Data types:

The use of data types is widespread accross computing and IT, best described as a definition of data, there are many different datatypes. In this section we will review the data types and why they might be used over others.

Numeric

Numeric data type will be best suited to inputs and outputs that deal with whole numbers, ie 1,2,3 10,100,1000 and so on. This data type is oftern used in database and software programs for storing or using data like house numbers, ages (not date of birth)

Text

The text date type is used when dealing with a written word, phrase or sentence. It is capable of using symbols in most programs too.

• media

• geospatial

• temporal

• logical

Sources of data for organisations:

• internal:

o sales data

o marketing data:

▪ engagement data

o financial data

o employee data

o customer data

o usage data:

     ▪ traffic data

     • external:

o public (for example open data, repositories)

o government (for example data.gov.uk)

o suppliers

o competitors

o sector/industry

o market research

o repositories

Storing data:

• on-premises:

o internal databases

o file structures and formats

o hard drives:

       ▪ solid state drive (SSD)

       ▪ hard disk drive (HDD)

o portable storage devices

o file servers

o network-attached storage (NAS) devices

o storage area network (SAN)

• cloud storage:

o file storage

o object storage

o block storage

o elastic cloud/scalable storage

o cloud-based database services

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R3.1 The fundamental characteristics of data

• input - data inputted in preparation for processing

• storage - recording and retention of data on an appropriate format:

o create/store - retain data records for future use or compliance

o organise - restructure and rank data in a specific order

• processing - transforming data into meaningful output:

o analyse - business/digital insight through search queries/criteria

o update - ensuring data records are up to date

o remove - removal of data entries where appropriate

o integrate - integrate different sets of information together

• output - data generated by the information system:

o read/search - identify and find specific information

o insight - gain from processing to support decisions

• feedback loop - a system structure that allows output to influence future input

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R3.2 The fundamental functions of information systems and the application of data:

Concepts:

• hierarchical database model - data organised and accessed in hierarchy structure

• network model - data organised and accessed through nodes and links

• entity relationship model - data organised and accessed through use of relationships

Tools and their application:

• entity relationship diagram (ERD):

o used to design relational databases

• data flow diagram (DFD):

o level zero and level one

o visual representation of information flow within a system

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R3.3 The concepts and tools of data modelling.

Data entry:

• assign common data types to screen input boxes:

o numeric:

   ▪ integer

   ▪ float

   ▪ double

o text:

    ▪ strings

    ▪ char

o Boolean

    ▪ true/false

    • reducing risk of data entry errors:

o validation - check that user-entered data is sensible and in correct format

o verification - check that user-entered data is accurate

• privacy:

o compliance with standards and legislation for usage and storage

Data maintenance:

• user:

o editable data screens for permitted data changes

• system administrator:

o privileges to allow direct changes to data:

     ▪ user level

     ▪ user group level

     ▪ file level

Business resource considerations for data entry and maintenance:

• operational:

o time

o staffing

• financial:

o budget

o estimating and forecasting

• technological:

o hardware

o software

o storage

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R3.4 The concepts involved in data entry and maintenance.

Data formats:

• file-based structure:

o data held within one file

o consistent set of attributes, data types and validation

o context is held within the file

o data is referenced within the file

o data stored in flat file format

• directory-based structure:

o data held across multiple files

o contains multiple attributes, data types and validation

o context held within the file and the structure

o relational data is referenced across multiple files

o datasets are extracted from system and filtered

o data can be structured in a hierarchy system

o allows multiple data owners and sources

• relational database systems:

o data organised using normalisation to reduce redundancy

o data connect by relationships

o structured query language (SQL)/data processing language

o server-client implementation

Importance for analysis:

• easier to query

• easier to keep up to date

• supports with drawing conclusions

• allows sharing of data

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R3.5 Characteristics of data formats and importance for analysis.

Presenting data:

• reports

• digital slides

• webinars

• extended reality (XR):

o virtual reality (VR)

o augmented reality (AR)

• video

• sound

• animation

Visualising data:

• graphs (for example bar, line)

• charts (for example pie, funnel, area)

• data tables

• dashboards

• infographics

• maps

• heat maps

Suitability for application:

• formal or informal

• meeting requirements:

o brief

o audience

o level of technical knowledge and skills (for example use of technical terminology)

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R3.6 Methods of presenting and visualising data and their suitability for application.

• analysis:

o identifying trends and patterns

o monitoring performance:

     ▪ staff

     ▪ product/service usage

o forecasting (for example predictive analytics)

o informing decision making

• marketing:

o customer profiles

o targeting customers

o direct promotion

• operational management:

o monitoring and control of operations

o setting and monitoring of KPIs

o service improvement

Anonymous Assessment - Learners assess an anonymous piece of work containing deliberate mistakes against given success criteria.

R3.7 Applications of data within an organisation:

Types of data access management:

• user access controls:

o physical access

o remote access

o permissions

o authentication

• application programming interface (API):

o set of rules or specifications

o allows interface between software

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R3.8 Types of data access management across platforms within in a digital environment.

• role-based access control (RBAC) - restricts or allows access to resources based on the role of a user

• attribute-based access control (ABAC) - restricts or allows access based on attributes or characteristics

• mandatory access control (MAC) - restricts or allows access based on a hierarchy of security levels

• discretionary access control (DAC) - restricts or allows access based on resource owner preference

Anonymous Assessment - Learners assess an anonymous piece of work containing deliberate mistakes against given success criteria.

R3.9 Types and application of access control methods: