages in systems design Testing tools and testing strategies Program version management Program libraries and project management tools Codes of conduct and professional behaviour

Advanced Architecture and Assembly Language

Topic overview Components of contemporary architecture Von Neumann and Harvard architectures The fetch-execute cycle in detail Parallel processing and its limits Assembly language and instruction formats Voice input, command and recognition Mobile and wireless networking

Communication Networks and File Organisation

Topic overview Calculating data transfer rates Lowest-cost routing The internet as a global infrastructure Creating, organising and processing files Hashing algorithms Overflow and file reorganisation Choosing an organisation and a route

Number Representation and Floating Point

Topic overview Binary arithmetic Sign and magnitude representation Two's complement Floating point representation Converting between real numbers and floating point Truncation, rounding and accuracy Shifts, overflow and underflow

Databases and Distributed Systems

Topic overview Consistency, redundancy and data independence Relational organisation and normalisation Restructuring data into third normal form Entity relationship modelling Query languages and SQL Validation, verification and the DBMS Big Data, data warehousing and mining Distributed systems and distributed databases

Operating System Management

Topic overview Types of operating system Interrupts and interrupt handling Memory management and partitioning Buffering and data transfer Scheduling and process states Scheduling policies and priorities Evaluating operating system design

Software Systems and Applications

Topic overview The range of software system types Safety related and safety critical systems Computer control and automation The scope of automation in practice Expert systems The internet, intranets and search Selecting and evaluating a software system

Data Security, Cryptography and Attack

Topic overview Integrity problems in online updating The need for cryptography Symmetric and asymmetric techniques Classical ciphers and cryptographic algorithms Comparing cryptographic strength Biometric technologies Malicious software and its vectors Attacks, defence and penetration testing

Databases and Distributed Systems

Big Data, data warehousing and mining

3 things to know
A2 Unit 4

Overview

Big Data, data warehouse and data mining.

What you need to know

Answer each one before you reveal it.

Your recallNot started

Key term

Where does data at very large scale come from, why do relational databases struggle with it, and what is a warehouse for?

Key term

What is Big Data?

Key term

Name the three characteristics conventionally used to describe Big Data.

Questions from this subtopic

Each one with the model answer underneath.

1
What is Big Data?
Model answer
Data sets so large, fast-arriving or varied that conventional database tools cannot capture, store or analyse them.
2
Name the three characteristics conventionally used to describe Big Data.
Model answer
Volume, velocity and variety — how much there is, how fast it arrives, and how mixed its forms are.
3
Give an example of a Big Data source.
Model answer
Sensor readings from a utility network, social media activity, or the click history of a large retail site.
4
Why do relational databases struggle with Big Data?
Model answer
Much of it is unstructured, its volume exceeds one machine, and normalised joins are too slow at that scale.
5
What is a data warehouse?
Model answer
A large store of historical data drawn together from several operational systems and organised for analysis rather than for transactions.
6
How does a data warehouse differ from an operational database?
Model answer
The operational database supports many small current transactions; the warehouse holds history, is read far more than written, and is optimised for large queries.

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Hardware: Architecture, Memory and Storage

Networks and Data Transmission

Logic Gates and Boolean Algebra

Data Representation and Data Types

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Fetch, , execute.

decodecompilestore

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AEncryption is reversible.

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CA hash cannot be reversed.

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